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The Indian Roads Congress
E-mail: [email protected]/[email protected]
Volume 43
4
Number 4
April 2015
ContentsISSN 0376-7256
From the Editor’s Desk - Some Essential Measures Warranted in Road Crash Prevention
Page
5
Technical Papers
Pedestrian Level of Service Criteria for Urban Off-Street Facilities of Mid-Size Cities Using Som in Ann
Rima Sahani
16
Founded : December 1934
IRC Website: www.irc.org.in
P.K. Bhuyan
Eco-Friendly Mulching - Enhancing Road Safety and its Aesthetics Through Value Engineering
B.K. Thakkar
22
Uttarakhand Deluge - Man - Made
W. Rahman
30
Tender Notice, NH Madurai
31
Tender Notice, NH Lucknow
32
Tender Notice, MORTH, NH Madurai
33
Tender Notice, NH Bareilly
Jamnagar House, Shahjahan Road,
New Delhi - 110 011
Tel : Secretary General: +91 (11) 2338 6486
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No part of this publication may be reproduced by any means without prior written permission from the Secretary General, IRC.
Edited and Published by Shri S.S. Nahar on behalf of the Indian Roads Congress (IRC), New Delhi. The responsibility of the contents
and the opinions expressed in Indian Highways is exclusively of the author/s concerned. IRC and the Editor disclaim responsibility and
liability for any statement or opinion, originality of contents and of any copyright violations by the authors. The opinions expressed in
the papers and contents published in the Indian Highways do not necessarily represent the views of the Editor or IRC.
From the Editor’s Desk
Some Essential Measures Warranted
in Road Crash Prevention
S.S. Nahar
Dear Readers,
The severity of road crash primarily depends upon degree of over-speed (driver’s state of mind)
and design of vehicle besides other contributory factors like road condition, weather, unexpected
hindrance(s) etc.
It is observed that in event of crash at speed of 30 km per hour or less, pedestrian have 90% chances
of survival but in case of crash at speed of 45 km per hour or more, the chances of survival remain
to be 50% or less.
With the improvement of technology, it has been realized that apart of frame and material type,
zoning is essential to enhance safety performance of vehicle. The crash worthiness of a vehicle
depends upon the structural strength and restraint system. In case of rollover, the strength of cabin
roof plays vital role. The restraint force per unit of weight (strength of roof) is the measure of the
strength to weight ratio. Managing the release of kinetic energy of vehicle in the event of crash
to minimize the intrusion is of vital importance in order to diminish chances of loss of life and
property.
In order to bring down the rate of fatalities, multiple air bags inside the vehicle, pre-tensioning
devices in the seat belt lock and tightening the belt webbing and besides foolproof testing for
frontal/side crash, rollover and whiplash of vehicles are recommended to be mandated. Besides,
in order to ensure the positioning of vehicle within safe driving zone, provision of crash barriers
and blinkers (preferably solar based) at hazardous locations like school, hospitals, zebra-crossings,
inter-changes, blind curves, ramps to fly-overs/high embankments etc. are recommended to be
mandated for identification through safety audit.
“A great man is different from an eminent one in that he is ready to be the servant of the society”.
Bharat Ratna Dr. Bhimrao Ramji Ambedkar
Place : New Delhi
Dated: 25th March, 2015
4
(S.S. Nahar)
Secretary General
INDIAN HIGHWAYS, April 2015
PEDESTRIAN LEVEL OF SERVICE CRITERIA FOR URBAN OFF-STREET
FACILITIES OF MID-SIZE CITIES USING SOM IN ANN
Rima Sahani* and P.K. Bhuyan**
ABSTRACT
Pedestrian Level of Service (PLOS) is a quantitative term which represents the quality of service of walking facilities. In this study
an attempt has been made to define levels of service provided by the off-street pedestrian facilities in mid-sized cities of India,
taking pedestrian space, flow rate, volume to capacity ratio and average walking speed as the Measure of Effectiveness (MOE).
As defining PLOS is a classification problem, it has been observed that Self Organized Map (SOM) one of the clustering methods
is used to classify the ranges of different measure of effectiveness in this regards. From the study it is observed that average space
of >15.67 meter2/pedestrian, flow rate of ≤0.063 pedestrians/second/meter width, average speed of >1.22 meter/second and volume to
capacity ratio of ≤0.4 pedestrian can move in their desired path at LOS ‘A’ without changing movements and it is the best condition
for off-street facilities. But situation considered to be PLOS ‘F’ at which movement is severely restricted and frequent collision among
pedestrians occurs, parametric ranges expressed as average space ≤4.48 meter2/pedestrian, flow rate of >0.145 pedestrians/second/
meter width, average speed of ≤0.62 meter/second and volume to capacity ratio of >1.00.The ranges of the parameters used for LOS
categories found in this study for Indian cities are different from that mentioned in HCM (2010) because of differences in population
density, traffic flow condition, geometric structure and some other factors.
1INTRODUCTION
Indian cities have traditionally been
cities of walkers, and many urban
dwellers rely on walking, cycling
and public transport for their daily
travel. However, with the exponential
increase in motorization, limited
attention has been paid to pedestrian
and public transport facilities. A
change in focus is required which
will allow people, not vehicles, to
reclaim the urban environment.
Growing motorization has also lead to
a dramatic increase in the number of
pedestrian fatalities and accidents, and
high levels of air pollution-particularly
exposing pedestrians who walk to
work or access public transport to
reach their destinations. There are few
initiatives to promote the improvement
of walking in Indian cities. The few
civil society organizations and non
government organizations working
in this area can play key roles in
promoting improvements on walk
ability and pedestrian facilities in their
cities.
As Pedestrian Level of Service
(PLOS) is an essential part for
highly heterogeneous traffic flow
on urban corridors in India, in this
study an attempt has been made to
define LOS criteria for mid-sized
cities. Defining the PLOS criteria is a
module of LOS analysis procedure of
urban off-street pedestrian facilities.
These methodologies affect the
planning, design, and operational
aspects of transportation projects
as well as the allocation of limited
financial resources among competing
transportation projects. This envisages
the importance of suitable methods that
should be adopted while defining the
PLOS criteria of urban streets in the
context of cities in India. Considering
the importance of LOS analysis for
urban off-streets pedestrian facilities
in Indian context, an in-depth research
was carried out in the present study.
In this study two important mid-size
cities (population less than a million),
Bhubaneswar and Rourkela of Odisha
state, India are taken as the study
area. By using video data collection
procedure all the field data like speed
of pedestrian, effective walkway
width and pedestrian hourly volume
are collected. For the determination of
different LOS categories parameters
like flow rate, pedestrian space and
Volume to Vapacity (V/C) ratio are
calculated. Then with the help of
SOM clustering, ranges of PLOS
are determined in establishing the
evaluation criteria for PLOS of offstreet pedestrian facilities in urban
Indian context.
The overall framework of this study is
illustrated in Fig. 1.
Fig. 1 Overall Framework of the Study
*Research Scholar, E-mail: [email protected], **Assistant Professor, E-mail: [email protected], Department of
Civil Engineering, National Institute of Technology Rourkela.
INDIAN HIGHWAYS, April 2015
5
TECHNICAL PAPERS
2BACKGROUND
STUDY
OF
THE
2.1 General
HCM (2000) describes that the LOS
criteria for pedestrian flow are based
on subjective measure, which can be
imprecise. However, it is possible to
define ranges of space per pedestrian,
flow rates and speeds, which then can
be used to develop quality-of-flow
criteria. It defines six LOS categories
for pedestrian facilities. The HCM
(2010) also designates six LOS from
“A” to “F,” for pedestrian facility,
with LOS “A” representing the best
operating conditions and LOS “F”
the worst. It uses distinct average
pedestrian space values as boundaries
for the various LOS. HCM (2010)
stated that as volume and density
increase, pedestrian speed declines. As
density increases and pedestrian space
decreases, the degree of mobility
afforded to the individual pedestrian
declines, as does the average speed of
the pedestrian stream. According to
HCM 2000 pedestrian facilities can be
of two types that are uninterrupted and
interrupted. When pedestrian facilities
are not affected by any motorized
modes of travel then the facility is
known as the uninterrupted pedestrian
facility or off-street pedestrian
facilities and vice versa. Several
studies have been performed relating
to the analysis of PLOS of pedestrian
facilities. IRC:103-2012 has defined
six ranges of pedestrian space and
flow rate to provide PLOS categories
in Indian condition, where LOS A is
having pedestrian space >4.9 m2/p and
flow rate ≤12 p/min/m. Dandan et al.
(2007) quantificational analysed the
correlation between the pedestrian
LOS and the affected factors; then
on the basis of the analysis of urban
roads with typical road transect form
it interpreted that the factors which
significantly affected the pedestrian
LOS were the bicycle volume, the
vehicle volume, the pedestrian
6
volume, driveway access frequency
and the distance between sidewalk and
vehicle lane and also a pedestrian LOS
model has been developed with the
significant variables. Muraleetharan
and Hagiwara (2007) focused on
examining the influence of overall
LOS of sidewalks and crosswalks on
pedestrian route choice behaviour
and attributes affecting overall LOS
of sidewalks and crosswalks. Smith
(2009) suggested that perceptions
as well as objective assessment of
the environment are significant in
different ways in predicting walking
behaviour.
In Indian cities pedestrian’s side walk
behaviour is different from that of
pedestrians in developed countries.
In this regard Rastogi et al. (2011)
discussed about the development of
adjustment factors for effective design
of pedestrian facilities on the basis
of pedestrian walking speeds under
influences like age and gender, land
uses, temporal variations, cell phone
usage, carrying baggage while walking
and moving in groups; on three types
of facilities, e.g., sidewalks, widesidewalks, and precincts. The authors
observed that pedestrians in India
cross slower than their counterparts
in other countries. Male pedestrian
were found to cross the road faster
(1.22 m/s) than female pedestrian
(1.11 m/s) irrespective of road system
and land use of surrounding area.
The authors suggested that the design
speed for specific locations such as
school and recreational area can be
taken as 0.98-0.99 m/s and the places
where older pedestrian are dominant,
a design speed of 0.79 can be adopted.
Laxman et al. (2010) have carried
out a study for medium-sized cities
in India and analyzed the pedestrians
flow characteristics under mixed
traffic condition. The authors observed
that the free-flow speed of Indian
pedestrian is 80 m/min which is higher
than that for China and Singapore, but
slightly lower than that in Germany.
2.2Sidewalk
Several factors have been observed
to influence the service level of
pedestrians while in movement along
the sidewalk. Petritsch et al. (2006)
incorporated traffic volumes on the
adjacent roadway and exposure (i.e.,
crossing widths) at conflict points with
intersections and driveway and the
study reveals that traffic volumes on
the adjacent roadway and the density
of conflict points along the facility are
the primary factors in the LOS model
for pedestrians travelling along urban
arterials with sidewalks. Sisiopiku
et al. (2007) compared the various
pedestrian sidewalk assessments and
shown that the same sidewalk segment
may receive multiple LOS ratings
when different assessment methods
are considered and the fact applies to
sidewalks located on both urban and
campus-like environments. Houten
et al. (2007) stated that because
pedestrian signal violations at midblock crosswalks are associated with
pedestrian crashes, it is important to
improve pedestrian signal compliance
at these locations. One way to improve
compliance is to decrease pedestrian
delay by reducing minimum green
time. Miller et al. (2008) investigated
the approach speed and passing
clearance that seg-way devices exhibit
on encountering a variety of obstacles
on the sidewalk. Keegan and Mahony
(2003)indicated that the countdown
timer units induced a reduction in the
number of individuals who crossed
during the red man (do not walk) signal
and as a result of the positive outcome
in terms of the analysis, the countdown
timer-units are being introduced on a
phased basis to a wider area in Dublin
city.
