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Using Publicly Available
Datasets to Evaluate the
Intersection between Bicycling
and Commercial Vehicles
Alison Conway
Assistant Professor of Civil Engineering
D-STOP Symposium Austin, TX April 1, 2016
Freight in New York City
• Population
• 8.5 million in the Five Boroughs
• 20+ million in metro areas
• World city with a diverse economy
• Tremendous local demand
• Critical foreign trade gateways
• Designated truck routes
Motivation Methods Results Future Research
Existing Challenges to Urban Goods
Movement in NYC
• Widespread traffic congestion (Lomax, Schrank, and Eisele, 2015)
• High parking fines (Holguin-Veras, 2011)
• Expensive tolls (King, Gordon, and Peters, 2014)
• Inadequate available parking for CVs (Jaller, Holguin-Veras, and Hodge, 2013)
• Parking/loading dock requirements not updated since 1950s (Morris, 2009)
Motivation Methods Results Future Research
Recent Changes
• Urban redevelopment
 mixed land uses
• E-Commerce boom
 new freight demand in residential areas
• Implementation of bicycle, pedestrian, and transit infrastructure
 shrinking urban street capacity
 growing volumes of multimodal travelers
Motivation Methods Results Future Research
Project Goals
• To provide basic quantitative evidence of truck route impacts and of
CV-bicycle interactions on the multimodal network through
visualization and basic statistical analysis of NYC open datasets
• To identify future research needs
Motivation Methods Results Future Research
NYC Open Datasets
• Collision data includes only incidents
that warrant an NYPD report
• Parking violations are issued only in
locations where enforcement is
performed
NYC DOT Local
Truck Route
Network
NYC DOT
Bicycle
Network
NYPD Collision
Data
NYC DOF
Parking
Violations
NYC DCP Lion
Street
Centerlines
Motivation Methods Results Future Research
NYC DOT Local
Truck Route
Network
NYC DOT
Bicycle
Network
NYPD Collision
Data
NYC DOF
Parking
Violations
NYC DCP Lion
Street
Centerlines
1. Extent of network overlap
2. Lane types on overlapping network
3. Collision locations by infrastructure type
4. Collision locations vs. freight demand factors
5. Critical violation blocks
Economic
Census LEHD
Data
US Census
Population
Data
6. Parking choices
Field
Observations
Motivation Methods Results Future Research
Networks and Overlap
• 794 mi local truck routes
• 604 mi bicycle routes
• Overlapping segments
• 89 miles
• About 2/3 installed since 2000
Motivation Future ResearchMethods Results
Lane
Types
Motivation Future ResearchMethods Results
0
10
20
30
40
50
60
70
80
90
100
On-Street Bike Lanes Truck Route Overlap Truck Route Overlap
Installed Since 2000
PercentofLanes
Signed Route
Sharrows
Standard
Curbside
Bike-Friendly Parking
Protected Path
Motivation Future ResearchMethods Results
Collision Locations
Bicycle Collisions per Lane-Mile
Network Truck Routes
All CV All CV
12.0 0.34 32.4 1.11
0
10
20
30
40
50
60
70
80
90
100
Lane Mileage All Collisions CV Collisions Lane Mileage All Collisions CV Collisions
Signed Route
Sharrows
Standard
Curbside
Bike-Friendly Parking
Protected Path
Collision
Locations
by Lane
Type
Network Truck Routes
Motivation Methods Results Future Research
Demand Factors
Large CV Small CV
Yes No Yes No
Observations 50 4308 73 4285
Median p-value Median p-value
Population Density 29824 17194 0.123 38350 17041 0.001 **
Employment Density 51023 59104 0.360 71079 59035 0.097
ShareofEmploymentin
Sector
Construction 1.37 1.49 0.940 1.83 1.49 0.428
Manufacturing 1.04 0.84 0.172 1.44 0.83 0.052 *
Wholesale 3.28 1.88 0.014 ** 2.60 1.91 0.064
Retail 6.87 9.60 0.072 * 8.89 9.60 0.191
Transp. &
Warehousing
0.78 0.44 0.040 ** 0.77 0.44 0.039 **
Service 60.91 58.32 0.952 61.26 58.32 0.853
Entertainment 12.19 14.34 0.260 15.68 14.29 0.720
Motivation Future ResearchMethods Results
Parking Violations
• 1 million + total parking
violations over 3 months
• 4,452 CV bicycle lane violations
• 4,271 on known on-street lane
types
• 20+ violations on 23 blocks
• Standard lanes
• Four boroughs
• Varying land uses
Motivation Future ResearchMethods Results
Field Observation Locations
W 77th StEast Broadway
