An Analysis of TDM Impacts on a Corridor Segment Research Findings

An Analysis of TDM Impacts on a Corridor Segment Research Findings Phil Winters, CUTR TDM Program Director Liren Zhou, Graduate Research Assistant Sachin Rai, ITS Research Associate Nevine Georggi, TDM Research Associate Presentation Overview Review Study Background Study Objective and Hypothesis Study Methodology The Process Analysis Results Sensitivity Analysis Conclusions Future Research Recommendations 2

Study Background This study seeks to establish the relationship between employer-based TDM strategies and transportation system performance Study Objectives Develop a methodology for measuring the impacts of employer-based TDM programs on transportation system performance Communicate these impacts to traffic management and operations professionals 2

Study Hypothesis A wide scale adoption of employerbased strategies is likely to have a noticeable difference on the transportation system performance at the local, corridor and regional levels Study Methodology Simulate the impacts of the Washington State Commute Trip Reduction program affecting a segment of I- in Seattle Use selected traffic ops. performance measures to communicate impacts 6

National Transportation Operations Coalition - the few good measures Extent of congestion - spatial Extent of congestion - temporal Recurring delay Speed Travel time-link Customer satisfaction Incident duration Non-recurring delay Throughput - person Throughput - vehicle Travel time reliability (buffer time) Travel time trip Study will use for analysis of TDM impacts 7 Transportation Network of the Study Area Seattle Downtown Area High Density of employers participating in TDM programs in the area Number of employers - 89 Number of employees 6, Planned improvements for the transportation network by the DOT Pavement reconstruction and bottleneck improvement project on I- 8

Study Network Study Area 9 Employer worksites

I- Corridor Study Area hr peak Volume : 9,9 hr peak Volume : 2,6 SR 2 8.6 Mile Segment 67 lane-mile 6 on-ramps and 9 off-ramps I- I-9 hr peak Volume: 22, hr peak Volume : 9,8 Traffic Analysis Tool : CORSIM CORSIM is a stochastic microsimulation tool which is being used by practitioners and researchers for the past years to simulate and conduct various transportation related evaluations Development of CORSIM being supported by FHWA and it is used by several state agencies including FDOT and WSDOT Comparable studies conducted in the past using CORSIM CORSIM Data was available for the Seattle region Research team has past experience and training in CORSIM 2 6

7 2 2 2 2 22 2 2 9 8 7 6 2 9 8 7 2 2 22 2 2 9 8 7 6 2 9 8 7 6 2 2 LEGEND lane link lane link lane link 2 lane link On/Off Ramp Node Number # N 6 Northbound I- Southbound I- LINK-NODE DIAGR 26 - - - - - 9 2 8 2 2 2 2 2 76 2 22 8 22 2 28 6 2 2 8 6 7 2 2 9 7 7 8 9 8 8 9 8 7 2 6 9 7 6 2 6 2 6 2 6 2 2 2 2 8 6 2 8 2 2 7 2 2 6 2 6 6 7 2 9 2 7 8 22 9 8 78 8 9 628 8 7 9 2 92 7 6 2 2 2 8 6 2 2 22 78 22 2 22 2 2 22 2 28 2 2 28 2 Node B Node A Node B Node A Number of HOV Lane Number of non-hov Lanes Link Length (feet) Links Number of HOV Lane Number of non-hov Lanes Link Length (feet) Links SOUTHBOUND I- NORTHBOUND I- Network Geometry I- 2 2

Analysis Process Evaluate the impacts of TDM programs by comparing the performance measures of the transportation corridor with TDM programs and without TDM programs Scenario A (with TDM) = existing traffic volume Scenario B (without TDM) = existing volume + trips reduced by TDM due to CTR program The Scenarios... Scenarios Corridor Geometry Traffic Volume With TDM Programs (A) 2 Network Traffic volumes for the year 2 Without TDM Programs (B) 2 Network Traffic Volumes for the year 2 + Vehicle trips reduced by TDM programs (from CTR) 6 8