2.3 Clustering
Self-Organizing Map (SOM) is one
of the techniques in Artificial Neural
Network (ANN) having the inherent
capability to learn the pattern of input
and to detect regularities and shows the
INDIAN HIGHWAYS, April 2015
TECHNICAL PAPERS
correlations in their input with respect
to its output. The application of SOM
in ANN for this particular problem is to
cluster the service levels provided by
the urban off-street facilities measured
by various parameters. Lingra (1995)
compared grouping of traffic pattern
using the Hierarchical Agglomerative
Clustering and the Kohonen Neural
Network methods in classifying traffic
patterns. It has been mentioned that
the Kohonen neural network integrates
the hierarchical grouping of complete
patterns and the least-mean-square
approach for classifying incomplete
patterns. It is advantageous to use
hierarchical grouping on a small
subset of typical traffic patterns to
determine the appropriate number of
groups and change its parameters to
reflect the changing traffic patterns.
Such an approach is useful in using
hour-to-hour and day-to-day traffic
variations in addition to the monthly
traffic-volume variation in classifying
highway sections. Florio and Mussone
(1995) have taken the advantage of
application of ANN in classification
problem to develop the flow-density
relationship of a motorway. The author
defined the stability and instability of
spacing of vehicle in traffic stream.
Sharma et al. (1994) studied and
compared the learning ability of both
supervised and unsupervised type
of learning method for clustering.
Al-Garni and Abdennour (2008)
developed a technique using the ANN
to detect and count the vehicles plying
on road from the video graph data.
Yang and Qiao (1998) used neural
network to classify traffic flow state.
Author applied a self-organizing neural
network pattern recognition method to
classify highway traffic states into some
distinctive cluster centres. Jian-ming
(2010) developed a combined ANN
and Genetic Algorithm method for the
prediction of traffic volume in Sanghai
Metropolitan Area. The accuracy of
prediction of traffic volume of future
traffic improved significantly with this
INDIAN HIGHWAYS, April 2015
combined algorithm. Cetiner et al.
(2010) developed a back propagation
Neural Network traffic flow model for
prediction of traffic volume of Istanbul
City. The model uses the historical
data at major junctions of the city for
prediction of future traffic volume.
From the background of this study
it has been observed that there is a
significant body of research featuring
new ways of evaluating pedestrian
service levels on urban sidewalks.
These studies recommend everything
from small amendments to the HCM’s
PLOS calculation to completely
new LOS methodologies, depending
on local needs and characteristics.
These studies suggest that the current
tool for measuring pedestrian LOS
prescribed by the HCM may not take
into account important differences in
pedestrian characteristics, location
characteristics, and flow characteristics
when evaluating midsized Indian
City sidewalks. The issue is how to
determine the threshold values for
partitioning different PLOS categories.
SOM clustering is the method that
is applied to define urban off-street
pedestrian LOS categories in this study.
The major objectives of this study are:
(1) To estimate the optimum number
of PLOS categories using various
cluster validation parameters and (2)
To determine the ranges of PLOS
categories using various Measure of
Effectiveness (MOE) for urban offstreets facility in urban India context.
3
ARTIFICIAL NEURAL NETWORK (ANN)
ANN is the result of academic
investigations that use mathematical
formulations to model nervous system
operations. The resulting techniques
are being successfully applied in
a variety of everyday business
application. ANN is used to learn
pattern and relationship in data. The
ANN mimics the human ability to
adapt to changing circumstances and
the current environment. They learn
from the events that have happened
from past apply this learning to future
environment. ANN consists of many
nodes i.e. processing unit analogous
to neuron in the brain. Each node has
a node function and also some local
parameters. Modification of local
parameter changes the node function.
Neural network may be of single or
multiple layers. Single layer consists
of input neurons and output neurons.
Multi layer artificial neural network
consists of input layer, output layer
and hidden layer. There are various
types of ANN like Feed forward
neural network, Radial basis function
network, Self-organizing Map (SOM),
recurrent neural network. For this
study, SOM which is best among
ANNs for clustering of data is used.
3.1Self-Organizing Map (SOM)
A self-organizing map is a type of
artificial neural network that is trained
using unsupervised learning to produce
a low-dimensional (typically twodimensional) map. Self-organizing
maps are different from other artificial
neural networks in the sense that they
use a neighbour-hood function to
preserve the topological properties of
the input space.
A self-organizing map consists of
nodes. A weight vector is associated
with each node and the weight vector
is of the same dimension as the input
data vectors. The usual arrangement
of nodes is a regular spacing in a
hexagonal or rectangular grid. The
self-organizing map describes a
mapping from a higher dimensional
input space to a lower dimensional
map space. The procedure for placing
a vector from data space onto the map
is to first find the node with the closest
weight vector to the vector taken from
data space. Once the closest node is
located it is assigned the values from
the vector taken from the data space.
3.2 Architecture of ANN and
Parameters Used
The architecture of the ANN is shown
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TECHNICAL PAPERS
in Fig. 2. SOM algorithm is used in this
research to train the Input data. SOM
basically has 2 layers architecture,
containing Input and Output layer. The
input layer contains nodes, through
which input data is given to the neural
network. The number of nodes varies
according to the dimension of input
data set. In this study the input layer
contains 120 nodes because 120 data
points are utilized for training of neural
network. Each node is associated with
a weight vector which changes in every
iteration during training process. The
output layer contains neurons and each
neuron corresponds to the centroid of
a particular cluster. The shape of the
neuron depends upon the topology
function. In this study hexagonal
topology was chosen.
Fig. 3 PLOS Methodology for off-Street
Walk-Ways (Source: HCM 2010)
Step: 1
Determination of Effective Walkway
Width
Effective walkway width is the
portion of a walkway that can be used
effectively by pedestrians. Various
types of obstructions and linear
features, discussed below, reduce the
walkway area that can be effectively
used by pedestrians. The effective
walkway width at a given point along
the walkway is computed as follows:
Fig. 2 A Self-Organizing Map (SOM)
Neural Network
4METHODOLOGY
Off-street pedestrian facility serves
only non-motorized traffic and is
separated from motor vehicle traffic
to the extent that such traffic does not
affect their quality of service. There
are different categories of exclusive
pedestrian facilities: walkways, crossflow areas, queuing area, underpass,
overpass, stairways etc. The LOS
thresholds for each category are
different, but all are based on the
concept of space per pedestrian, which
is a measure of pedestrian comfort and
mobility. The HCM 2010 methodology
for determining PLOS categories is
followed in this study. Following are
the steps shown in Fig. 3 taken to
determine the LOS of exclusive offstreet walkways pedestrian facilities.
8
WE = Wr – WO
... (1)
where,
WE =effective walkway width,
Wr = total walkway width at a given
point along walkway, and
WO =sum of fixed-object effective
widths and linear feature shy
distances at a given point along
walkway.
Step: 2
Calculation
Rate
of
Pedestrian
Flow
An hourly pedestrian demand is used
as an input to the analysis. Consistent
with the general analysis procedures
used throughout the HCM, hourly
demand is usually converted into peak
15 min flows, so that LOS is based on
the busiest 15 consecutive minutes
during an hour:
... (2)
where,
V15 =pedestrian flow rate during peak
15 min (p/h),
Vh = pedestrian demand during analysis hour (p/h), and
PHF = peak hour factor.
However, if peak-15min pedestrian
volumes are available, the highest
15-min volume can be used directly
without the application of a peak
hour factor. Next, the peak 15-min
flow is converted into a unit flow rate
(pedestrians per second per meter of
effective path width):
... (3)
Where,
VP is pedestrian flow per unit width
measured by pedestrian /meter/second
(p/m/sec) and all other variables are as
previously defined.
Step: 3
Calculation of Average Pedestrian
Space
The service measure for walkways
is pedestrian space, the inverse of
density. Pedestrian space can be
directly observed in the field by
measuring a sample area of the facility
and determining the maximum number
of pedestrians at a given time in that
area. The pedestrian unit flow rate is
related to pedestrian space and speed:
... (4)
where,
AP = pedestrian space (meter2/pedestrian (m2/p),
Sp = pedestrian speed (meter/second
(m/sec)), and
Vp = pedestrian flow per unit width
(p/m/sec).
Volume to Capacity ratio (v/c)
Calculation
For determination of PLOS category
of off-street pedestrian facility volume
to capacity (v/c) ratio is one of the
most important factor. For this study
pedestrian hourly volume can be
found out from video data collection
and capacity of side-walks has been
taken from IRC:103. Here width of
side-walk for 1.5 m, 2 m, 2.5 m, 3
m and 4 m capacities in number of
INDIAN HIGHWAYS, April 2015
TECHNICAL PAPERS
persons per hour in both directions
are 800, 1600, 2400, 3200 and 4000
respectively.
Step: 4
Determine Pedestrian Level of
Service (PLOS)
PLOS categories are to be resolute on
the basis of average pedestrian space
(Ap). Six no of PLOS designated as
“A” to “F” has to determine for offstreet pedestrian facilities. Not only
on the basis of average space, other
related measures like flow rate, average
space and volume by capacity ratio are
also considered for categorisation of
PLOS.
5SOM CLUSTER ANALYSIS
AND VALIDATION MEASURE
5.1SOM Cluster Analysis
Among various types of ANN
algorithms, in this study SelfOrganizing Map is used for clustering
of speed data because of its inherent
capability to learn the pattern of input.
SOM is trained iteratively being
inspired by neural networks in the
brain. Self-Organization Map (SOM)
uses a competition and cooperation
mechanism to achieve unsupervised
learning. In SOM, a set of nodes is
arranged in a geometric pattern which
is typically a 2-dimensional lattice. In
the basic SOM algorithm, the neurons
are connected to adjacent neurons by
neighbourhood relation. This dictates
the topology, or structure of the map
and the arrangement of neuron may be
grid, hexagonal or random topology.
Usually the neurons are connected
to each other via rectangular or
hexagonal topology. One can also
define a distance between the map
units according to their topology
relation. The topological relation may
be rectangular or hexagon, it should be
fixed from beginning. In this research
Hexagonal topology is used. Each node
is associated with a weight vector with
the same dimension as the input space.
INDIAN HIGHWAYS, April 2015
The purpose of the SOM is to find a
good mapping. During training, each
node is presented to the map so also the
input data associated with it. An input
weight vector of same dimension as
that of input data dimension was given
to the ANN. The clustering using SOM
algorithm was done in two steps.