Image source: Google Maps
Grand Concourse
Motivation Future ResearchMethods Results
Motivation Methods Results Future Research
0
10
20
30
40
50
60
70
80
90
100
Available at
Location
Available On Block Used at Location Used on Block
Food and Beverage (43)
Parcel (58)
Moving Truck (6)
Service Vehicle (35)
Curbside Legal Parking by Sector
0
5
10
15
20
25
30
35
40
45
50
0-5 5-10 10-15 15-20 20-25 25-30 30+
Grocery, Food, & Beverage
Major Parcel
Other Parcel
Service
Moving Truck
PercentofCommercialVehicles
Parking Duration (min)
Parking
Durations
Motivation Methods Results Future Research
Key Observations
• Significant bicycle lane mileage installed on truck route network
• Growing share of protected lanes and bicycle-friendly parking
• Bicycle collisions disproportionately concentrated:
• On truck routes
• In protected lanes
• Parking availability and choices vary considerably
• With curb regulations
• By sector
Motivation Methods Results Future Research
Future Research
• Measure the short and long term implications of reduced capacities for
CV operations and for the surrounding area
• Examine detailed accident causality on specific types of bicycle
infrastructure
• Evaluate demand and operator-specific curb management strategies
Motivation Methods Results Future Research
Acknowledgements
• Student Researchers
• Lisa Chauvet
• Medwin Chiu
• Niloofar Gharamani
• Victor Leal-Tavares
• Nathan Tavernier
• Xue Bing Yeap
• Volvo Research and Education Foundations
• Student Fellowship Programs
• Brazilian Scientific Mobility Program
• CCNY’s NSF-funded programs
• Louis Stokes Alliance for Minority
Participation (LSAMP)
• STEM Talent Expansion Program (STEP)
• FHWA Eisenhower Fellowship Program
• French Ministry of Ecology, Sustainable
Development and Energy

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Using Publicly Available Datasets to Evaluate the Intersection between Bicycling and Commercial Vehicles

  • 1. Using Publicly Available Datasets to Evaluate the Intersection between Bicycling and Commercial Vehicles Alison Conway Assistant Professor of Civil Engineering D-STOP Symposium Austin, TX April 1, 2016
  • 2. Freight in New York City • Population • 8.5 million in the Five Boroughs • 20+ million in metro areas • World city with a diverse economy • Tremendous local demand • Critical foreign trade gateways • Designated truck routes Motivation Methods Results Future Research
  • 3. Existing Challenges to Urban Goods Movement in NYC • Widespread traffic congestion (Lomax, Schrank, and Eisele, 2015) • High parking fines (Holguin-Veras, 2011) • Expensive tolls (King, Gordon, and Peters, 2014) • Inadequate available parking for CVs (Jaller, Holguin-Veras, and Hodge, 2013) • Parking/loading dock requirements not updated since 1950s (Morris, 2009) Motivation Methods Results Future Research
  • 4. Recent Changes • Urban redevelopment  mixed land uses • E-Commerce boom  new freight demand in residential areas • Implementation of bicycle, pedestrian, and transit infrastructure  shrinking urban street capacity  growing volumes of multimodal travelers Motivation Methods Results Future Research
  • 5. Project Goals • To provide basic quantitative evidence of truck route impacts and of CV-bicycle interactions on the multimodal network through visualization and basic statistical analysis of NYC open datasets • To identify future research needs Motivation Methods Results Future Research
  • 6. NYC Open Datasets • Collision data includes only incidents that warrant an NYPD report • Parking violations are issued only in locations where enforcement is performed NYC DOT Local Truck Route Network NYC DOT Bicycle Network NYPD Collision Data NYC DOF Parking Violations NYC DCP Lion Street Centerlines Motivation Methods Results Future Research
  • 7. NYC DOT Local Truck Route Network NYC DOT Bicycle Network NYPD Collision Data NYC DOF Parking Violations NYC DCP Lion Street Centerlines 1. Extent of network overlap 2. Lane types on overlapping network 3. Collision locations by infrastructure type 4. Collision locations vs. freight demand factors 5. Critical violation blocks Economic Census LEHD Data US Census Population Data 6. Parking choices Field Observations Motivation Methods Results Future Research
