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
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