Step: 1
The input data is compared with all
the input weight vectors mi(t) and the
Best Matching Unit (BMU) on the map
is identified. The BMU is the node
having the lowest Euclidean distance
with respect to the input pattern x(t).
The final topological organization of
the map is heavily influenced by this
distance. BMU mc(t) is identified by:
For
... (5)
Step: 2
Weight vectors of BMU are updated
as
.. (6)
Here hb(x) is the
function, which is
neighbourhood
... (7)
Where 0 < α(t) < 1 is the learning
rate factor which decreases with each
iteration. ri and rb(x) are the locations of
neuron in the input lattice. α(t) defines
the width of the neighbourhood
function. The above two steps were
repeated iteratively till the pattern in
input was processed.
5.2 Validation Measure
Cluster validity is concerned with
checking the quality of clustering
results. It has been mainly used
to evaluate and compare whole
partitions, resulting from different
algorithms or resulting from the same
algorithms under different parameters.
Common application of cluster
validation measure is to determine the
correct number of cluster for a set of
data (Bensaid et al., 1996). Different
validity measures have been proposed
in the literature, none of them is perfect
by oneself, and therefore several
indices are used in this study, such
as: Silhouette Index, Davies-Bouldin
Index,
Calinski-Harabasz
Index,
Dunn Index, Krzanowski-Lai Index,
Weighted inter-intra Index.
A.Silhouette Index (SI)
This index was proposed by Rousseeuw
(1987) to evaluate clustering results.
Silhouette width is a composite index
which reflects the compactness and
separation of the clusters. For each
data point i the Silhouette width is
calculated as follows:
... (8)
Where a(i) is the average distance of
a data point I to other data point in
the same cluster, b(i) is the average
distance of the that particular data
point to all the data points belonging
to the nearest cluster. The average s (i)
of all data points reflects the quality
of clustering result. Larger silhouette
value signifies good cluster.
B. Davies-Bouldin Index (DBI)
This index is a function of the ratio
of the sum of within-cluster scatter
to between-cluster separation. This
DB index is defined by (Davies and
Bouldin, 1979):
... (9)
Here Dc and dce are intra-cluster and
inter-cluster distances respectively. The
intra cluster distances are calculated
by average of pair wise distances from
points in the cluster to the cluster
centroid. The inter cluster distance
between two cluster is computed as the
distance between their centroids. Xa
any chosen arbitrary data that belongs
9
TECHNICAL PAPERS
to cluster i. Ni is number of data that
belong to cluster i. Ci and Cj cluster
centre of I and j cluster. So, when the
cluster is compact and far from each
other the ratio is small. Consequently
Davies-Bouldin index is small for
good cluster. Dimitriadou et al. (2002)
found that optimal numbers of cluster
for a data set is the number of cluster
for which the Davies-Bouldin index
(DBI) value is the lowest.
C. Calinski-Harabasz Index (CHI)
Calinski-Harabasz (1974) suggested
the index for cluster validation
purpose. This index uses the quotient
between the intra-cluster average
squared distance and inter-cluster
average squared distance.
E. Krzanowski-Lai Index (KI)
The index of Krzanowski and Lai
(KLI) is defined as (Krzanowski and
Lai, 1985):
... (12)
Where,
And p denotes the number of features
in the data set, c denotes the number
of clusters and c ≥ 2, W (c) denotes
the within cluster sum of square of
the partition. Dudoit et al. (2002)
suggested that the highest value of
Krzanowski-Lai index (KLI) gives the
optimal number of cluster for a given
data set.
F.
Weighted inter-intra Index (WI)
This index tries to find the optimal
number of cluster φ(Q) by high overall
quality of cluster and a small number
of cluster k. The quality of cluster is
determined as follow:
... (13)
Where
... (10)
Here n is total number of input data
points. c is number of cluster. nk
is number of data points in cluster
k (k = 1,2,…c), and Xi and
are
observation vectors for input data I and
the centroid for group k, respectively.
This parameter was found to be the
best global statistic criterion in cluster
evaluation by Milligan and Cooper
(1985).
D. Dunn Index (DI)
The index was formulated by Dunn
(1974) in order to check the quality
of cluster resulted from a clustering
algorithm. The equation is defined by:
(11)
Here d(ci,cj) is the dissimilarity
function between two clusters ci and
cj defined as d(ci, cj) =
and
diam(c) is the diameter of a cluster
which is the measure of dispersion
of the clusters. The diam(c) of the
cluster can be defined as follows.
10
... (14)
And
Here i and j are cluster indices Xa and
Xb are two vertices.
6STUDY CORRIDORS AND
DATA COLLECTION
A century of industrialization and
technical advancement has brought
forth rapid urbanization in India.
Statistics on census of India 2011
reveals that about 377 million of the
total 1.21 billion population of India
lives in urban areas. As per the
census Odisha is having 41 million
populations, that is 3.14 percent of
population of India and the population
is closest to country Argentina.
However, decadal growth in the
urban population of the State, during
the last decade (2001-2011) has been
enormous with a growth rate of about
26.80 percent, which is nearly that of
national growth rate of 31.80 percent.
It is noteworthy that the state’s
population during the last decade has
grown by about 13.97 percent while
that of the urban population has grown
at almost at double this rate.
... (15)
Two important mid-size cities
Bhubaneswar and Rourkela of
Odisha state, India are taken up in
the present study. Sampled area
sees heavy foot traffic, because of
sidewalks on the streets and transit
points. Another feature of the selected
area is the great variety of land uses:
residential, commercial, office and
institutional (e.g., school, hospital).
Often, commuters need to walk at
least a short distance to reach their
final destinations. Bhubaneswar and
Rourkela has straight, wide streets,
unlike the narrow, winding, ancient
streets found in most Indian cities
and also the edge of the sidewalks are
having sufficient distance from the
window shopping, so that pedestrian
don’t have to face problem for that.
Streets are arranged in a grid, meeting
at signalized intersections that are
installed with pedestrian crosswalks.
In the surveyed area, almost all the
streets have sidewalks on both sides
and crosswalks at intersections.
INDIAN HIGHWAYS, April 2015
TECHNICAL PAPERS
Bhubaneswar, the temple city
enjoys excellent connectivity with
other adjoining regions of strategic
importance - however, the passenger
transit option needs improvement
of greater interaction. Bhubaneswar
is primarily an administrative city
and a tourism city. Bhubaneswar has
emerged as a fast-growing, important
trading and commercial hub in the
state and eastern India. Tourism is a
major industry, attracting about 1.5
million tourists in 2011. Bhubaneswar
was designed to be a largely residential
city with outlying industrial areas.
The economy had few major players
until the 1990s and was dominated by
retail and small-scale manufacturing.
There exists a significant level of
disparity within this region in terms
of accessibility to major urban centres.
At intra urban level, incapacity of
the existing traffic and transportation
network will create a serious constraint
to its future growth. The traffic
demand management will play a key
role as the role of supply management
is near exhaustion. On the other hand
Bhubaneswar enjoys a variable level
of mobility at different parts of the
city. Rourkela, the site for this study
is commonly known as the steel city
in all over world is one of the largest
city located at northern west of the
Odisha state. It is situated at the heart
of mineral belt .The correct selection
of sample sites is an important issue
in designing the field survey. In reality,
selection of a proper site is not an easy
task because different routes need to
appear in different LOS conditions
to examine the influence of LOS on
pedestrian route choice. Sampled
area sees heavy foot traffic, because
of sidewalks on the streets and transit
points. Riders of public transportation
(subway, bus, train) usually walk from
transit points to their destinations.
Another feature of the selected area
is the great variety of land uses:
residential, commercial, office and
institutional (e.g., school, hospital).
Often, commuters need to walk at
INDIAN HIGHWAYS, April 2015
least a short distance to reach their
final destinations. Bhubaneswar and
Rourkela has straight, wide streets,
unlike the narrow, winding, ancient
streets found in most Indian cities.
Almost all the streets have sidewalks
that are separated from the carriageway
by small trees and curbs. Since bicycle
lanes have not been established in
cities cyclists also use these sidewalks.
Streets are arranged in a grid, meeting
at signalized intersections that are
installed with pedestrian crosswalks.
In the surveyed area, almost all the
streets have sidewalks on both sides
and crosswalks at intersections.
Study corridors for the study area are
presented in Fig. 4.
(a) Bhubaneswar Study Corridors
(b) Rourkela Study Corridors
Fig. 4 Map Showing the Road Corridors of the Study Areas
Increasingly, researchers are using
video camera to observe and collect
data about pedestrians. Video data
has plenty of advantages over direct
observation: one can collect data from
the video carefully back in the office or
lab, can easily share video with others
to illustrate a point, and there are tools
available to automate data collection.
High resolution video camera was
fixed to the side of the foot-path
that is the pedestrian off-street
facilities with the help of a tripod
stand. Always a length of 4m has
been marked to observe the flow of
pedestrian. However the start and end
point of the stretch having four meter
length of the footpath helped
in determining the speed of the
pedestrian.
11
TECHNICAL PAPERS
Pedestrian speed and attributes on
road features data were collected on a
sample of 3,764 pedestrians observed
at various sidewalk locations in both
of the cities about 62 days in both
peak and off-peak hours of working
and non-working days. This shows
that a large size data set is used for the
development of LOS categories in this
study. The speed of each pedestrian is
recorded by using stopwatch. With the
help of stopwatch pedestrian crossing
time from the starting point to the end
point of the observed portion of the
off-street segment was recorded. From
which pedestrian speed per meter
is calculated and average speed of
pedestrian for each segment is taken
for further calculation. It is assumed
that the average speed of pedestrians
on the observed section of the facility
represents the average speed of the
street segment as a whole. In the same
locations, over the same time period,
all pedestrians were counted in order
to determine sidewalk flow rates, and
basic information about each of the 31
station points was recorded.
Then the videos loaded to computer
to play the recorded videos. Manually
the pedestrian peak volume and flow
rate were calculated from video
data. It is observed that in these two
cities pedestrian flow and density
are comparatively lower because
population sizes of these two cities are
less than a million and also mobility
due to commercial activities is
comparatively lower. Based on these
sets of data, two databases were built:
a database containing speed and an
aggregate database of each of the study
locations. This aggregated locational
database includes the calculated flow
rate based on the count at the location,
the effective width of the sidewalk,
and land use proportions based on two
cities. Effective walkway width is the
portion of a walkway that can be used
effectively by pedestrians. Various
types of obstructions such as trees,
electric poles, information sign boards,
12
projections of road side shops and
linear features, reduce the walkway
area that could have effectively used
by pedestrians.
Value of validation parameters were
obtained for 2 to 7 number of cluster
and were plotted in Fig. 5 and the
validation indices are shown in Table
1. Bolshakova et al. (2005) shows that
the largest silhouette value indicates
a better quality of clustering result.
Fig. 5(a) shows that the index value
is largest for 6 number of cluster.
Also Bolshakova et al. (2005) says
that for Davies-Bouldin (DB) a low
value indicates the optimum number
of cluster. From the Fig. 5(b) it is
observed that index value is minimum
for 6 number of cluster. Dudoit et al.