  • 8. Networks and Overlap • 794 mi local truck routes • 604 mi bicycle routes • Overlapping segments • 89 miles • About 2/3 installed since 2000 Motivation Future ResearchMethods Results
  • 9. Lane Types Motivation Future ResearchMethods Results 0 10 20 30 40 50 60 70 80 90 100 On-Street Bike Lanes Truck Route Overlap Truck Route Overlap Installed Since 2000 PercentofLanes Signed Route Sharrows Standard Curbside Bike-Friendly Parking Protected Path
  • 10. Motivation Future ResearchMethods Results Collision Locations Bicycle Collisions per Lane-Mile Network Truck Routes All CV All CV 12.0 0.34 32.4 1.11
  • 11. 0 10 20 30 40 50 60 70 80 90 100 Lane Mileage All Collisions CV Collisions Lane Mileage All Collisions CV Collisions Signed Route Sharrows Standard Curbside Bike-Friendly Parking Protected Path Collision Locations by Lane Type Network Truck Routes Motivation Methods Results Future Research
  • 12. Demand Factors Large CV Small CV Yes No Yes No Observations 50 4308 73 4285 Median p-value Median p-value Population Density 29824 17194 0.123 38350 17041 0.001 ** Employment Density 51023 59104 0.360 71079 59035 0.097 ShareofEmploymentin Sector Construction 1.37 1.49 0.940 1.83 1.49 0.428 Manufacturing 1.04 0.84 0.172 1.44 0.83 0.052 * Wholesale 3.28 1.88 0.014 ** 2.60 1.91 0.064 Retail 6.87 9.60 0.072 * 8.89 9.60 0.191 Transp. & Warehousing 0.78 0.44 0.040 ** 0.77 0.44 0.039 ** Service 60.91 58.32 0.952 61.26 58.32 0.853 Entertainment 12.19 14.34 0.260 15.68 14.29 0.720 Motivation Future ResearchMethods Results
  • 13. Parking Violations • 1 million + total parking violations over 3 months • 4,452 CV bicycle lane violations • 4,271 on known on-street lane types • 20+ violations on 23 blocks • Standard lanes • Four boroughs • Varying land uses Motivation Future ResearchMethods Results
  • 14. Field Observation Locations W 77th StEast Broadway Image source: Google Maps Grand Concourse Motivation Future ResearchMethods Results
  • 15.
  • 16. Motivation Methods Results Future Research 0 10 20 30 40 50 60 70 80 90 100 Available at Location Available On Block Used at Location Used on Block Food and Beverage (43) Parcel (58) Moving Truck (6) Service Vehicle (35) Curbside Legal Parking by Sector
  • 17. 0 5 10 15 20 25 30 35 40 45 50 0-5 5-10 10-15 15-20 20-25 25-30 30+ Grocery, Food, & Beverage Major Parcel Other Parcel Service Moving Truck PercentofCommercialVehicles Parking Duration (min) Parking Durations Motivation Methods Results Future Research
  • 18. Key Observations • Significant bicycle lane mileage installed on truck route network • Growing share of protected lanes and bicycle-friendly parking • Bicycle collisions disproportionately concentrated: • On truck routes • In protected lanes • Parking availability and choices vary considerably • With curb regulations • By sector Motivation Methods Results Future Research
  • 19. Future Research • Measure the short and long term implications of reduced capacities for CV operations and for the surrounding area • Examine detailed accident causality on specific types of bicycle infrastructure • Evaluate demand and operator-specific curb management strategies Motivation Methods Results Future Research
  • 20. Acknowledgements • Student Researchers • Lisa Chauvet • Medwin Chiu • Niloofar Gharamani • Victor Leal-Tavares • Nathan Tavernier • Xue Bing Yeap • Volvo Research and Education Foundations • Student Fellowship Programs • Brazilian Scientific Mobility Program • CCNY’s NSF-funded programs • Louis Stokes Alliance for Minority Participation (LSAMP) • STEM Talent Expansion Program (STEP) • FHWA Eisenhower Fellowship Program • French Ministry of Ecology, Sustainable Development and Energy

Editor's Notes

  1. Concentrated in Downtown/Midtown Manhattan, Downtown Brooklyn, and along waterfronts in Brooklyn and Queens
  2. Trucks traveling where they are supposed to
  3. Collisions involving small cv vs. those not
  4. Simulation modeling of the urban street network Evaluation of GPS spot speed data on routes with and without infrastructure