Traffic Engineering for Optimal BRT and TSP Success
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1 Traffic Engineering for Optimal BRT and TSP Success October 31, 2018
2 Agenda Introduction Challenges Solution Process Traffic Engineering Decisions Case Study Results
3 About Presenter PI of 1981 FHWA research on TSP 21 TSP projects since 1997 Traffic engineering consultant for NYCDOT city-wide TSP since 2011 Mark Yedlin GPI: Full service Engineering Firm Staff of 1500 in over 40 US offices 6 offices in Pennsylvania
4 What is TSP? Real Time signal adjustments to expedite buses: Extend Green Early Green Advance Green (Queue jump)
5 Why TSP? Reduce Travel Time Reduce Variability Reduce Operating Costs Maintain Schedule Increase Ridership Reduce Congestion Improve Mobility
6 The devil is in the details Can you see it? Now?
7 We work in the realm of the devil Lots of details!! Many pitfalls Political Institutional Technical Many voices and choices Decisions influence success
8 Keys to Success Start small think big! Find a champion! Bring agencies together Communicate x 3 Know what s needed Understand constraints Address bottlenecks Good traffic engineering!!
9 Start Small Think BIG Pick pilot to succeed Opportunities for improvement Reasonable cross street volumes Keep eye on the future Anticipate full roll-out Plan system wide policies, hardware
10 Find a Champion! Lead process Take responsibility Shephard agencies to consensus Keep pushing!!
11 Bring Agencies Together Department of Transportation Transit Agency Consultants Multiple staff in each Recognize different: Priorities Agendas Responsibilities Cost/Benefit realities
12 Communicate, Communicate, Communicate! Throughout process Objectives Policies Design Implementation Acceptance testing Ongoing operations Even within same agency!
13 What are the constraints? Cross street traffic Pedestrians, seniors Capacity Coordination Bus stops Other corridor traffic
14 How should it work? Primary objectives? Conditional, Unconditional TSP? Coordination? Transition? Competing calls? How soon to accept next call? Door switches?
15 What do we have to Decide? What timings/offsets? Which intersections? What phases? How much time? When to act? Which call? Queue jumps? What are effects? Is it worth it? Simulation invaluable! Answers vary by time of day Also vary by direction
16 Why simulate? Resolve the decisions Determine savings for buses Determine effects on others Examine tradeoffs Optimize system Justify funding!!!
17 Public Transit in NYC 5.7 million subway, 2.4 million bus riders per day 5,700 buses on 2,800 miles of routes Public transit system operated by MTA NYC Transit Streets and 13,000 signalized intersections operated by NYCDOT
18 Problem: Bus Speeds in NYC Source: Sources: National Transit Database
19 Case Study: TSP in NYC Wall Street Financial District 2 nd highest ridership in city Intermodal route Lots of pedestrians, bicycles Unloading trucks Congested Coordination Canyon for GPS signal Success unlikely!
20
21 Comparing Bus Operations With and Without TSP Without TSP Intersections Crossed: Next: Allen Pike Pearl Madison State Water / / E. Henry Madison / Stanton Rivington Delancey Broome Grand Hester Canal Division Peter Wagner St. Dover Peck Beekman Fulton John Maiden Pine Wall Gouverneur Old 55 Coenties Whitehall Fletcher Broadway / St. Market Catherine Oliver James Water Slip Minuit James Slip Active TSP Intersections Crossed: Next: Allen Pike Madison Pearl Water State / / E. Henry Madison / Stanton Rivington Delancey Broome Grand Hester Canal Division Peter St. Wagner Dover Peck Beekman Fulton John Fletcher Maiden Pine Wall Gouverneur Old 55 Coenties Whitehall Broadway / James Market Catherine Oliver St. Water Slip Minuit James Slip Early Extended TSP not return to green available green Time saved to last intersection: 00:00 00:20 00:23 00:35 00:36 01:02 01:13 02:01 01:56 02:02 02:53 02:49 02:50 03:53 03:26 01:57 02:05 02:59 03:01 03:02 04:04 03:23 03:14 03:17
22 Results: Win-Win! Period Travel Time Savings Min/Bus trip % NB SB NB SB AM Peak Mid-day PM Peak M15 SBS Bus Travel Time Deviations, SB/WB Direction, AM Period Lowered Bus Travel Time Up to 18.4% Reduced Delay for Other Traffic Side streets improved too! Side street delay: 3.2 to 10.3% Peak hour delay for corridor: 12.4 to 15.1% Peak hour delay for all traffic: 8.3 to 11.9% Travel Time (mins) Existing Active TSP Lowered Variability Improved reliability
23 840 intersections 92 miles
24 Keys to Success Find a champion! Bring agencies together Communicate!!! Know what s needed Understand constraints Address bottlenecks Simulation and good traffic engineering!!
25 Questions? Mark Yedlin Director of Simulation Modeling Services Greenman-Pedersen, Inc. (GPI) Thank you!
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