(2002) and Bolshakova et al. (2005)
found that the maximum value of
Calinski-Harabasz
Index,
Dunn
Index and Krzanowski-Lai Index
represents the optimum number of
cluster respectively. Fig. 5(c) and
5(e) shows that the optimum number
of cluster for Calinski-Harabasz
Index and Krzanowski-Lai Index are
7 and 3 respectively whereas from
Fig. 5(d), for Dunn index 6 is the
optimum number of cluster.
7RESULTS AND ANALYSIS
The average pedestrian space data
acquired through Video Camera was
clustered using SOM algorithm of
ANN. For determination of the
parametric values of validation
measures, average pedestrian space
data and cluster ranges found from
ANN analysis were used. In this
research six validation parameters were
used. These six number of validation
parameters were used to know the
optimum number of clusters for these
four parameters used; for example
data set of average pedestrian space
is explained in detail in this study.
By knowing the optimum number
of clusters we can classify the urban
off-street pedestrian facilities into
that number of LOS categories. It is
always considered that lesser number
of clusters is better if variation in
validation parameters is minimal.
a) Silhouette Index vs Number of Cluster
b) Davies-Bouldin Index vs Number of Cluster
c) Calinski-Harabasz Index vs Number of Cluster
d) Dunn Index vs Number of Cluster
e) Krzanowski-Lai Index vs Number of Cluster
f) Weighted inter/intra Index vs Number of Cluster
Fig. 5 Validation Measures for Optimal Number of Cluster using SOM Clustering
INDIAN HIGHWAYS, April 2015
TECHNICAL PAPERS
Table 1 Numerical Values of Cluster Validation Measures using SOM Clustering
NC
SI
DBI
CHI
DI
KI
WI
2
0.0007
0.0005
0.4006
0.0035
0.0036
0.0006
3
0.0006
0.0005
0.5167
0.0033
0.0285
0.0006
4
0.0006
0.0004
0.4771
0.002
0
0.0006
5
0.0006
0.0005
0.7385
0.0033
0.0005
0.0006
6
0.00071
0.0003
0.2908
0.0038
0.0008
0.0007
7
0.0007
0.0004
1.211
0.0016
0.0008
0.0006
Here,
NC = Number of Cluster
SI
= Silhouette Index
DBI = Davies-Bouldin Index
CHI = Calinski-Harabasz Index
DI = Dunn Index
KI = Krzanowski-Lai Index
WI = Weighted inter/intra Index
Again Dudoit et al. (2002) found that
for Weighted inter/intra Index the
first down –tick of the index during
searching forward is the optimal
number of cluster. In Fig. 5(f) it
occurs at 6 number of cluster. Out of
six validation parameter considered
in this study four parameters give
the optimal cluster value as 6 which
are also same as suggested by
HCM (2010). Also it is observed
that the other parameters or
measure of effectiveness (MOE)
that is pedestrian flow, speed and
volume to capacity (v/c) ratio
considered to define ranges of LOS
categories also satisfies classification
LOS into six categories. That is the
reason for which in this research the
urban off-street pedestrian facilities
are classified into six categories using
the SOM in ANN.
After getting the optimum number
of clusters as six all the parameters
that are the average pedestrian space,
speed, flow and v/c ratio data acquired
through video data collection was
clustered using the SOM algorithm.
The different ranges of the parameters
are given in different symbols, also
the legends in Fig. 6 (a-d) gives
the ranges. All the clustered ranges
of PLOS categories for off-street
pedestrian facilities are shown in
Fig. 6 and Table 2.
(A) Average Pedestrian Space of PLOS Categories
(B) Flow rate of PLOS Categories
(C) AverageTravel Speed of PLOS Categories
(D) v/c ratio of PLOS categories
Fig. 6 PLOS Categories of Urban Off-Street Pedestrian Facilities using SOM Clustering on Various Parameters
INDIAN HIGHWAYS, April 2015
13
TECHNICAL PAPERS
Table 2 PLOS Categories for Urban Off-Street Pedestrian Facilities using SOM Clustering
LOS
Average
Space
(m2/p)
Related Measures
Comments
Flow Rate
(p/sec/m)
Average Speed
(m/sec)
v/c ratio
A
>15.67
≤0.063
>1.22
≤0.4
Ability to move in desired path, no need to
alter movements
B
>11.9415.67
>0.063-0.081
>1.11-1.22
>0.4-0.53
Occasional need to adjust path to avoid
conflicts
C
>9.07-11.94
>0.081-0.103
>0.95-1.11
>0.53-0.68 Frequent need to adjust path to avoid conflicts
D
>6.49-9.07
>0.103-0.133
>0.78-0.95
>0.68-0.84 Speed and ability to pass slower pedestrians
restricted
E
>4.48-6.49
>0.133-0.145
>0.62-0.78
>0.84-1.00 Speed restricted, very limited ability to pass
slower pedestrians
F
≤4.48
>0.145
≤0.62
From SOM cluster analysis it is found
that for PLOS “A” average pedestrian
space is greater than 15.67 m2/p and
for PLOS “F” it is less than 4.48 m2/p.
Pedestrians will face frequent
contact with other users and speed is
restricted when flow rate is greater than
0.145 p/sec/m and at that time volume
to capacity ratio is at extreme level
i.e. near about 1. Whereas pedestrians
can move at their desired speed at less
than 0.064 p/sec/m flow rate and less
than 0.4 volume to capacity ratio. This
occurs in PLOS “A” condition and
here pedestrians move at near about
1.22 m/sec speed. In PLOS “F” speed
is about 0.62 m/sec, where it is difficult
to walk for a pedestrian. Applying this
method it is found that all the ranges for
urban off-street pedestrian facilities for
six PLOS categories are significantly
different from those values mentioned
in HCM 2010. In this study, these two
cities are having less than a million
populations, for which pedestrian
movement is comparatively low than
the highly populated metropolitan
cities. In Indian cities highly
heterogeneous traffic flow on the main
carriageway occasionally influence the
pedestrian’s movement on off-street
facilities. Due to poor enforcement of
laws for traffic on main carriageways
14
>1
Speed severely restricted, frequent contact
with other users
as well as the off-street pedestrian
facilities, a haphazard movement is
perceived. Also it has been observed
that inadequate road infrastructures
lead to varying geometry conditions
creates unwanted confusion to the
users. Besides, some of the pedestrian
facilities are unauthorized occupied by
vendors for their commercial use and
installation of advertisements boards.
In some cases unplanned utilities such
as electric and telephone poles become
a natural obstruction to the pedestrian
movements on the path. Illegal parking
on off-street facilities becomes a
common phenomenon for which the
pedestrian has to forcefully reduce
its speed and divert the direction of
movement. For these reasons PLOS
ranges in Indian cities are different
from other developed countries. In
India, social and cultural inheritance
is also different as people love to
move in platoons, which has a broad
effect on off-street movements. Also
the physical size of Indian population
is also another contributing factor for
which the PLOS categories in this
study are different from the values
described in HCM.
8
CONCLUSION
Over the years, PLOS methods have
been developed in a variety of ways for
different walking environments and it
has been suggested for substantial
improvements
in
the
analysis
procedures. Majority of these methods
and models have been developed by
combining models that have been
applied to other choice contexts and,
as a result, are not suited to universal
applications. Various models available
are suitable for homogenous traffic
flow condition as seen in developed
countries. From the background
studies it is found that HCM (2010)
methodology for the prediction of
PLOS can be used for Indian context
after due modifications. Hence the
PLOS methodology developed in
HCM (2010) is adopted in this study.
SOM clustering method is used to
define PLOS criteria. Different LOS
values based on pedestrian space, flow
rate, speed of pedestrian and volume
to capacity (v/c) ratio are defined from
clustering analysis method which gives
numeric ranges for LOS categories.
From this study it is observed that
pedestrian data collection using video
cameras is a very simple and accurate
procedure. SOM clustering is highly
efficient in terms of time saving and
provides a very accurate solution to
this kind of classification problem. By
using SOM cluster analysis, ranges of
parameters for six pedestrian levels
INDIAN HIGHWAYS, April 2015
TECHNICAL PAPERS
of service categories i.e. A, B, C,
D, E and F are defined for off-street
walking facility in Indian context;
where LOS “A” represents the best
operating conditions and LOS “F” the
worst. The PLOS ranges defined in
this study are significantly different
from that mentioned in HCM (2010)
because of highly heterogeneous
traffic flow on main carriageway, poor
enforcement of traffic laws, varying
road geometry, unauthorized vendors
activities, unwanted obstructions from
utilities, and illegal parking on offstreet facilities. Considering the local
condition, data collection method
using video cameras and SOM in
ANN clustering techniques can be
applied in other countries to define
the PLOS categories. One limitation
to the application of SOM in ANN
cluster analysis is that it require large
INDIAN HIGHWAYS, April 2015
amount of data set for which is
cumbersome.
The
relationships
among the variables at each step of
the methodology followed in this
study are empirical only. Hence
this methodology can be applied to
define the PLOS ranges irrespective
of city size or population size. In
the populated cities of population
more than million are having large
commercial, industrial, educational
and residential activities, which give
rises to heavy pedestrian activities.
The method followed in this study can
be applied to define the PLOS ranges
for off-street pedestrian facilities for
populated cities as the ranges defined
in this study are different; hence
similar studies can be carried out for
other bigger cities having population
size more than a million to develop
comprehensive PLOS criteria.
References
1.
2.
3.
4.
5.
Al-Garni, S., Abdennour, A. (2008).
“A Neural Network Based Traffic
Flow Evaluation System for Highways.” Journal of King Saud University of Engineering Sciences, 20(1),
37-46.
Highway
Capacity
Manual.
Transportation Research Board,
1965, Washington, D.C.
IRC.
(2012).
Guidelines
for
Pedestrian
Facilities,
IRC:103,
New Delhi.
Laxman, K.K., Rastogi, R., Chandra,
S. (2010) Pedestrian Flow Characteristics in Mixed Traffic Conditions. Journal of Urban Planning and
Development, American Society of
Civil Engineers, 136(1), 23-33.
Smith, A.L. (2009), Contribution
of Perceptions in Analysis of
Walking Behavior. Transportation
Research Board, Washington, D.C.,
pp. 128–136.
15
Eco-friendly Mulching – Enhancing Road Safety and its
Aesthetics through Value Engineering
Bhavesh Kantilal Thakkar*
ABSTRACT
Not only in Construction Phase of Road Projects, but even in Operation & Maintenance (O&M) Phase also, there is a need to
adopt Value Engineering approach in achieving Green objectives. However many a times these aspects during O & M Phase are
overlooked.
Value Engineering Process needs to be practiced for maintaining the standards of Quality and Reliability with reduced Costs in every
phase of Activities for which Kaizen approach could be successfully adopted.
Study was undertaken at 100 km Road Project constructed on Build Operate Transfer (Annuity Model) in Andhra Pradesh by Gammon
India Limited. Untapped Mulching Technique in Road Works was explored to convert one of the easily available nearby waste
Materials (i.e. Paddy grass) into Green Resource to enhance aesthetics of Highways besides improving Safety to Commuters by virtue
of better growth to Road Plantations and reduction in glaring effect especially in Medians.
