ITE Traffic Engineering Workshop and
Planning Forum
April 22, 2015
Predicting Recurring and Non-Recurring Delay
for a Benefit-Cost Analysis Tool
Dawn Krahn, P.E.
Todd Polum, P.E
[email protected]
[email protected]
Project Objectives
• WisDOT uses Benefit-Cost Analysis to evaluate candidate Major Highway Projects
• Major Highway Project defined in State Statutes 84.013(1)
• Over $33.4 million and adding capacity for 2.5,5 or 10 miles
• Over $83.5 million
WisDOT
Evaluates
and
Recommends
Major
Projects to
Study
TPC
Selects
Major Projects
for
Environmental
Study
WisDOT
Completes
Environmental
Study and
Preferred
Alternative
Selected
WisDOT
Evaluates
and
Recommends
Candidate
Major
Projects
TPC
Recommends
Candidate
Major
Projects for
Enumeration
to Governor,
Legislature
and JCF
Projects
Enumerated
in State
Budget
Benefit-Cost
Analysis
2
Project Objectives
• Determine economic value of a highway capacity expansion project
• Evaluate the stream of both the benefits and costs over the life of facility
 BC Ratio = Present Value of Benefits/Present Value of Cost, B/C > 1.0
 Net Present Value (NPV) = PV of Benefits – PV of Costs, NPV > 0
• Main objective is to maximize Net Present Value (NPV)
PV Benefits
PV Costs
Net Present Value
BC Ratio
Project A
$ 200 m
$ 50 m
$150 m
4.0
Project B
$ 230 m
$ 60 m
$ 170 m
3.8
3
Project Benefits
Traditional Benefits:
• Travel time savings–reduction in recurring congestion by users of the roadway
Speed (mph)
80
60
40
4‐Lane Speed
No‐Build
Build
6‐Lane Speed
20
0
0
2,000
4,000
6,000
8,000
10,000
Volume (vph)
• Crash costs savings -- reduction in fatal/injury/property damage crashes
• Vehicle operating savings -- reduction in user expenditures (fuel, oil, tires, vehicle
maintenance and depreciation )
4
Project Costs
Base Year
Open to Traffic
52 Years
End of Analysis
Build
Capital Cost
Rehab and Maintenance
52 Years
No-Build
Rehab and
Maintenance
Reconstruction
Cost
Rehab and Maintenance
Remaining
Capital Value
5
Travel Time Savings
• Traditional Approach was Missing Important
Travel Time Benefits due to:
 Crash
or Incident
 Snow or Bad Weather
 Work Zone Conditions
 Special Event Traffic
• Goal -- Develop a model to capture travel delays caused
by both recurring and non-recurring congestion
Sample data from I‐94 Minneapolis to St. Paul
• Methodology – Developed using concepts from:
• SHRP2 Pilot Reliability Study in MN
• FDOT’s Predictive Travel Time Reliability Model for Freeway System
6
Data Collection Corridors
• Approximately 800 directional miles
• Freeways -- 4 and 6 lanes
• Rural two-lane highways
• Urban arterials
• 3 years of Travel Time Data
•
1 to 5 min. intervals
• ATR Continuous Volume Data
• Sites with highest combined volumes and
crashes received priority
• 90% used for model development
10% used to verify and calibrate
7
Example Travel Time Data
•Travel Time Data Filtered to only include Real Time Data
8
Travel Reliability – CDF Curves
100%
90%
Cumulative Frequency
80%
70%
60%
Normal Conditions
50%
Rain
40%
Snow
30%
Incident
20%
Rain+Incident
10%
Snow+Incident
0%
0
2
3.5 4
6
8
6.8
Travel Time (min)
10
12
14
16
9
Travel Time Scenarios
Condition
Characteristics
1. Normal
None of the non-recurring conditions present
Only influence on travel time is volume
2. Snow
“Low”, “Medium”, and “High” intensity from NOAA data
3. Crash
Accident identified from MV4000 data
4. Incident
Non-crash event identified from STOC EventManager data
5. Crash+ Snow
Crash identified during snow conditions
6. Incident+ Snow Incident identified during snow conditions
10
Travel Time Model Process
1. Determine Hourly Volumes
2. Estimate Hourly Travel Time for each Scenario
3. Estimate Probability of Occurrence for each Scenario
4. Sum All Scenario Outcomes to Obtain Annual Performance
11
Travel Time Model Process
Step 1 ) Determine Hourly Volumes
• Continuous Traffic Count Data -- averaged using hourly percent of AADT
• Hourly volume profiles developed for 109 Days
• 84 non holidays (12 months x 7 days)
• 25 holidays and unique travel days
Wednesday
500
6‐Jun
Hourly Volume
400
13‐Jun
300
20‐Jun
27‐Jun
200
4‐Jul
100
11‐Jul
18‐Jul
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
25‐Jul
12
Peak Spreading
• Hourly volume profile adjusted to reflect peak spreading
• Excessive hourly demands reduced to avoid unrealistic travel times
• Surplus demand distributed to hours before and after peak with reserve
capacity
12,000
Raw Demand
Hourly Volume
10,000
Peak Spreading
8,000
6,000
4,000
2,000
0
4:00 AM
6:00 AM
8:00 AM
10:00 AM
12:00 PM
2:00 PM
4:00 PM
6:00 PM
8:00 PM
13
Travel Time Model Process
Step 2 ) Estimate Hourly Travel Time
Volume
Inrix Travel Times
Crash Data
MV4000
Incident
Event‐
Manager
NOAA Weather
Meta‐
Manager
RWIS
Combined Data Base
>80 million records
Freeway Capacity and Speed Flow Curves
1.