TDM Trip Reduction Estimation, Trip Distribution, and Trip Assignment Objective Provide link traffic flow change due to TDM Programs as input to CORSIM micro traffic simulation model Methodologies and data Estimating TDM reduced vehicle trips at employer level Distributing the estimated reduced vehicle trips to the Worksite-Home pairs Assigning the reduced vehicle trips to the highway network Output includes Number of reduced vehicle trips for each worksite Traffic flow change for each on and off ramp of I- within the study area On and off ramp ID for each reduced vehicle trip 7 Trips Reduced at a Glance Total number of worksites Total number of affected employees Total number of reduced vehicle trips Average percentage of TDM vehicle trip reduction Average Share of Driving Alone Average Share of Transit Total number of person trips Total number of vehicle trips Total number of reduced vehicle trips takes I- 89 6,2,9.2% With TDM Without TDM 6.9% 6.% 28.% 2.%,9,997,86,9 Peak Period Peak Period,,82 Total I- ramp traffic flow Average percentage of I- ramp traffic flow change 99,68.2% 9,7.% 8 9

Ramp traffic flow change for peak period (Home to Worksite Trip) On -Ramp Node On I- 2 6 6 8 2 2 6 9 2 2 2 On Ramp I- NB South End Corson NB Spokane NB I-9 NB University NB Oliver NB Mercer NB SR2 NB Harvard NB Spokane SB 6th SB th SB Yale SB Mercer SB Boylston SB SR2 SB th SB I- SB North End Total Original Flow 298 28 66 7 778 27 2927 288 8 2686 88 2826 27 2 76 87 89 97 Flow Change 7 2 8 7 2 9 88 Percent Change 6.% 6.% 2.%.%.6% %.2% % % %.2% %.%.% 8.6% 2.% %.%.% Off- Ramp Node On I- 9 2 7 9 22 2 2 6 7 2 7 8 2 22 Off Ramp Spokane NB I-9 NB th NB Seneca NB Oliver NB Mercer NB Lakeview NB SR2 NB th NB I- NB North End I- SB South End Corson SB Spokane SB Forest SB I-9 SB 6th SB Union SB Stewart SB Mercer SB SR2 SB Boylston SB Total Original Flow 76 9262 6 8 8 92 68 7 2 77 276 27 98 87 82 2726 277 299 2 992 9968 Flow Change 6 2 87 2 2 2 7 7 9 6 Percent Change.7%.% 8.% 9.%.% %.%.2% % % % %.%.2%.% 6.2% 9.% 9.8%.% 2.% %.2% 9 Trips Reduced by TDM Programs Additional Trips Vehicle Trips Peak (6: 9: ) NB SB 9 Total Peak (: 6: ) NB SB 9 Total Vehicle trips using I- 92 29 22 69 82 % of Total Trips..6.6.9..8 2

Analysis Period Morning Period Analysis Duration- 7 Time Periods (TPs) 2 Time Periods (TPs) of minutes TPs of minutes 6: 9: : Peak Period for Work Trips Evening Period Analysis Duration - 7 Time Periods 2 Time Periods (TPs) of minutes TPs of minutes : 6: 7: Peak Period for Work Trips 2 Reduced Link Volumes 2 2 NORTHBOUND Links % of Added Original Volume Volume 6. 2 98 6. 98 6. 98 6. 6 8.2 6 96 6. 7 96 6. 8 96 6. 9 6.2 9 9. 9 9. 2 97.8 2.8 7 2.7. 6.2 7. 8. 9. 2. 2 22 2 2 - - - Peak Links 2 2 2 22 2 2 9 8 7 6 2 9 8 7 6 2 SOUTHBOUND % of Added Original Volume Volume 88. 88. 88 9.2 88.2 778 2.6 928 8.9 29 8.9 87 9. 86 7.9 2 7. 2 6.2 2.7. 9. 9. 9. 9. 9. 9. 6 6 6 6 Peak NORTHBOUND Links % of Added Original Volume Volume Links 2 2 2 2 22 2 6 8. 2 7 8. 9 8 8. 8 9 6. 7 6. 6 6.2 2 6.2 87. 287 6. 2 28 7. 6 79 7.8 7 79 9. 9 8 262 8.8 8 9 9 8. 7 2 9 8. 6 2 7.9 22 77 8.6 2 86 8.2 2 86. 2 - - - SOUTHBOUND % of Added Original Volume Volume 2. 8. 8. 7. 8 2.2 2. 2 2.6 7. 7. 7.9 7.9 7.9 7 2. 2. 6 6.2 9 6. 9 6. 9 6. 2.9 22 I-