The Qualitative and Quantitative benefits attained using these approaches are:
●
Growth of plant
: 3 times
●
Foliage Coverage
: 2 times
●
Savings in water consumption
: 52%
●
Reduction in Weed Growth
: substantial
Thus, Eco-friendly Mulching Technology is aimed to preserve Natural Environment by going Green apart from reducing costs by
10 – 12%.
1INTRODUCTION
Value Engineering approach can be
used to achieve one or more benefits
like optimizing Project Life Cycle
Costs, saving time, Increasing Profits,
Expanding Market Share, solving
Problems and/or using resources more
effectively.
Some of the approaches for Continual
Improvement can be through various
processes as listed below:
● Innovation of methodology by
rebuilding a new Technology
● Continuous slow Improvements
from the existing process
● Reverse Engineering in the usage
of alternate or similar materials
for intended use;
● Lean Concepts
Innovative Eco-friendly concept of
Mulching never attempted in Gammon
of its existence and also found no
records in either Internet or any
records of its application elsewhere
while developing Road Works in India
is used as Value Engineering concept
to especially reduce the Cost of
Operation and Maintenance of Median
Plantation on National Highways
Fundamentals of Value
Engineering
Resources are measured in terms of
summation Material, Labor, Price,
Time etc. required to accomplish the
function in its Project Life Cycle.
2.1 Value
It is defined as fair return or equivalent
in Goods, Money or Services for
something exchanged. It can be
commonly represented by the
relationship as below:
Value ≈ Functions/Resources
Where Function is measured by the
Performance requirement of the
Customer in terms of summation of its
functionality, Performance and Quality
of its Deliverables.
2.2 Application
of
Value
Engineering Concepts
Value Engineering can improve
Decision Making that leads to
optimal expenditure of Owner funds
while meeting required function and
Quality level. Hence, the timing of
the application of Value Engineering
concepts is critical to determine the
results of its benefits to the Project
which can be graphically represented
as below:
besides preserving Environment using
Kaizen Approach.
2
Graph 1 Pictorial Representation of Value Engineering Benefits
* Dy. Manager, Gammon India Limited, E-mail: [email protected]
16
INDIAN HIGHWAYS, April 2015
TECHNICAL PAPERS
The above graph clearly enunciates
the following:
● The Value Engineering benefits
attained are very high when conceived during the Initial Stages of
Project Construction where the
Cost to Change is very low.
● In case of O & M Phase of
Project Life Cycle, Cost to
Change is not that significant but
potential savings continue to rise
with the passage of time if
pursued.
2.3Tools and Techniques
The success of Value Engineering
is due to the ability to identify the
opportunities to remove unnecessary
costs while assuring the other factors
as listed above.
The basic approach to improvement
in Quality Parameters can not only
be through Proprietary approaches
like ISO, principles recommended by
Deming, Juran, Cros by and others but
also from Non Proprietary Approaches
such as TQM, Six Sigma, FMEA, Voice
of Customer, Cost of Quality and also
through Continual Improvement.
Tools for Continual Improvement are
2.3.1Functional Analysis System
Technique (FAST) Diagram
The FAST model has a horizontal
directional orientation described as
the HOW-WHY dimension. This
dimension is described in this manner
because HOW and WHY questions
are asked to structure the logic of the
system’s functions. Starting with a
function, we ask HOW that function is
performed to develop a more specific
approach. This line of questioning
and thinking is read from left to right.
To abstract the problem to a higher
level, we ask WHY that function is
performed. This line of logic is read
from right to left.
Graph 2 Pictorial Representation of FAST Methodology
2.3.2Creative Thinking
The creativity thinking is adopted
through various Group Creativity
Techniques
like
Brainstorming,
Idea/Mind
Mapping,
Affinity
Diagram, Nominal Group and Delphi
Techniques on any process execution
or Improvement works.
2.3.3Life Cycle Costing
The sum of all recurring and one time
(non-recurring) costs over the full life
INDIAN HIGHWAYS, April 2015
span or a specified period of good,
service, structure or system. It also
includes Purchase Price, Installation
Cost, Operation Cost, Maintenance and
upgrade costs, and remaining salvage
value at the end of the Ownership or
its useful life.
2.3.4Analytical Hierarchy Process
(Weighing Score Technique)
It provides a comprehensive and
rational framework for structuring a
decision problem, for representing and
quantifying its elements, for relating
those elements to overall goals, and
for evaluating alternative solutions.
2.3.5Kaizen Costing
Life cycle costing anticipates cost
improvements during the Project
Life Cycle well as recognizing the
importance of the design stage. This
is sometimes referred to as Kaizen
costing.
Kaizen
costing,
unlike Target
Costing, is not accompanied by a
set of techniques or procedures that
are automatically applied to achieve
cost reductions. Workers are given
the responsibility of improving the
processes and reducing costs.
3Project
Brief
on
Median Plantations
100 km of 4 Lane divided carriageway
was executed by Gammon – Punj
Lloyd JV in BOT Annuity Model
for National Highways Authority of
India which achieved Commercial
Operations in Oct 2004. Presently, it is
in ninth year of Operations and one of
maintenance activities is to Enhance
Safety measures, prevent Weeds,
improve aesthetics besides periodic
Overlay works and other routine
Maintenance activities.
Graph 3 Relationships Between Target Price, Profit and Cost
17
TECHNICAL PAPERS
Approximately 57 km of Total length
of 100 km is encompassed by Median
Plantations on a 4-lane divided
Carriageway from Rajahmundry
to Tuni on NH 16 in the state of
Andhra Pradesh. The quantitative
details of the Project are tabulated as
below:
●
●
●
Table 1 Median Plantation Details in the Project
S. No.
Package Identification
Plants in Nos
Approx. Length of
Corridor
1.
Rajahmundry Expressway Ltd
(Contract Package : AP 15)
12,024
21.75 km
2.
Andhra Expressway Limited
(Contract Package : AP 16)
16,326
35.00 km
Grand Total
3.1 Deliverables to Customer at any
Point of Time
● No Weed growth should be
visible
● Foliage of Plant should cover the
entire median
● Height of the Median Plants
restricted to max 2.0 m
3.2Present
Methodology
of
Execution
Conventional system of using Water
tankers of 10 KL Capacity are
deployed daily (4 Nos) to water the
plants for the entire stretch which used
to make 3 trips per day/ per tanker and
regular labor are deployed for cleaning
the basin and removal of Weeds
periodically, every 2-3 months to
ensure the deliverables as mentioned
in the above paragraph.
4Selection of Process
Improvement Methodology
Considering the balance Concession
period of six years only, Process
Improvement through completely
new innovation was out of reach. The
activity being related to Environment
Oriented,
Reverse
Engineering
cannot be implemented. The Project
is already in Lean Management and
further optimization was not possible
and therefore, the only option left out
for process Improvement was Kaizen
Approach.
18
●
●
●
●
Decreases water loss due to
evaporation;
Works against the Weeds;
Protects the roots from drying
and temperature
Extremes;
Adds organic matter to the soil;
Adds Nutrient to the soil;
Feeds soil life and improve soil
structure;
56.75 km
4.1Method Approach
Kaizen approach brings small
improvements at a time and
participation of team members is the
key element for its success.
● Project Team was enthusiastic
on change process and PM had
a buy-in from team Members
and the Independent Engineer to
undertake the Experiment;
● Team was given the task of
Brainstorming the Ideas for
alternative and better performance in terms of the Job
requirements;
● During Brainstorming Exercise,
Drip Irrigation and Exploiting
Mulching were identified and
Drip Irrigation was eliminated by
using
analytical
hierarchy
process and Mulching was selected as Process Design to test
the performance of the Median
Plantations;
● Team studied the results of
Mulching in various landscaping activities of Hotels and other
farming activities.
5
What is Mulching?
It is a simple protective layer to cover
the soil from the top by Organic or
Inorganic Materials to improve the soil
conditions and crop plants generally
by Farmers.
5.1 Benefits of Mulching
● Helps in preventing the soil
erosion;
Picture 1
5.2 Different Type of Mulch
Material which are Available
that Includes
● Grass Clippings
● Straw
● Bark chips
● Stones
● Brick chips
● Plastic
But Unfortunately, Mulch, being
generally treated as green waste, by
majority people to get rid of it but
folks understands the value when this
is treated as green resource.
As it is known fact, Organic Material
gets decomposes and it needs to be
replaced at certain period depending
on the type of material. The below
table shows the various details like its
availability on Earth, its anticipated
life and its major benefits which will
give the Professional, a ready reference
to evolve the suitable design by
constrained optimization techniques.
INDIAN HIGHWAYS, April 2015
TECHNICAL PAPERS
Graph 4 Details of Mulching Materials
6Broadly How Mulching
Links
to
Process
Improvement ofMedian
Plantation
Table 2 Comparison of Mulching Benefits vis-à-vis its Application
Material Benefits
Application in our Project
Prevents the Soil Erosion
Water requirement will be reduced and
deployment of Water Tanker can reduce
Decrease water loss in evaporation and decrease in OH and HSD expenditure
(Eco friendly measures)
Works against the weeds
Reduced Labor for jungle clearance
towards weeds removal will help in
Protects
from
drying
and
optimizing the work force for other
temperature in extreme conditions
activities
Adds Organic and Nutrients to soil, Early growth of plants will enhance
if organic material used
Aesthetics and reduce glaring effects
Improve Soil Structure
India, presently on mega Infrastructure
platform, for developing Road
Network across different corners is
stressing on continual improvement
process for sustaining Road Aesthetics
and Improvement of Safety to the
Commuters and Mulching is evolving
into one of the Process Alternative
at an reduced cost specifically to the
Performing Organization which in
turn will benefit Customer and Project
Sponsor.
INDIAN HIGHWAYS, April 2015
7Mulching
Implementation at Site as Trial
Experiment
One km length of Stretch is
considered for implementation of
Mulch as Process Improvement
Initiative
to
compare
the
Performance in the areas of
Non-Mulch areas for understanding
the
Moisture
Retention
and
Growth of Plants and its foliage
as per the Methodology furnish
below:
7.1Understanding
Moisture
Retention
● Form the basin at the girth of at
least 0.75 m diameter;
● Clear the entire weeds existing in
the basin;
● Apply Mulch 3-4” thick in the
basin and in our case, we have
considered as Straw (Paddy
Grass) as easily available local
material;
● Record the Moisture content @
500 mm depth below the basin
to know the present status of the
Plant which was 5% in our case
● Apply Water to Plants in both the
categories as per the Conventional practice;
● Monitor and Note the Moisture
Content (@ 500 mm below the
basin) twice a day at the fixed
times to under the Retention Rate
of the Soil
● Similarly, Monitor and Record
the Temperature at the basin to
understand the Evaporation rate
of the Soil
● Apply the Water in the Mulch
Areas only when the Moisture
content attains 5%;
● Record the Readings for
every cycle and determine the
Retention Rate and Evaporation
rate;
7.2 Understanding Plant Growth
Selected 6 Plants of Big and
Small Plants in both Categories
were measured initially in terms
of its Height, Girth, and Foliage
Coverage;
The above listed parameters were
recorded at the end of the Experiment
Cycle of one month and analyze the
results in comparison to the Non
Mulch Areas.
