LT4: A comparison of ridership response to incremental BRT upgrades considering land use and network effects
1. 1
A Comparison of Ridership Response
to Incremental BRT Upgrades
Considering Land-Use and Network Effects
Anson Stewart
January 15th, 2013
2. 2
Overview
• Incremental BRT in car-centric cities
• Pre/post analysis
• Direct ridership modeling
• Cross-sectional analysis
3. 3
BRT – Integrated or Incremental?
• “The major components of BRT are planned with the objective of
improving the key attributes of speed, reliability, and identity.
Collectively, as an integrated package, they form a complete
rapid-transit system with significant customer convenience and
transit level of service benefits” (TRB, 2001).
Vs.
• “Incremental development of BRT will often be desirable.
Incremental development may provide an early opportunity to
demonstrate BRT’s potential benefits to riders, decision makers,
and the general public, while still enabling system expansion and
possible upgrading.” (TCRP 90, 2003)
4. 4
Benefits of BRT Elements
• TCRP 90 – Bus Rapid Transit – Case Studies
and Implementation Guidelines
• TCRP 118 – Bus Rapid Transit Practitioner’s
Guide
• Characteristics of BRT for Decision-Making
(2009)
• “Quantifying the Benefits of Bus Rapid Transit
Elements” (2010)
5. 5
Research Objective
BRT Service Performance
Characteristics Indicators
• Priority lanes • Commercial Speed
• Signal priority • Loading
• All-door boarding • Reliability
• Increased stop spacing
External Factors? Ridership and
Productivity
• Boardings
• Boardings per service
hour
• Boardings per veh. mile
• Determine which incremental upgrades to conventional
bus service most effectively improve productivity and
quality in the context of larger more developed cities
6. 6
Overview
• Incremental BRT in car-centric cities
• Pre/post analysis
• Direct ridership modeling
• Cross-sectional analysis
7. 7
Pre/Post Analysis
• Comparing longitudinal changes
• Dependent variable
• Percent increase in ridership
• Independent variables
• Percent of corridor with dedicated lanes
• Percent of intersections with signal priority
• Percent of stops with all-door boarding
• Percent increase in speed
• Percent increase in stop spacing
8. 8
Pre/Post Analysis
Pct Pct All- Pct Stop
Dedicated door Pct Speed Spacing Pct Ridership
City Corridor Lanes Pct TSP Boarding Increase Increase Increase
Miami Busway 1 0 0 0.29 1.79
Orlando Lymmo 1 0 1 0.33
Los Angeles Orange Line 0.93 1 1 0.16 0.51
Boston Washington Street 0.92 0 0 0.09 0.64 0.92
New York M34 SBS 0.67 0.06 1 0.23 0.01 0.31
Eugene EmX 0.65 1 1 0.06 2.52 1.32
Kansas City MAX 0.63 0.89 0 0.25 1.32 0.5
New York M15 SBS 0.62 0.4 1 0.2 0.1 0.12
Cleveland HealthLine 0.62 0 1 0.26 1.24 0.58
Las Vegas North Las Vegas MAX 0.6 0.6 1 0.25 1.69 0.43
New York Bx12 SBS 0.28 0.57 1 0.19 1.40 0.12
Albuquerque Rapid Ride 0.05 0.8 0 0.26 2.48 0.67
Los Angeles Wilshire/Whittier Rapid 0 1 0 0.29 4.60 0.33
Los Angeles Ventura Rapid 0 1 0 0.23 2.23 0.26
Oakland Rapid San Pablo Corridor 0 1 0 0.17 1.42 0.13
San Jose Rapid 522 0 0.44 0 0.2 2.64 0.18
14. 14
Ridership and Productivity
1.00
0.50
% Change in Ridership
%Change in Boardings per Service Hour
0.00
Washington Wilshire/Whittier Ventura Rapid Bx12 SBS M15 SBS
Street Rapid
Boston Los Angeles Los Angeles New York New York
-0.50
15. 15
Overview
• Incremental BRT in car-centric cities
• Pre/post analysis
• Direct ridership modeling
• Cross-sectional analysis
16. 16
Stop-level Sketch Planning
• TCRP 16
• Lane et al. (2006). “Sketch Models to Forecast Commuter
and Light Rail Ridership”
• Stop-level ridership model for 17 US regions
18. 18
Direct Ridership Modeling
• Extending stop-level DRM to corridor-level analysis
• Revise binary consideration of right-of-way
• Scale branches based on frequency
• Consider network-length buffers (“reach” metric)
19. 19
Overview
• Incremental BRT in car-centric cities
• Pre/post analysis
• Direct ridership modeling
• Cross-sectional analysis
20. 20
Cross-Sectional Analysis
• Dependent Variables
• Boardings per service hour
• Independent Variables
• Percentage of corridor with priority lanes
• Percentage of intersections with signal priority
• Percentage of stops with all-door boarding
• Stop spacing
• Population density along corridor
• Auto ownership along corridor Land Use, from GIS
• Employment density along corridor
Network, from alighting estimation
• Transfers from other services/modes
or GTFS Transfer Potential
21. 21
Land Use
Average Weekday Weekday Boardings/ Weekday Boardings/ Weekday Boardings/ Land Area Within Population Density
City Data Year Route Corridor
Boardings Service Hour Service Mile Route Mile 0.5 miles of Stop Within 0.5 Miles of Stop
NYC 2011 M15 SBS1st/2nd Ave 33,467 77.9 8.0 86,456
NYC 2009 Bx12 SBSFordham 30,490 94.5 7.4 42,903
NYC 2011 B41 Flatbush 33,948 52.0 9.6 40,628
NYC 2011 Q12 Sanford Ave/Nort 10,571 47.9 5.9 27,186
LOS 2011 754 Vermont 21,275 93.4 14.0 23,244
LOS 2011 204 Vermont 28,032 97.9 14.0 23,244
BOS 2009, 2011 SL4/5 Washington St. 15,086 88.7 12.7 3142.9 3.1 22,241
LOS 2011 720 Wilshire 40,106 60.6 27.4 17,053
LOS 2011 18 Wilshire 24,844 76.2 27.4 17,053
LOS 2011 20 Wilshire 16,630 55.1 27.4 17,053
VAN 2010 B-99 Broadway 57,050 193.8 9.8 14,705
LOS 2011 910 Silver Line 10,423 47.9 11.2 9,779
VAN 2010 99 Broadway 57,050 248.3 14.1 3565.6 7.2 9,601
LOS 2011 901 Orange Line 24,867 81.6 10.7 8,837
MSP 2010, 2009 21 Lake 12,886 58.8 5.9 1451.8 12.9 8,020
MSP 2010, 2009 5 Chicago 16,325 57.6 4.7 1189.0 19.1 6,899
MSP 2010, 2009 10 Central 7,330 43.9 3.4 632.8 16.9 5,020
MSP 2010, 2009 84 Snelling 3,583 38.2 2.4 341.1 12.2 4,934
BOS 2009, 2011 SL1/2 Waterfront 14,940 80.5 10.7 2490.0 3.0 4,432