Performance Measures Delay in vehicle-hours and seconds per vehicle Extent of congestion Spatial Temporal Average speed in mph Vehicle miles traveled Fuel consumption in gallons Emissions in kg 2 Average Delay in Secs/Vehicle Average Delay is the delay per vehicle on a section of roadway during a predefined time period Delay is calculated as actual time taken by vehicle to traverse a section of roadway minus the time it would have if it was traveling at free-flow speed 2 2

2 2 Avg. Delay in Secs/Vehicle Period -.2 28 2779 2.2 2 2 2782.2 2 2 2782 268 22 2967. 2 2. 22 6. 267 2 282 7. 2669 9. 292 8. 2867 8. 292 9. 278 7.2 29 282 6-6.9 78 2 -. 29 2 26 -. 282.7 2 -. 2799. 9 2 9 -.6 282. 2768 6 -.2 266 22 7. 279 9 2.6 2679 8.2 8 8 8.6 9 9. 8 7 6. 29 2 797 6 2.2 962 2.6 27 269 22. 827. 27998 2 2. 822.6 29 2 27.6 8 2 28.7 28 2 2.7 289 Δ Average Delay (secs/vehicle) # of vehicles Link Δ Average Delay (secs/vehicle) # of vehicles Link SOUTHBOUND I- NORTHBOUND I- I- 2 2 26 26 Avg. Delay in Secs/Vehicle Period. 28762.2 28 2. 2282 2 2.2 2. 28 2 2. 22. 27 22 7.9 7. 296 2.9 2862 6.6 297 2.2 67 7 6.8 297 9.9 228 8 8.7 8 8 6. 228 9. 268 7.6 28 8. 77 6 2. 776 9. 29. 779 2.8 2626. 2729. 29 2. 6.7 97 2 8. 8 -. 268. 287 6 -. 2 6. 2262 7 2 9 8.7 2627 8. 29 8.6 88 9 2 7 9 2 22 6 2799 2. 282 27668 22. 296 -.2 2 296 -. 2672 2 296 2 -.7 26668 2 228 Δ Average Delay (secs/vehicle) # of vehicles Link Δ Average Delay (secs/vehicle) # of vehicles Link SOUTHBOUND I- NORTHBOUND I- I- 2 2

Total Delay in Vehicle-minutes Total Delay is delay accumulated for all the vehicles on a section of roadway for a predefined time period Delay is calculated as actual time taken by vehicle to traverse a section of roadway minus the time it would have if it was traveling at free-flow speed 27 Total Delay in Veh-minutes NB : Period 2, 8, 6, Delay (veh-mins), 2,, 8, 6, Time Periods with Significant Impact of TDM Significant Impact of TDM, 2, 6: 6: 6: 6: 7: 7: 7: 7: 8: 8: 8: 8: 9: 9: Time Period Scenario A (with TDM) Scenario B (without TDM) 9: 9: : 28

Total Delay in Veh-minutes SB : Period 8, 6, Delay (veh-mins), 2,, 8, 6,, 2, Time Periods with Significant Impact of TDM Significant Impact of TDM 6: 6: 6: 6: 7: 7: 7: 7: 8: 8: 8: 8: 9: 9: Time Period Scenario A (with TDM) Scenario B (without TDM) 9: 9: : 29 Total Delay in Veh-minutes NB : Period 8, 6,, Delay (veh-mins) 2,, 8, 6,, Time Periods with Significant Impact of TDM Significant Impact of TDM 2, : : : : : : : : : : : : 6: 6: 6: 6: 7: Time Period Scenario A (with TDM) Scenario B (without TDM)