The Pictorial Representation of Mulch
Performance is shown below.
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TECHNICAL PAPERS
Picture 2 Experimental Results of Mulching in Site
8Experiment Results
8.1 The
Results
of
Water
Properties in terms of Moisture
and Evaporation during one month
of study in five cycles are tabulated
below:
Table 3 Test Results of Moisture Retention and Evaporation Observation
10
1.
Moisture Retention and Evaporation Results
Sl. No.
Mulch Area
Non Mulch Area
Retention Loss
Rate (Moisture
Content/Hour
Evaporation Rate
(Moisture Content/
Deg C)
Retention Loss Rate
(Moisture Content/
Hour
Evaporation Rate
(Moisture Content/
Deg C)
Cycle 1
0.045
0.36
0.090
0.72
Cycle 2
0.047
0.69
0.065
0.95
Cycle 3
0.038
0.42
0.053
0.58
Cycle 4
0.033
0.69
0.048
1.00
Cycle 5
0.046
0.46
0.063
0.63
Average
0.042
0.523
0.064
0.776
1.52
1.48
Variation
Non Mulch Area requires 52% more of
Water due to its direct exposure to Sun
which also indicates evaporation is
9
Costing Parameters
The Costing per plant per year
for the maintenance of Median
Plantations when being executed as
per Conventional practice is around
Rs.147/- per Plant as per the details as
shown in Table 5.
Incorporating the Experiment Results
lead to the reduction of the following:
● Lower Consumption of Water
resulting in reduction of Water
Tanker by 1 No and corresponding Labor Helper:
● Fuel consumption reduced by
25% due to reduction of Water
Tanker from 4 Nos to 3 Nos;
● Requirement of Periodical Labor
for Weed Removal gets eliminated and on the other hand, Cost of
Mulch has been added;
With the above Methodology, the
Revised Cost of Maintenance of Plant
using Mulching works out to Rs.128/per Plant per year as per details
tabulated as shown in Table 6.
2.
3.
higher by 48% in Non Mulch Areas.
8.2 Plant Growth and its Foliage
Growth rate are tabulated below:
Table 4 Physical Growth Results of Plants
Trend Results
Area
Type of
Plant
Mulch
Big
Non
Mulch
20
Plant Growth Foliage/Canopy
Rate (%)
Coverage Rate
(%)
2.01
4.5
small
0.86
NA
Big
0.66
1.31
small
0.43
Conclusions
1) Growth rate is almost 3 times in
Mulch zone than non culch zone
2) Canopy/Foliage increases almost by
2 times
3) Weed growth is substantially high
4.
Conclusions
Exploiting Mulching Technology
(by converting the Waste) into
Green Resource can yield around
12% reductions in Costs;
Implementation of Mulching
activity looks to be feasible and
easily executable;
The above Technology not
only reduces costs but more
importantly is contributing the
Society (which is the Primary
Responsibility of the Organization) by way of proper utilization
of Scarce Resource Like Fuel
and Water besides converting the
Waste Material into Green
Resource resulting in Preservation of Environment for a span of
seven years to any project having around 50 odd km of 4 laning
work;
The Organization can have better Branding due to application
of Go Green Initiatives;
INDIAN HIGHWAYS, April 2015
TECHNICAL PAPERS
5.
Small Improvement by using
Straw will pave the way for
the
usage
of
Alternate
Materials and subsequently
can help in developing the
Standard Operating Procedure
by getting more inputs from
other working Professionals
across the Country.
Table 5 Activity Based Costing of Median Plant using Conventional Methodology
Item Description
Hire Charges Water Tanker Charges
Unit
Qty
Rate (Rs)
Amount
Equip. months
48
30,000
1,440,000
Lts
20,571
45
925,714
Kl
2,170
75
162,750
sqm
161,280
8
1,290,240
Man cays
1,460
200
292,000
4,110,704
Say 147/-
HSD Consumption
(50 kms/day*30 days* 12 months* 4 Nos)/3.5
Water charges
(28000 Nos *50% free *20 Lts *365days/every 4th day
Weed Removal
(once in 2-3 months)
Helper
Grand Total
Costing Per Plant
146.81
Table 6 Activity Based Costing of Median Plant using Mulch Technology
Item Description
Hire Charges Water Tanker Charges
Unit
Qty
Rate
Amount
Equip. Months
36
30000
1,080,000
Lts
15,400
45
693,000
Remarks
HSD Consumption
(50 kms/day*30 days* 12 months* 4 Nos)/3.5
Water charges
(28000 Nos *50% free *20 Lts *365/4 day)
Kl
1,680
75
126,000
Mulch cost
m
113,500
6.67
757,045
Man days
3,390
200
678,000
No
1,095
200
219,000
8,064
8
64,512
3,618,843
127.60
(2 times a year)
(Rs. 5000/acre/1.5 tractor/500 m)
Mulch Removal and Replacement
Helper (man days)
Weed removal (assumed 5%) Mulch prevent weeds
Sq. m
Total cost of Maintenance using Mulching
Costing Per Plant
11 Acknowledgements
The Author thanks PMI for giving
the opportunity to present the paper.
The Author also thanks entire team of
Rajahmundry Site team comprising
M/s. Bhagavan Raju, Kashinath,
Apparao and other team members
besides GIPL Management for
facilitating this experimentation to
give way for this new thought process.
The Author also thanks Mr. M. U.
Shah, member- BoM for his constant
guidance and encouragement in
submitting this paper. The Author also
thanks Mr. E. Krishna Murthy, PMP
and Mr. V. S. Pillai for their valuable
INDIAN HIGHWAYS, April 2015
support to undertake this submission.
The Author also thanks various authors
shown in the references for providing
their various valuable insights in their
respective fields to culminate this
overall innovation into possible new
thought process of sustainable project
execution.
4.
References
5.
1.
2.
3.
Project Management Institute, “A
Guide to the Project Management
Body of Knowledge”, Chapter 8,
pp. 189-213.
CTAHR, “Mulching for Healthier
Landscape Plants”, Oct – 2007, L-3.
MM Odendaal, thesis on the
6.
Say Rs. 128/-
Estimation and Management of Cost
Over Life Cycle of Metallurgical
Research Projects Submitted to
University of Pretoria, Feb 2009.
Giedrius
Grondskis,
Alfreda
Sapkauskiene – Cost Accounting
Information use for Product Mix
Design, Eknomica IR Vadyaba,
2011:16.
James R. Wixson, CVS, CMfgE,
Function Analysis and Decomposition using Function Analysis Systems
Technique.
Hussein Ali Mohammed, University
of Karbala, Role of Value Engineering in the Sustainable Construction
Projects.
21
UTTARAKHAND DELUGE – MAN-MADE
Er. W. Rahman* and Er. Akhilesh Kumar Gupta**
ABSTRACT
The upper Himalayan territories of Himachal Pradesh and Uttarakhand are full of forests and snow-covered mountains. They are home to several major
and historic Hindu and Sikh pilgrimage sites besides several tourist spots and trekking trails. From 14 to 17 June 2013, the Indian state of Uttarakhand
and adjoining areas received heavy rainfall, which was about 375 percent more than the benchmark rainfall during a normal monsoon, due to ecological
imbalance, in the hills of Uttarakhand rainfall is becoming variable & unseasonal. This caused the melting of Chorabari Glacier at the height of 3800
metres, and eruption of the Mandakini River which led to heavy floods near Gobindghat, Kedar Dome, Rudraprayag district, Uttarakhand, Himachal
Pradesh, Nepal and Northern India. Destruction of bridges and roads left about 100,000 pilgrims and tourists trapped in the valleys leading to three
of the four Hindu Chota Char Dham pilgrimage sites. It is Man-Made factors, unscientific human interference with the youngest and fragile hills of
Uttarakhand are responsible to a great extent, for the wreckage of Uttarakhand of June 2013.
The incessant rain that hit Uttarakhand triggered flash floods and landslides, led to thousands of deaths, while thousands more missing. The Indian Air
Force, the Indian Army, and paramilitary troops evacuated more than 110,000 people from the flood ravaged areas.
The unplanned infrastructure development done in the past decade in the fragile hills of Uttarakhand, without taking in to consideration environmental
aspects & ecological aspects i.e. unscientific way of roads and building constructions (heavy blasting), indiscriminating dynamiting& quarrying,
felling of trees, and cutting of forest, power project build to next to each other on flood prone rives of Uttarakhand, and encroachment on river banks
have totally damaged the hills of Uttarakhand resulting “Ecological Imbalance”, that led to uncontrolled flow of water in the flood prone rivers of
Uttarakhand and heavy landslides, resulted to “Disaster Waiting to Happen".
Until we find a vaccine for the two kinds of diseased developmental pragmatisms afflicting us – the rational and the rapacious, we might have to get
used to such tragedies, as of the Uttarakhand Disaster June 2013.
1INTRODUCTION
The Uttarakhand region has been target
of intense development activities,
since it was born on 9th November
2002. Bestowed with scenic beauty,
bracing climate and excellent agro –
climatic conditions, Uttarakhand is
highly suitable for development of
tourism, as well as have great potential
for economic growth in development
of agro – horticulture based economy,
beside wild life, adventure or
pilgrimage. Uttarakhand is very rich
in natural resources too.
Uttarakhand has a total area of
53,484 km2 of which 93% is
mountainous and 64% is covered
by forest. Most of the Uttarakhand
part of the state is covered by
high Himalayan peaks
and
glaciers. Two of India’s largest
rivers, the Ganges and the Yamuna,
originate
in
the
glaciers
of
Uttarakhand. These two pilgrimage,
Badrinath and Kedarnath form
the Chota Char Dham lies in
Uttarakhand. It is well know as the
“Land of the Gods“. Uttarakhand is
also well known for its “chhota char
dham”:  Kedarnath Temple
 Badrinath Temple
 Gangotri Temple
 Yamunotri Temple
Kedarnath Temple
*Ex-Chief Engineer UPPWD/Consultant, **Senior Vice President (Highways), ICT Pvt. Ltd., New Delhi.
22
INDIAN HIGHWAYS, April 2015
TECHNICAL PAPERS
Badrinath Temple
Several modes of transport are
prevalent in our country, but
unfortunately in hilly areas of
Uttarakhand,
because
of
the
topography and other physical
features, roads remains the only mode
of transport for Uttarakhand people.
The roads in hills not only provides the
vital connection between the remotest
Gangotri Temple
corner of hill region, facilitating
movement of goods and men , but also
forms an important vehicle for social
interaction and economic upliftment,
bringing the backward people into the
Nation’s mainstream. It goes without
saying that good roads network is the
pre-requisite for the social-economic
development of Uttarakhand state.
Existing Roads in Uttrakhand
A View of Nanital Lake
It is also a fact that good infrastructure
development has taken place in
Uttarakhand, in the past decade, or
so, but unfortunately due care &
INDIAN HIGHWAYS, April 2015
Panormic View of Nanital
precautions had not been taken in the
Himalayas region of Uttarakhand,
being worlds, youngest mountain
range, prone to landslides, floods,
Yamunotri Temple
folded and faulted. Hardly, any
attention was given to environment
& ecological consideration in the
development plans of Uttarakhand.
