SlideShare une entreprise Scribd logo
1  sur  29
Télécharger pour lire hors ligne
1




A Comparison of Ridership Response
to Incremental BRT Upgrades
Considering Land-Use and Network Effects

Anson Stewart

January 15th, 2013
2




Overview
• Incremental BRT in car-centric cities
• Pre/post analysis
• Direct ridership modeling
• Cross-sectional analysis
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




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




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




Overview
• Incremental BRT in car-centric cities
• Pre/post analysis
• Direct ridership modeling
• Cross-sectional analysis
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




   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
9


Percent Ridership Increase vs. Percent Dedicated Lanes

                                                 Avg. 89% Increase




                          Avg. 54% Increase


  Avg. 31% Increase




 Coefficients:
                     Estimate Std. Error t value Pr(>|t|)
 (Intercept)           0.2290     0.1729   1.325   0.2064
 Pct.Dedicated.Lanes   0.6067     0.2779   2.183   0.0466 *
 ---
 Adjusted R-squared: 0.2006
10


Percent Speed Increase vs. Percent Dedicated Lanes




R2 = -0.02
11



Percent Speed Increase vs. Percent Stop Spacing Increase




R2 = -0.03
12




Percent Ridership Increase vs. Percent Speed Increase
13




Percent Ridership Gain

Coefficients:
                     Estimate Std. Error t value Pr(>|t|)
(Intercept)           0.21682    0.31495   0.688 0.50855
Pct.Dedicated.Lanes   0.84899    0.25843   3.285 0.00945    **
Speed.Increase       -2.23115    1.01773 -2.192 0.05604     .
Stop.Spacing.Increase 0.21319    0.06806   3.132 0.01208    *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘   ’ 1

Adjusted R-squared: 0.618
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




Overview
• Incremental BRT in car-centric cities
• Pre/post analysis
• Direct ridership modeling
• Cross-sectional analysis
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
17




Direct Ridership Modeling
• Cervero (2010)
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




Overview
• Incremental BRT in car-centric cities
• Pre/post analysis
• Direct ridership modeling
• Cross-sectional analysis
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




       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
22




Network Effects
23




Network Effects
Hadas (2012): Stop Transfer Potential at the network level




                                               𝑇 → 𝑋𝑋 𝐴




                                               𝑇 → 0.5𝑋𝑋 𝐴
24




Network Effects
Scale transfer opportunities according to proportion of corridor trips
serving a station
25




Transfer Potential - Boston
26




Transfer Potential – Los Angeles
27




Land Use - Circular Buffer
28




Land Use - Street Network Buffer
29




A Comparison of Ridership Response
to Incremental BRT Upgrades
Considering Land-Use and Network Effects

Anson Stewart

January 15th, 2013

Contenu connexe

Plus de BRTCoE

MaaS Trial in Sydney
MaaS Trial in SydneyMaaS Trial in Sydney
MaaS Trial in SydneyBRTCoE
 
Full cost reliability by Juan Carlos Muñoz
Full cost reliability by Juan Carlos MuñozFull cost reliability by Juan Carlos Muñoz
Full cost reliability by Juan Carlos MuñozBRTCoE
 
Congreso nacional chileno 2019 DITL
Congreso nacional chileno 2019 DITLCongreso nacional chileno 2019 DITL
Congreso nacional chileno 2019 DITLBRTCoE
 
Gabriel Oliveira - BRT in Brazil: state of the practice as from the BRT Stand...
Gabriel Oliveira - BRT in Brazil: state of the practice as from the BRT Stand...Gabriel Oliveira - BRT in Brazil: state of the practice as from the BRT Stand...
Gabriel Oliveira - BRT in Brazil: state of the practice as from the BRT Stand...BRTCoE
 
Heather Allen - Why do we need to consider how women move in urban transport ...
Heather Allen - Why do we need to consider how women move in urban transport ...Heather Allen - Why do we need to consider how women move in urban transport ...
Heather Allen - Why do we need to consider how women move in urban transport ...BRTCoE
 