2.
3.
4.
5.
6.
Normal
Snow
Crash
Crash + Snow
Incident
Incident + Snow
Rural Arterial Capacity and Speed‐Flow Curves
Urban Arterial Capacity and Speed‐Flow Curves
1.
2.
3.
4.
5.
6.
1.
2.
3.
4.
5.
6.
Normal
Snow
Crash
Crash + Snow
Incident
Incident + Snow
Normal
Snow
Crash
Crash + Snow
Incident
Incident + Snow
14
Flow vs. Speed Data – 4-Lane Freeway
15
Flow vs. Speed Data – 4-Lane Freeway
16
Normal Conditions – 4-Lane Freeway
70
60
Estimated
Curve
Speed (mph)
50
40
30
65 mph
NCHRP
Curve
20
10
0
0
1000
2000
3000
4000
5000
6000
7000
8000
Volume (passenger car equivalent/hr)
17
Snow Conditions
• Estimation process repeated for other scenarios
• Lower free-flow speed and capacity observed for snow conditions
70
Speed (mph)
60
50
Normal Conditions
40
Snow Conditions
30
20
10
0
0
1000
2000
3000
4000
5000
6000
7000
Volume (passenger car equivalent/hr)
18
Crash Conditions
• Additional delay was observed during crashes/incidents caused by
bottleneck point
• In cases with reduced throughput, demand in excess of bottleneck capacity
are stored in queue
60
Travel Time (min)
50
40
30
Normal Condition
20
Crash Condition
10
0
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
Volume/Capacity
19
Travel Time Equation Summary
70
Freeway Corridor with 65 mph FFS
60
Normal Conditions
Speed (mph)
50
Snow Conditions
Crash
40
Incident
30
Crash + Snow
Incident + Snow
20
10
0
0
1000
2000
3000
4000
5000
6000
7000
8000
Volume (pce/hr)
20
Travel Time Equation Summary
35
2‐Lane Urban Arterial Corridor with 30 mph Posted Speed
30
Signal density = 1.0 Access density = 1.2
25
Speed (mph)
Normal Conditions
20
Snow Conditions
Crash
15
Incident
10
Crash + Snow
Incident + Snow
5
0
0
500
1000
1500
2000
2500
3000
3500
4000
Volume (pce/hr)
21
Travel Time Model Process
3) Probability of Occurrence
• Snow Scenario
• Precipitation frequency
calculated using 8 years
of NOAA Weather data
• Frequency determined by
geographical area of the
state
22
Snow Frequencies
• Average Frequencies developed for each month by weather region
Snow – Northwest Region
25%
Average Frequency
20%
15%
Snow
10%
5%
0%
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sept
Oct
Nov
Dec
23
Probability of Crash Presence
Annual Crashes
• Segment crash rate applied to VMT, or
• Predicted crashes from detailed analysis (ISATE)
Monthly Crashes
• Monthly crash distribution based on historical averages
Hourly Crashes
• Volume‐
based crash risk distribution
Crash Duration
• Crash duration for more or less than one hour
24
Crash Frequency by Month
0.16
0.14
0.12
0.1
0.08
0.06
Crash %
0.04
0.02
0
25
Crash Risk Distribution
Crash Observations per 1000 Volume Occurrences
35
30
y = 1.7689e0.0007x
R² = 0.9146
25
20
15
10
5
0
0
500
1000
1500
2000
2500
3000
3500
4000
4500
Volume
26
Work Zone Evaluation
• Work Zone delay computed for major life-cycle rehabilitation improvements
Rehab Rehab Rehab Rehab
Rehab
Rehab
Rehab
Rehab
• Work zone travel time impacts based on capacity and speed calculated
using TOPS Lab work zone equations
• Frequency of work zone delay computed for:
• Year of scheduled Rehab improvement:
• Number of weeks estimated for that year
• Percent or work during day/night
27
Travel Time Model Process
1. Determine Hourly Volumes
2. Estimate Hourly Travel Time for each Scenario
3. Estimate Probability of Occurrence for each Scenario