The concept of improvement without
much degradation was missing.
Indiscriminately
dynamiting
&
quarrying, felling of trees, power
projects built next to each other on
Alaknanda & Bhagirathi Rivers –
flood prone rivers. Encroachment on
river banks, forest & dangerous slopes
(hotels & restaurants), have damaged
the hills of Uttarakhand.
2MAN AS THE AGENT OF
CHANGE
What took place in Uttarakhand on
June 16th & 17th; 2013 was actually
a tragedy waiting to happen, as
Uttarakhand
Himalayas
region
has seen unchecked construction
activities, illegal & legal mining,
unscientific way of road & building
construction
and,
of
course,
hydropower projects built next to
each other. In Kedarnath, large scale
construction has been done on the land
evacuated by glacier in the past few
years. Unscientific human interference
with the nature is responsible for the
wreckage of Uttarakhand. In view of
ecological imbalance in the hills of
Uttarakhand, rainfall is also becoming
variable and unseasonal. This is what
happened in Uttarakhand on that
fateful day June 16th, 2013, it rained
without a break; some 200 mm
came down within hours at few
23
TECHNICAL PAPERS
places in Uttarakhand. Rain was also
unseasonal; June is still not considered
the beginning of the monsoon season
in Uttarakhand, so pilgrims and
tourists visiting the region were
caught unaware. It brought down
the mighty Himalayas. It is believed
that in this period between June 16th
& 17th 2013, large number of slides
had occurred along the river valley
of Mandakini, Mandaini, Kali and
Madhya Maheshwar in Kedar Valley.
What really compounded the disaster
– made it truly man – made – is the
scale of development intervention in
the past decades or so. The mountain
of Uttarakhand are bleeding and its
NASA Satellite Imagery of Northern India
on 17th June 2013, Showing Rainclouds
that Led to the Disaster
people have been left battered, bruised
and dead. The images of building
tumbling down like cardboard boxes
in the ragging water of Bhagirathi,
Mandakni and Alaknanda will stay with
all of us for a long time. Numbers of
villages wiped out, property damaged,
road and bridges washed away and
Hydropower projects damaged in the
mountain state of Uttarakhand. So far
as the estimates regarding the death
toll in the calamity of Uttarakhand
on June 16th - 17th 2013 is concerned
nobody is quite certain. However, the
figures are shockingly high. This is the
deadly and painful cost of environment
mismanagement.
A View of Landslide
Few Photographs of Kedar Valley after Uttarakhand Disaster June 2013
24
Several
Environmentalists
have
described the death & damages of
Uttarakhand of June 2013, as a Man
– Made disaster. In other words we
can say that a mixture of many lapses
added to the severity of devastation in
Uttarakhand in June 2013. The painful
things which happen to us are not
punishment of our misbehavior, nor are
they part of God’s design. Tragedies
are part of natural law, ecologically, it
is Mother Nature’s balancing act.
It is true that development of any
infrastructure project in hilly areas in
many ways goes in contradiction to
conservation of nature and promotes
encroachment upon echo system. To be
honest, the infrastructure developments
in hills, from the geological point
of view are such that it can never be
possible to eradicate them in totality.
However, these problems could be
minimized to the level of acceptability
if proper & careful measures are taken
from the stage of project conception.
Mr. James Hutton, the founder of
modern geology predicted more than
200 years ago that hills and mountains
of Himalayas region of the present
days are far from being everlasting
and the surface of the land is made by
nature to decay. Whereas his prophecy
has largely come true, he certainly
failed to realize that one day man
himself will compound the problems
and may even take it to the, point of no
return. Memory is very short lived and
we even forget the major catastrophe
happened in the young & vulnerable
Himalayas of Uttarakhand in the past.
A few years ago before the new state
of Uttarakhand was born, the Malpa
rock avalanche tragedy of 18th August
1998, hit the newspaper headlines, as it
instantly killed 220 people and wiped
out the entire village of Malpa on the
right bank of river kali in Kumaon
region of Uttarakhand.
INDIAN HIGHWAYS, April 2015
TECHNICAL PAPERS
Photograph of Malpa Rock Avalanche
One should not forget the severity of
landslide problems in the youngest
and vulnerable mountain range of
Uttarakhand. The divesting debris
flew in the year 1880 on the slopes
of Sher-ka-danda in Nainital district
of Uttarakhand. It was so swift that
it traveled 1 km in 30 seconds, killed
150 people and swept away “Victory
Hotel”, Naina Temple and other big
buildings and filled part of the Naini
Lake.
A View of Nanital – Year 1880; Before and After Land Slide Hazard
Now the Government of Uttarakhand
shall have to rethink of the existing
policies, regarding infrastructure
development at Uttarakhand, unregulated urbanization, deforestation
which triggers landslides and ill –
planned development projects, which
degrade the environment have to
be stopped. Commercialization of
pilgrimage routes with encroachment
on the river banks, forest & dangerous
slopes (Hotels & Restaurants) have to
stopped and demolished if necessary.
A numbers of hydropower projects on
the Bhagirathi and Alaknanda rivers
damaging hills and increasing the
possibility of flashfloods have to be
stopped. Tourists & Pilgrims entries
are to be restricted. It is a wakeup
call for Authorities of Uttarakhand
to reconsider their infrastructure
development model in the hilly areas
of Uttarakhand to cater for the fragility
& vulnerability of the region. Apart
from the reduction in size and greenery
of forests, instability of the hill sides
in Uttarakhand, causing damages to
property & lives has been reached to the
INDIAN HIGHWAYS, April 2015
extent of disaster. It is a time to ensure
that the infrastructure development in
Uttarakhand blend with environment,
facilitating its nourishment besides
serving the people of the area. It
cannot be anybody’s contention that
Himalaya region of Uttarakhand must
not see development. The question to
consider is how it should develop, road
constructions, building constructions
and hydropower projects or local
economics based on tourism, which do
not work against nature. The way ahead
is to give due respect to the vulnerability
of the hilly region of Uttarakhand. A
general awareness in the Engineering
profession needs to be created, so that
our environment is protected while
planning of infrastructure development
in Hilly areas of Uttarakhand. There is
a need to understand that sustainable
development is only possible by
maintaining the ecological balance.
It is the time to understand that
drawing from the hill cannot be oneway process. The approach should be
development activities in harmony with
ecological balance, so as to promote
the quality of life of hill people of
Uttarakhand.
Construction of roads in hills
requires imaginative planning and
methodical construction, adopting
environmentally friendly construction
techniques, environmentally friendly
materials, and mechanized techniques.
But when Engineers work against time,
they may not even have the basic data
on geological formation, topography,
drainage pattern etc., and as a result,
some of the hill roads begin. One
should not forget that every kilometer
of road when constructed in hills may
bring about a stress relief equivalent to
about 1-2 lakh tons of rock mass and
if cuttings are not properly protected,
as per the present practice of in
discriminate dynamiting, the most
fast & economical method of road
construction, landslides and rock falls
become imminent, adding additional
of about 1,000 tone of land loss per
km annually. At many major landslide
locations, the debris clearance may
well be of the order of 4000 – 5000
tons annually. The construction of hill
roads, therefore, calls for a greater
expertise. A little thought bestowed in
the initial stages of planning, design
& construction of hill roads will go a
long way towards preservation of the
environment.
3ECOLOGICAL
CONSIDERATION
IN
DESIGN,
CONSTRUCTION & MAINTENANCE OF HILLS ROADS
IN UTTARAKHAND
The construction of roads in
Himalayan region of Uttarakhand
calls for a greater expertise & skill by
adopting the best engineering practice
to have minimum effect on physical
environment. The basic guiding
principles in hill road construction
should be improvement without much
degradation, environmental friendly
materials & environmental friendly
constructions techniques are to be
adopted. The hill road construction in
25
TECHNICAL PAPERS
Uttarakhand by the normal & cheapest
method by blasting operation needs
to be avoided, as far as possible.
However, if unavoidable well qualified
and trained hands be entrusted with
the task of designing and executing
“controlled blasting”, as per prescribed
specification, after taking due safety
measures as prescribed in the code of
practices. On one side execution of
development plans are essential for
the upliftment of backward areas of
hilly regions of Uttarakhand, while
on other side soil, vegetation and
atmosphere has to be saved. It is vital
to preserve various eco-systems which
support human life. Every human
activity effects the environment
and environmental changes affect
human life. Hill road development in
Uttarakhand is a complex problem and
all the activities involved in hill road
construction are inter-related. Tackling
each activity individually does not
provide correct solutions; it should be
taken as integrated system.
Hill road construction is basically
cutting a seat into natural hill face,
the cutting can be either be full or part
cut & part fill by doing so, the natural
geo-physical setting is disturbed
and problem of stability arise more
often than not. The problem is
more accentuated if the stratum met
with, was already adversely placed
from geological point of view. In
Uttarakhand the Himalayan hills
which are geologically quite young &
fragile, highly folded and faulted, road
construction is normally be set with
large number of stability problems.
It is therefore, necessary to properly
investigate and design the hill slopes
before execution of any hill road
construction work in Uttarakhand,
with the path breaking advance in
space technology and remote sensing,
it is possible to map landslides to a
fair degree of accuracy. Thus, most
landslide disaster in the hills of
Uttarakhand could be averted by the
26
Engineers by taking timely appropriate
action. Thus, careful & detail study
of Stability of material slopes and
control of landslides should be form
an integral part of any hill road design
& construction in the hilly regions
Uttarakhand. Once the landslides
problem is solved in the hills of
Uttarakhand, no further loss of land,
property & lives of the people will
take place in the hills of Uttarakhand.
No blockage/closure of Holy corridors
in Uttarakhand will take place beside
better transportation & communication
will be available in the hilly region of
Uttarakhand. In short, the performance
of a hill road is directly proportional to
degree of stability of slopes on which
it has been built.
Construction of the ropeways
in Uttarakhand shall curtail the
disturbance of the ecology. Viaducts
and tunnel construction should be
given preference in the Himalayan
regions of Uttarakhand to have zero
landslides & blockage problem.
Suitably located and appropriately
designed cross drainage work has
to be provided in the entire length
of the road so as to provide quick
and efficient disposal of water to the
valley side. Proper drainage not only
reduces the weight of the mass tending
to slide but also increases the strength
of the slope-forming material. Mere
provision of drains, culverts and
drainage chutes does not help, if it is
not ensured that the catchment would
effectively feed them and the drainage
system is firmly founded. Surface
drains are to be located very carefully
after detail study of the topography of
the ground. As far as possible, cross
drainage should be provided at right
angles to the road.
Environment assessment plays a very
important part in the investigation for
hill roads construction. It is necessary
to identify, examine and evaluate all
the natural and social environmental
aspects so that they can be considered
along with the Economic &
Engineering factors and the broader
planning issues during the initial
development stage of the proposal
for any road construction in the hilly
regions of Uttarakhand.