Workshop Innovation in Africa - Manifesto for BRT Lite
Workshop Innovation in Africa - Manifesto for BRT LiteWorkshop Innovation in Africa - Manifesto for BRT Lite
Workshop Innovation in Africa - Manifesto for BRT LiteBRTCoE
 
Workshop Innovation in Africa - BRT Lessons from Nigeria by Dr. Dayo Mobereola
Workshop Innovation in Africa - BRT Lessons from Nigeria by Dr. Dayo MobereolaWorkshop Innovation in Africa - BRT Lessons from Nigeria by Dr. Dayo Mobereola
Workshop Innovation in Africa - BRT Lessons from Nigeria by Dr. Dayo MobereolaBRTCoE
 
Workshop Innovation in Africa - Context, challenges & opportunities for urban...
Workshop Innovation in Africa - Context, challenges & opportunities for urban...Workshop Innovation in Africa - Context, challenges & opportunities for urban...
Workshop Innovation in Africa - Context, challenges & opportunities for urban...BRTCoE
 
Workshop Innovation in Africa - Mobilize
Workshop Innovation in Africa - MobilizeWorkshop Innovation in Africa - Mobilize
Workshop Innovation in Africa - MobilizeBRTCoE
 
Workshop Innovation in Africa - Day one of operations by Cristina Albuquerque
Workshop Innovation in Africa - Day one of operations by Cristina AlbuquerqueWorkshop Innovation in Africa - Day one of operations by Cristina Albuquerque
Workshop Innovation in Africa - Day one of operations by Cristina AlbuquerqueBRTCoE
 
Workshop Innovation in Africa - BRT Lessons from Dar es Salaam by Ronald Lwak...
Workshop Innovation in Africa - BRT Lessons from Dar es Salaam by Ronald Lwak...Workshop Innovation in Africa - BRT Lessons from Dar es Salaam by Ronald Lwak...
Workshop Innovation in Africa - BRT Lessons from Dar es Salaam by Ronald Lwak...BRTCoE
 
Workshop Innovation in Africa - BRT, Minibus System and Innovation in African...
Workshop Innovation in Africa - BRT, Minibus System and Innovation in African...Workshop Innovation in Africa - BRT, Minibus System and Innovation in African...
Workshop Innovation in Africa - BRT, Minibus System and Innovation in African...BRTCoE
 
Workshop Innovation in Africa - BRT in South Africa by Christo Venter
Workshop Innovation in Africa - BRT in South Africa by Christo VenterWorkshop Innovation in Africa - BRT in South Africa by Christo Venter
Workshop Innovation in Africa - BRT in South Africa by Christo VenterBRTCoE
 
Workshop Innovation in Africa - BRT+ Centre of Excellence Presentation
Workshop Innovation in Africa - BRT+ Centre of Excellence PresentationWorkshop Innovation in Africa - BRT+ Centre of Excellence Presentation
Workshop Innovation in Africa - BRT+ Centre of Excellence PresentationBRTCoE
 
Camila Balbontin - Do preferences for BRT and LRT change as a voter, citizen,...
Camila Balbontin - Do preferences for BRT and LRT change as a voter, citizen,...Camila Balbontin - Do preferences for BRT and LRT change as a voter, citizen,...
Camila Balbontin - Do preferences for BRT and LRT change as a voter, citizen,...BRTCoE
 
Cristian Navas - Testing collaborative accessibility-based engagement tools: ...
Cristian Navas - Testing collaborative accessibility-based engagement tools: ...Cristian Navas - Testing collaborative accessibility-based engagement tools: ...
Cristian Navas - Testing collaborative accessibility-based engagement tools: ...BRTCoE
 
Juan Carlos Muñoz - Connected and automated buses. An opportunity to bring re...
Juan Carlos Muñoz - Connected and automated buses. An opportunity to bring re...Juan Carlos Muñoz - Connected and automated buses. An opportunity to bring re...
Juan Carlos Muñoz - Connected and automated buses. An opportunity to bring re...BRTCoE
 