4. Sum All Scenario Outcomes to Obtain Annual Performance
28
Travel Time Example Results
Forecast Year Vehicle Hours of Travel (VHT)
50
Annual VHT (million-vehicle-hours)
45
40
35
Workzone
Incident+Snow
30
Crash+Snow
25
Incident
Crash
20
Snow
15
Normal
10
5
0
No Build
Build
29
Benefit-Cost Inputs
1,200,000
1,000,000
Project
Benefit
Annual VHT
800,000
No Build VHT
600,000
Build VHT
400,000
200,000
0
2015
2020
2025
2030
2035
2040
2045
Benefit-Cost Analysis Process
31
Review of Benefit-Cost Guidance
Resources Referenced
Parameter
• Existing WisDOT BenefitCost Analysis Process
Analysis Period
52 years
• FHWA BCA Guidance
(TIGER Grant Process)
Discount Rate
5%
• MnDOT Guidance/
SRF BCA Tool
Value of Time
(2014 dollars)
Auto ‐ $19.10/hr
Truck ‐ $26.02/hr
• Facility Development
Manual (FDM)
Operating Cost
(2014 dollars)
Auto ~ $0.30 to $0.73/mi
Truck ~ $0.98 to $3.10/mi
Input Value
• AASHTO Red Book (2010)
• WisDOT Guidance
Crash Costs
Fatal ‐ $9.3M
Injury ‐ $61 ‐ 445k
PDO ‐ $3.9k
32
Benefit-Cost Network
• Network to include routes with Traffic Diversion
• Segment Analysis versus Node Analysis
• Benefit-Cost Analysis does not include:
• Detailed interchange and ramp geometry analysis
• Simulation-level queuing and spillback
33
Summary Results Example
• Benefit-Cost Performance Measures
• Net Present Value (NPV)
• Benefit-Cost Ratio (BCR)
Total
PV No Build
($Million)
$ 3,200
PV No Build
($Million)
PV Build
($Million)
$ 2,925
PV Build
($Million)
PV Project Benefits
($Million)
$ 275 PV Project Costs
($Million)
Total
$ 40
$ 115
$ 75
User Costs (Benefits)
Department Expenditures (Costs)
Net Present Value Benefit‐Cost Ratio
$ 200
3.6
34
Graphical Results Example
$20,000,000
$10,000,000
$0
-$10,000,000
-$20,000,000
Avoided No Build Costs
-$30,000,000
User Benefits
-$40,000,000
Build Costs
-$50,000,000
50
40
30
20
10
-$60,000,000
0
Present Value of Annual Costs and
Benefits
• Present Value of Constant Dollar Annual Costs and
Benefits (2014 Dollars)
Year
35
Graphical Results Example
• Aggregates total annual benefits and costs
• Calculates present value of annual savings
200
150
100
50
0
50
40
30
20
10
‐50
0
Cumulative Cash Flow (millions of $s) Cumulative Benefit‐Cost Stream
Year
36
Travel Time Reliability
Freeway (4.35 miles)
37
Reliability Measures
Travel Time Index
%
Buffer Index
%
Planning Time Index
Planning Time Failure / On-Time Measures
80th Percentile Travel Time Index
Misery Index
.
%
∗
%
. %
38
Travel Reliability – CDF Curves
100%
90%
Cumulative Frequency
80%
70%
60%
Normal Conditions
50%
Rain
40%
Snow
30%
Incident
20%
Rain+Incident
10%
Snow+Incident
0%
0
2
3.5 4
5.8 6
7.2 7.5 8
Travel Time (min)
10
12
14
16
39
Reliability Statistics
Reliability
Snow
Median
3.5 min
Free Flow
1.8 min
95th
%
7.2 min
80th
%
5.8 min
97.5th
%
7.5 min
Reliability Indices
Snow
Travel Time Index (TTI)
1.94
Buffer Index (BI)
1.06
Planning Time Index (PTI)
4.00
On‐Time Performance (OTP, 1.25)
20%
80th Percentile Travel Time Index (TTI80%)
3.22
Misery Index (MI)
4.17
40
Questions?
• Key Contacts:
• Dawn Krahn – WisDOT
• Todd Polum – SRF
• Paul Morris – SRF
• Ryan Loos – SRF
• Chengdong Cai – SRF
• Expert Panel:
•
•
•
•
•
•
•
•
•
Joe Nestler – WisDOT
Kasey Deiss – WisDOT
Keith Wendt -- WisDOT
Mark Wolfgram – SRF
Brian Porter -- WisDOT
Jen Murray – WisDOT
Paul Keltner -- WisDOT
Steven Parker – TOPS Lab
Peter Rafferty – TOPS Lab
41