Total Delay in Veh-minutes SB : Period, 2, Delay (veh-mins) 2,,,, Significant Impact of TDM Time Periods with Significant Impact of TDM : : : : : : : : : : : : 6: 6: 6: 6: 7: Time Period Scenario A (with TDM) Scenario B (without TDM) Spatial Extent of Congestion Spatial extent of congestion is the length of roadway within a predefined area and time period for which average travel time are % longer than unconstrained travel time Unconstrained travel time is the time it takes for the motorist to traverse a roadway section when traveling at the posted speed limit of 6 mph 2 6

Spatial Extent of Congestion Unconstrained Speed Speed limit: 6 mph Level of Spatial Congestion % longer or more than unconstrained travel time 6% longer or more than unconstrained travel time % longer or more than unconstrained travel time 2% longer or more than unconstrained travel time Congested Speed mph.6 mph 2. mph 2.7 mph Period: Spatial Extent of Congestion Spatial Congestion - Lane Miles ( period) Time Period % Longer or more 6% Longer or more % Longer or more 2% Longer or more Scenario A Scenario B Scenario A Scenario B Scenario A Scenario B Scenario A Scenario B 2. 2.. 9.7. 6.6. 6.6 2 2. 29. 6.7 22. 6.6 9. 6.6 2.6.9. 29. 29. 9.7 2.6 6.6 2.6. 6.2.7. 2. 2.6 2.6.9 6. 7. 28..7 2.6 2.7.9. 6..8 29.7 26.6 26.7 2.6. 7. 7 6..2 28. 29.6 2.7 2.6. 7. 8.2.2 27. 22. 2.6. 7. 9 2.7 2.7 27. 22. 2.. 7..8.2 27.7 28.9 2.7 2.6. 7..9.2 22.9 28.6 2.6 2.6 8. 7. 2 29.7.2 8.7. 2. 6.6. 9.2.2.9 2.6... 2. 2. 28. 8. 22..7.9 2. 29.7.7 2.7.7 9.6.7 2.6 6. 27.9.7 2.7.7 9.6. 7.7 22. 7.7.. Total 2.7.. 7.2 22.7.2. 2.9 % increase 2% % % 7% 7

Period: Spatial Extent of Congestion Spatial Congestion - Lane Miles ( period) Time Period % Longer or more 6% Longer or more % Longer or more 2% Longer or more With TDM Without TDM With TDM Without TDM With TDM Without TDM With TDM Without TDM 2. 22. 9. 2.6.8.7. 2.7 2 22.8 27..7 9. 8..2.7 8. 29.8 2.9. 2. 2.8 7. 9.6.7 27..9 6.9 2.8 2.8 2. 8..2. 2. 2.. 2. 9. 9.2 6 29.8. 2..9.8 22. 9. 2. 7 2.. 2.6 6. 7.9 2.8 9. 2. 8.6. 22. 6. 7.2 2.8 9. 9.2 9 2.8. 2.9 8. 6.8 2.2 8. 7.9 2.7. 2.. 27. 6..6 9.. 6. 2. 2.6 9..7.6 2.6 2. 2.9 22.6 8..6.7. 22....7 8..7 6. 6..9.7..7 6.6.7 6.. 8..7..9.9 6.7.7 7.7.7 Total 2.2 67. 2. 9.8 6. 27.7 8.7 9. % increase % 9% 7% 2% Temporal Extent of Congestion Temporal extent of congestion is the time duration during which more than 2% of the roadway sections in a predefined area are congested The time duration considered for this study is one time period ( minute blocks of time); therefore, if 2% of the roadway is congested for a particular time period, that time period is considered as congested 6 8

Period: Temporal Extent of Congestion Temporal Congestion Minutes ( period) Time Period % Longer or more 6% Longer or more % Longer or more 2% Longer or more Scenario A Scenario B Scenario A Scenario B Scenario A Scenario B Scenario A Scenario B 2 6 7 8 9 2 6 7 Total 9. 2. 2. 22. % increase % 6% 67% % 7 Period: Temporal Extent of Congestion Temporal Congestion - Minutes ( period) Time Period % Longer or more 6% Longer or more % Longer or more 2% Longer or more Scenario A Scenario B Scenario A Scenario B Scenario A Scenario B Scenario A Scenario B 2 6 7 8 9 2 6 7 Total 9. 9 6. 2 9 % Increase % 8% 7% All 8 9