Rethinking the Next Generation of BRT in China
Rethinking the Next Generation of BRT in ChinaRethinking the Next Generation of BRT in China
Rethinking the Next Generation of BRT in ChinaBRTCoE
 
Habitat III can help accelerate action on sustainable urban transport
Habitat III can help accelerate action on sustainable urban transportHabitat III can help accelerate action on sustainable urban transport
Habitat III can help accelerate action on sustainable urban transportBRTCoE
 
2016 05-30 may session ulises navarro
2016 05-30 may session ulises navarro2016 05-30 may session ulises navarro
2016 05-30 may session ulises navarroBRTCoE
 

Plus de BRTCoE (20)

MaaS Trial in Sydney
MaaS Trial in SydneyMaaS Trial in Sydney
MaaS Trial in Sydney
 
Full cost reliability by Juan Carlos Muñoz
Full cost reliability by Juan Carlos MuñozFull cost reliability by Juan Carlos Muñoz
Full cost reliability by Juan Carlos Muñoz
 
Congreso nacional chileno 2019 DITL
Congreso nacional chileno 2019 DITLCongreso nacional chileno 2019 DITL
Congreso nacional chileno 2019 DITL
 
Gabriel Oliveira - BRT in Brazil: state of the practice as from the BRT Stand...
Gabriel Oliveira - BRT in Brazil: state of the practice as from the BRT Stand...Gabriel Oliveira - BRT in Brazil: state of the practice as from the BRT Stand...
Gabriel Oliveira - BRT in Brazil: state of the practice as from the BRT Stand...
 
Heather Allen - Why do we need to consider how women move in urban transport ...
Heather Allen - Why do we need to consider how women move in urban transport ...Heather Allen - Why do we need to consider how women move in urban transport ...
Heather Allen - Why do we need to consider how women move in urban transport ...
 
Workshop Innovation in Africa - Manifesto for BRT Lite
Workshop Innovation in Africa - Manifesto for BRT LiteWorkshop Innovation in Africa - Manifesto for BRT Lite
Workshop Innovation in Africa - Manifesto for BRT Lite
 
Workshop Innovation in Africa - BRT Lessons from Nigeria by Dr. Dayo Mobereola
Workshop Innovation in Africa - BRT Lessons from Nigeria by Dr. Dayo MobereolaWorkshop Innovation in Africa - BRT Lessons from Nigeria by Dr. Dayo Mobereola
Workshop Innovation in Africa - BRT Lessons from Nigeria by Dr. Dayo Mobereola
 
Workshop Innovation in Africa - Context, challenges & opportunities for urban...
Workshop Innovation in Africa - Context, challenges & opportunities for urban...Workshop Innovation in Africa - Context, challenges & opportunities for urban...
Workshop Innovation in Africa - Context, challenges & opportunities for urban...
 
Workshop Innovation in Africa - Mobilize
Workshop Innovation in Africa - MobilizeWorkshop Innovation in Africa - Mobilize
Workshop Innovation in Africa - Mobilize
 
Workshop Innovation in Africa - Day one of operations by Cristina Albuquerque
Workshop Innovation in Africa - Day one of operations by Cristina AlbuquerqueWorkshop Innovation in Africa - Day one of operations by Cristina Albuquerque
Workshop Innovation in Africa - Day one of operations by Cristina Albuquerque
 
Workshop Innovation in Africa - BRT Lessons from Dar es Salaam by Ronald Lwak...
Workshop Innovation in Africa - BRT Lessons from Dar es Salaam by Ronald Lwak...Workshop Innovation in Africa - BRT Lessons from Dar es Salaam by Ronald Lwak...
Workshop Innovation in Africa - BRT Lessons from Dar es Salaam by Ronald Lwak...
 