Plantation of new trees, herbs &
vegetation should be done as much as
possible on the exposed areas resulted
from hill cutting operations, selection
of proper types of plants & vegetation
is necessary.
The storm water should be properly
intercepted and disposed of safely
by providing interceptor drains, side
drains & catch water drains should
be provided at the right place. High
velocity and falls in the cross drainage
should be controlled by means of
bed bars, check walls, water cushion
and other energy dissipation devices
so as to curtail down their scouring
capacity.
The present practice of preventing
slope failure by, making random
rubble masonry or dry masonry walls,
sometimes with vertical and horizontal
masonry bends has to be replaced by
construction of Eco friendly gabion
walls, which are flexible, permeable
and hence can cope with differential
settlement problem of foundation and
require less space, than rock buttress.
The combination of gabion wall and
short cerate, the factor of safety comes
well above the critical value.
However, where earth fills with high
retaining walls exists, it has to be
ensured that the back fill used is having
good drainage characteristics. Weep
holes of retaining walls & breast walls
should be cleared & all vegetative
growth/blocked drains should be
removed before onset of monsoon.
Sealing of tension cracks present in all
slopes, has to be done by short cerate
& grouting to prevent any ingress of
water. Slope treatment by vegetative
turfing, jute mesh/coir mesh should be
adopted to prevent erosion and help the
INDIAN HIGHWAYS, April 2015
TECHNICAL PAPERS
vegetation to grow on slope. Mulching
treatment for protection of hill slopes
is also extremely beneficial, as it
reduces water loss from soil, minimize
weed competitions and improves soil
structure.
Gabbion Walls Construction
Mulching Treatment for Slope Protection on Hill Roads
The hill road will remain safe after
proper slope treatment has been carried
out, and the same can also be repeated
INDIAN HIGHWAYS, April 2015
in case required before and after every
rainy season.
All excavated materials from road
construction & improvement in the
hilly region of Uttarakhand, goes
down the hills, deface and degrade the
27
TECHNICAL PAPERS
land below & above, due to which the
top soil adversely effects the growth
of vegetation, trees etc. and thus
causes ecological imbalance. Beside
the enormous quantities of soil, rock
fragments, debris which goes down
to the stream of rivers below the hills
on valley side, the rate of erosion in
the catchment area of the Himalayan
rivers of Uttarakhand has increased
manifold, resulting rapid siltation of
reservoirs and dams. It was estimated
in the year 1990 each kilometer of
road in hills require displacement of
40 to 80 thousand cubic meter of
debris. The eroded debris carried by
Himalayan Rivers of Uttarakhand
shall always remain vulnerable to
flash floods.
This unhealthy construction practice
has to be stopped by introducing some
judicious technical method to avoid
construction materials & debris going
to the rivers on the valley side, such as
build stones wall on the valley sides,
then pour earth to widen hill roads, no
debris or any materials be allowed to
go down the valley side to increase the
silting problem of Himalayan rivers
of Uttarakhand. Modern earth work
equipment may be used to remove
the mass earth work & other materials
from the construction site of work, to
be deposited at safer & proper place.
Proper monitoring of surface and
subsurface movements and pore water
pressures (Piezometric) in all sensitive
& critical hilly areas of Uttarakhand
has to be noted carefully and
monitored. A proper data bank has
to be developed, to forecast the
possibility of landslides disaster.
To minimize disturbance on hill side
it is advisable to construct road in half
cut & half fill, if not in all sections of
hill road, but at sensitive locations the
practice be gainfully employed.
4EARLY WARNING SYSTEM
FOR
UTTARAKHAND
DISASTER
In view of the prediction of the
geologist, that the young Himalayan
28
hills of Uttarakhand, the surface of the
land is made by nature to decay and is
not everlasting, there is an urgent need
to develop a proper warning system
in Uttarakhand that alerts, residents,
tourists and pilgrims across Himalayan
regions of Uttarakhand. The need in
Uttarakhand is to pre-empt the disaster
by disseminating information available
before it strikes. This is only possible,
when several Government agencies
have constant proper interaction
and work closely. The Geological
Survey of India (GSI) must identify
vulnerable hilly area of Uttarakhand.
Indian Space Research Organization
(ISRO) though satellite mapping must
identify all critical areas having cracks
etc. in the hills of Uttarakhand. The
MET department must give advance
warning of inclement weather. Once
in Uttarakhand the proper warning
system is made effective, collateral
damages of the kind unleashed in
Uttarakhand on June 16th - 17th 2013,
can be prevented to a great extent.
However, the need of the hour
for
Uttarakhand
infrastructure
development
is
sustainable
development
with
ecological
balance. The bottom line is that the
development authorities responsible
for
infrastructure
development
in Uttarakhand have to response
on priority to the wakeup call of
Uttarakhand wreckage of 16th - 17th
June 2013. To accomplish the goal,
the policy makers, concerned with the
development project in Uttarakhand,
must understand that a “Decade of
Action” must be a “Decade of Change”
to be effective. They cannot continue
to do the same things and except better
results. It is the time that the authorities
responsible
for
infrastructure
development in Uttarakhand should
make a strong commitment to meet
this great challenge to avoid further
wreckage of Uttarakhand in the
coming future. As one can see that a
dark and lengthening shadow of an
“Ecological Disaster” looms large
across the future population living
in Himalayan region of Uttarakhand.
The development authorities of
Uttarakhand have to ensure more
ecological
friendly
construction
processes, procedures, techniques
and technology to not only reduce
degradation of the eco-system but to
create a process of rehabilitation of
eco-system that has been degraded,
destroyed or damaged in the hills of
Uttarakhand. No development plans
of Uttarakhand are to be cleared
without proper geological and
geotechnical investigations, besides
till adequate provision is made for
protective measures adopted to
prevent degradation of environment.
Construction
and
development
activities for hilly region of
Uttarakhand should be appropriately
regulated with in-built provision
for simultaneous implementation of
protective measures, short and longterm interests should be safeguarded
through systematically launched and
strictly monitored with scientific
studies, old constructions should
be appropriately strengthened and
maintained.
The wreckage of Uttarakhand on 16th
– 17th June 2013 is a wakeup call for
the authorities of Uttarakhand; it is the
time to treat the health of Himalayans
hills of Uttarakhand. If your doctor
is 98 percent sure you had a serious
disease, one should immediately
start looking for the cure, if not, and
death is imminent. The way ahead is
to respect the vulnerability of hills of
Uttarakhand, to avoid the repeat of
Himalayan tragedy. The development
authorities of Uttarakhand had to
now ensure zero tolerance against
deliberate environmental violence &
unhealthy construction practice in the
young Himalayans of Uttarakhand.
This may sound like a dooms day
prediction but if the authorities of
Uttarakhand are not waken up and
human activities in Uttarakhand,
relating to expansion on unstable
slopes or locations, unscientific
quarrying & mining, unsafe haphazard
construction of roads, dams and river
training works, ignoring environmental
INDIAN HIGHWAYS, April 2015
TECHNICAL PAPERS
& natural features are continued in
Uttarakhand, the extent of calamities
in Uttarakhand will only multiply,
with point of no return.
Few photographs of rescue operations
of Uttarakhand Deluge – June 2013
only taken up, in phases as per the
urgency & availability of funds with
the Government of Uttarakhand.
ACKNOWLEDGEMENT
The pictures and data referred above
are
courtesy
of
government
broadcasting agencies and literature
provided
by
the
newspapers,
magazine, and reports etc. during the
disaster of Uttarakhand in June 2013.
REFERENCES
5
CONCLUSIONS
A wakeup call for the authorities
of Uttarakhand responsible for
development work in the state,
to rethink of the existing policies
for development in the light of
“Ecological Disaster” looms across
the future population living in
Himalayan region of Uttarakhand.
The authorities of Uttarakhand have to
make stringent rules & regulations for
“Zero Tolerance” against deliberate
environmental violence & unhealthy
INDIAN HIGHWAYS, April 2015
construction activities prevailing in
the hills of Uttarakhand. A holistic
short term & long term policies for
development of different regions
(depending on Geological strata)
of Uttarakhand is to be formulated
at the Government level, with the
involvement of local Panchayat,
influential & experience people of
that particular regions to make
a “Disaster Free Model” for
development of that particular region.
The construction work in that region,
1.
2.
3.
4.
Kala, C.P. Deluge, disaster and development in Uttarakhand Himalayan region of India: Challenges and
lessons for disaster management.
International Journal of Disaster
Risk Reduction, 2014.
Uttarakhand: Army Commander walks with 500 people out of
Badrinath.
“Uttarakhand: Rescue efforts in full
swing”. 18 June 2013.
Kedarnath temple in Uttarakhand
survives glacier, floods Down to
Earth.
29
Government of Tamil Nadu
NATIONAL HIGHWAYS CIRCLE
MADURAI- 625 002
Ph: 0452-2530540 e-mail: [email protected]
TENDER NOTICE No. 4/2015/DO/Dt. 19.03.2015
For and on behalf of Governor of Tamil Nadu the Superintending Engineer, National
Highways, Madurai invite tender (Two Cover System) through Online only for Construction
works as detailed in the table.
Sl.
No.
Name of the work
1
2
1
Periodical renewal in
km 5/0-9/0, 11/0-16/0,
38/0-48/0 of Trichy
Chidambaram Road
on NH 227
Value of
work in
lakhs
3
912.20
Bid
Security
in Rupees
4
18,25,000
Cost of tender
document plus
VAT in Rs.
(Not refundable)
Concerned
NH
Division
5
6
15000/+ 750/-
Divisional
Engineer
(NH)
Thanjavur
Period of
Completion
in months
7
9 (Nine
Months)
1. Tender documents are available Online in the website https://morth.eproc.in
upto 15.00 hrs. of 23.04.2015.
2. Submission of Tender through Online can be done upto 15.00 hrs. of 23.04.2015.
3. Bids will be opened on 30.04.2015 by 15.00 hrs in the office of the Chief Engineer
(NH) at Chepauk, Chennai.
4. Pre bid meeting will be held on 07.04.2015 by 11.00 am at office of the
Superintending Engineer (NH) Circle, Madurai -02 .
5. The bidders must possess Digital Signature Certificate of Class III (Signing &
Encryption) for submission of bids through online in the above website.
6. The bidders shall be paid required tender processing fee as furnished in Tender
Document (non-refundable) to M/s C1 India Pvt Ltd against tender Processing Fee
through E-Payment gateway using Credit Card/ Debit Card- Master Card and Visa Card
only
7. The original financial instruments such as cost of bidding document, Bid Security and
the original / attested document shall
be
received
by the Superintending
Engineer (NH), Madurai / Divisional Engineers (NH), Thanjavur / Chief Engineer (NH),
Chepauk, Chennai / Regional Officer, MORT&H, Chennai & Chief Engineer (P7),
MORT&H, GOI, New Delhi on or before 29.04.2015, 15.00 hrs. failing which the bid
shall be summarily rejected.
8. Further details can be seen on Web site https://morth.eproc.in
DIPR/1469/Tender/2015
Superientending Engineer,
N.H.Circle, Madurai-02
IRC - 23CMS X 17CMS
30
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INDIAN HIGHWAYS, April 2015
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