Period: Spatial and Temporal Extent of Congestion Southbound I- Northbound I- With TDM Without TDM With TDM Without TDM North Time Period -7 Time Period -7 Time Period -7 Time Period -7 % longer or more Un-congested Condition 6% longer or more % longer or more 2% longer or more 9 Period: Spatial and Temporal Extent of Congestion Southbound I- Northbound I- With TDM Without TDM With TDM Without TDM North Time Period -7 Time Period -7 Time Period -7 Time Period -7 % longer or more Un-congested Condition 6% longer or more % longer or more 2% longer or more 2

Average Speed: Period 7 6 Speed (mph) 2 2 mph 9 mph 6: 6: 6: 6: 7: 7: 7: 7: 8: 8: 8: 8: 9: 9: Time Period Scenario A (with TDM) Scenario B (without TDM) 9: 9: : Average Speed: Period 7 6 Speed (mph) 2 mph : : : : : : : : : : : : 6: 6: 6: 6: 7: Time Period Scenario A (with TDM) Scenario B (without TDM) 2 2

22 VMT Reduction 268.8 9 2 898. 86 2. 6 2. 2 67. 2 - -. - - 6.7 Total 98.9 Total 968. Total 769. Total VMT 6.9 9 2.9 86 2.8 6.7 2 2. 9 86. 77 22.8 6.2 22 276.7 6 9.2 7 2. 6. 2 28. 6 98.8 9 2. 6 2. 2 7.7 7 7. 9 9 2.9 9 7 2. 9 96. 7 8 6.7 262 8.9 9 8. 8 9.7 7 9 7.6 79 7.6 9 9 2.6 7 9. 7.7 79 6.8 9. 6 82. 7 2.6 28 2. 9 8.. 7 2 76.8 287.8 9 2.2 7. 2 29.7 87. 7. 66.6 2.6 6 2. 2.7 97 2 6. 8.2 6. 2 27. 9 27.2 7 6.8 6 2. 2 6. 9 2.2 8 7.6 6 9 7.6 86 7.8 6 9 8.7 8 8.2 8 8 9. 87 8 7. 96 8 6.7 2 9.6 8 7 687. 29 9 92. 96 7. 2. 8 6 7.7 928 2 6. 96 6 2 8.2 778 2 98.7 6 22 8. 88 22. 98 2 2. 88 2 68.8 98 2 2 78. 88 2 7 98 2 2 997. 88 2 7. Added VMT Added Volume Links Added VMT Added Volume Links Added VMT Added Volume Links Added VMT Added Volume Links SOUTHBOUND NORTHBOUND SOUTHBOUND NORTHBOUND Peak Peak I- 2 2 Fuel Savings : Period,, 2, 2, 6: 6: 6: 6: 7: 7: 7: 7: 8: 8: 8: 8: 9: 9: 9: 9: : Time Period Fuel Consumption (Gallons) Scenario A (with TDM) Scenario B (without TDM)

Fuel Savings : Period, Fuel Consumption (Gallons) 2, 2,,, : : : : : : : : : : : : 6: 6: 6: 6: 7: Time Period Scenario A (with TDM) Scenario B (without TDM) Emission Reduction Period Pollutant With TDM Without TDM Added Emissions Percentage Increase HC Emissions (Kg) 9. 7. 6..% CO Emissions (Kg) 6. 2672.7 9.2 9.6% NO Emissions (kg) 68.6 662.9. 8.9% Period Pollutant With TDM Without TDM Added Emissions Percentage Increase HC Emissions (Kg) 6. 87. 2.7.% CO Emissions (Kg) 27.8 7.9. 2.7% NO Emissions (kg) 62.2 69. 67.9.9% 6 2