Workshop Innovation in Africa - BRT, Minibus System and Innovation in African...
Workshop Innovation in Africa - BRT, Minibus System and Innovation in African...Workshop Innovation in Africa - BRT, Minibus System and Innovation in African...
Workshop Innovation in Africa - BRT, Minibus System and Innovation in African...
 
Workshop Innovation in Africa - BRT in South Africa by Christo Venter
Workshop Innovation in Africa - BRT in South Africa by Christo VenterWorkshop Innovation in Africa - BRT in South Africa by Christo Venter
Workshop Innovation in Africa - BRT in South Africa by Christo Venter
 
Workshop Innovation in Africa - BRT+ Centre of Excellence Presentation
Workshop Innovation in Africa - BRT+ Centre of Excellence PresentationWorkshop Innovation in Africa - BRT+ Centre of Excellence Presentation
Workshop Innovation in Africa - BRT+ Centre of Excellence Presentation
 
Camila Balbontin - Do preferences for BRT and LRT change as a voter, citizen,...
Camila Balbontin - Do preferences for BRT and LRT change as a voter, citizen,...Camila Balbontin - Do preferences for BRT and LRT change as a voter, citizen,...
Camila Balbontin - Do preferences for BRT and LRT change as a voter, citizen,...
 
Cristian Navas - Testing collaborative accessibility-based engagement tools: ...
Cristian Navas - Testing collaborative accessibility-based engagement tools: ...Cristian Navas - Testing collaborative accessibility-based engagement tools: ...
Cristian Navas - Testing collaborative accessibility-based engagement tools: ...
 
Juan Carlos Muñoz - Connected and automated buses. An opportunity to bring re...
Juan Carlos Muñoz - Connected and automated buses. An opportunity to bring re...Juan Carlos Muñoz - Connected and automated buses. An opportunity to bring re...
Juan Carlos Muñoz - Connected and automated buses. An opportunity to bring re...
 
Rethinking the Next Generation of BRT in China
Rethinking the Next Generation of BRT in ChinaRethinking the Next Generation of BRT in China
Rethinking the Next Generation of BRT in China
 
Habitat III can help accelerate action on sustainable urban transport
Habitat III can help accelerate action on sustainable urban transportHabitat III can help accelerate action on sustainable urban transport
Habitat III can help accelerate action on sustainable urban transport
 
2016 05-30 may session ulises navarro
2016 05-30 may session ulises navarro2016 05-30 may session ulises navarro
2016 05-30 may session ulises navarro
 

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
  • 9. 9 Percent Ridership Increase vs. Percent Dedicated Lanes Avg. 89% Increase Avg. 54% Increase Avg. 31% Increase Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.2290 0.1729 1.325 0.2064 Pct.Dedicated.Lanes 0.6067 0.2779 2.183 0.0466 * --- Adjusted R-squared: 0.2006
  • 10. 10 Percent Speed Increase vs. Percent Dedicated Lanes R2 = -0.02
  • 11. 11 Percent Speed Increase vs. Percent Stop Spacing Increase R2 = -0.03
  • 12. 12 Percent Ridership Increase vs. Percent Speed Increase
  • 13. 13 Percent Ridership Gain Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.21682 0.31495 0.688 0.50855 Pct.Dedicated.Lanes 0.84899 0.25843 3.285 0.00945 ** Speed.Increase -2.23115 1.01773 -2.192 0.05604 . Stop.Spacing.Increase 0.21319 0.06806 3.132 0.01208 * --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Adjusted R-squared: 0.618
  • 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
  • 23. 23 Network Effects Hadas (2012): Stop Transfer Potential at the network level 𝑇 → 𝑋𝑋 𝐴 𝑇 → 0.5𝑋𝑋 𝐴
  • 24. 24 Network Effects Scale transfer opportunities according to proportion of corridor trips serving a station
  • 27. 27 Land Use - Circular Buffer
  • 28. 28 Land Use - Street Network Buffer
  • 29. 29 A Comparison of Ridership Response to Incremental BRT Upgrades Considering Land-Use and Network Effects Anson Stewart January 15th, 2013