Summary of Results Performance Measures Delay savings (veh-mins) Spatial Congestion Reduction (%) Temporal Congestion Reduction (%) Average Speed Increase (mph) VMT Reduction (veh-miles) Fuel Savings (gal) HC Emissions Reduction (kg) CO Emissions Reduction (kg) NO Emissions Reduction (kg) Period 2,89.7 lane-miles 6 minutes Up to 9 mph 7,297.,89 6.,9.2. Period 69,86 2.9 lane-miles minutes Up to mph,.6, 2.7,. 67.9 7 Queues on NB I- Peak With TDM Without TDM 8 2

Queues on SB I- Peak With TDM Without TDM 9 Queues on I- Peak With TDM Without TDM 2

Congestion on NB I- - Peak With TDM Without TDM Average Speed < 22 mph 22 2 mph 2 mph mph > mph Congestion on SB I- - Peak With TDM Without TDM Average Speed < 22 mph 22 2 mph 2 mph mph > mph 2 26

Congestion on I- - Peak With TDM Without TDM Average Speed < 22 mph 22 2 mph 2 mph mph > mph Sensitivity Analysis Scenario A Existing TDM Programs % Trip Reduction at 89 Employer Sites Scenario B No TDM Programs No Trip Reduction Scenario C Less Aggressive TDM Program % Trip Reduction at 89 Employer Sites 27

Sensitivity Analysis Period Performance Measures ( Period) Decrease in Delay (vehicle-min) Decrease in Fuel consumption (gal) Decrease in HC Emissions (kg) Decrease in CO Emissions (kg) Scenario A (% trip Reduction) 2,89,89 6.,9.% % 9.% 8.8% Scenario C (% trip Reduction),9 2,67. 78 2.9% 6.8% 6.% 6.2% Decrease in NO Emissions (kg). 8.2% 8..8% Period Performance Measures ( Period) Decrease in Delay (vehicle-min) Decrease in Fuel consumption (gal) Decrease in HC Emissions (kg) Decrease in CO Emissions (kg) Scenario A (% trip Reduction) 69,86, 2.7, 2.% 2.%.6%.% Scenario C (% trip Reduction),276,7.2,6 2.% 8.8% 8.% 7.6% Decrease in NO Emissions (kg) 67.9 9.8% 7. 6.8% Spatial Congestion ( Period) Decrease in lane-miles % longer or more to travel Decrease in lane-miles 6% longer or more to travel Decrease in lane-miles % longer or more to travel Decrease in lane-miles 2% longer or more to travel Sensitivity Analysis Scenario A (% Trip Reduction).7.2.. 8.7% 2.% 28.6% 2.9% Scenario C (% Trip Reduction) 6. 78. 67.6 7..% 7.% 9.% 29.% Spatial Congestion ( Period) Decrease in lane-miles % longer or more to travel Decrease in lane-miles 6% longer or more to travel Decrease in lane-miles % longer or more to travel Decrease in lane-miles 2% longer or more to travel Scenario A (% Trip Reduction) 2.9. 7.6 6..6%.%.%.7% Scenario C (% Trip Reduction).7 92. 89.6 79.6 2.6% 26.% 2.7%.7% 6 28

Conclusions TDM has significant impact on the operation of the transportation network Small reductions in vehicle trips had significant impact on the performance of the transportation network Numbers are as important as methods of communicating them: traffic ops, decisionmakers, planners, TDM and transportation professionals can understand and talk the same language of numbers 7 Some Factors Affecting the Results The number of trips reduced by TDM programs depend on The level of TDM strategies applied at worksites The number of employers and employees participating in these TDM programs Dependable collection techniques for gathering employer and employee data The level of congestion on a roadway corridor 8 29

Transferability To assess potential TDM impacts on a roadway, the following framework is recommended: Estimate the number trips reduced by the TDM programs based on a regional transportation model data Distribute and assign the reduced trips using a regional transportation planning software package Calibrate a microsimulation model for the transportation network study area Communicate VTR in terms of overall traffic region 9 Future Research This research study sets a foundation for future research focus on: Regional, state, and national qualitative processes for assessing the impacts of TDM Cost/benefit analysis of TDM programs Impact of TDM programs on freeways, arterials, and surface streets The effects of combining different TDM strategies with appropriate ITS applications locally and regionally 6