CYCLIST BEHAVIOR AT DISCONTINUITIES IN THE CYCLING NETWORK Matin S. - - PowerPoint PPT Presentation

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ICTCT, Lund 2016 CYCLIST BEHAVIOR AT DISCONTINUITIES IN THE CYCLING NETWORK Matin S. Nabavi Niaki , cole Polytechnique de Montral Nicolas Saunier , cole Polytechnique de Montral Luis Miranda Moreno , McGill University ICTCT, Lund 2016

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CYCLIST BEHAVIOR AT DISCONTINUITIES IN THE CYCLING NETWORK

Matin S. Nabavi Niaki, École Polytechnique de Montréal Nicolas Saunier, École Polytechnique de Montréal Luis Miranda Moreno, McGill University ICTCT, Lund 2016

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Introduction

  • Transportation engineers and planners are focusing on improving:
  • cycling mode share
  • cyclist safety
  • The World Health Organization reported that about 1.25 million people die

each year as a result of road traffic crashes (1)

  • half of which are vulnerable road users
  • In Canada, 3.2 % of all traffic fatalities involved cyclists (2)
  • 1.3 % of Canadian commuters are cycling to work (2)

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  • To improve safety and cyclist mode share, cyclist behavior must be

studied throughout the cycling network

  • Many studies have identified some of the reasons for low cycling mode

share to be the low objective and perceived safety of cyclists which could be due to the discontinuities in the cycling network (6, 7, 8, 9, 10)

  • Therefore the road network must be designed so it can accommodate

different road users safely in different conditions and situations

  • by better understanding the risks and factors related to discontinuities

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Introduction

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  • Cycling network provides connectivity between origin and destinations by

means of cycling facilities:

  • separate cycling facility
  • bike lane
  • shared/designated roadway
  • off road
  • etc.

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Introduction: Discontinuity in Network

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  • Cyclists face interruptions in the cycling network: e.g. discontinuities
  • Discontinuities include (10):
  • end of a cycling facility
  • change of side of a cycling facility
  • change in cycling facility type
  • intersections
  • re‐routing due to construction
  • change in pavement quality
  • variation in motorized traffic volume on roads along bike facilities
  • bus stops that cut off cyclists on the cycling facility
  • parking spaces where vehicles cut off cyclists on the cycling facility
  • Discontinuities have only recently been introduced as a measure of

cycling network performance (10)

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Introduction: Discontinuity in Network

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  • Discontinuity: end of cycling facility

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End of cycling facility at Chemin de la Côte‐Sainte‐Catherine and Avenue Villeneuve, Montreal, QC (Google street view)

Background

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  • Discontinuity: change in cycling facility side

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End of cycling facility at Saint Catherine Street West and Boulevard de Maisonneuve Ouest, Montreal, QC (Google street view)

Background

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  • Discontinuity: change in cycling facility type

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End of cycling facility at Boulevard Pierre Bernard and Rousseau Street, Montreal, QC (Google street view)

Background

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  • Cyclist behavior and safety at discontinuities has not been studied in the

past

  • Understand the microscopic impacts of discontinuities in the cycling

network in terms of behaviour and safety

  • The methodology is based on
  • video analysis
  • comparing cyclist behaviour at sites with and without discontinuities (control)
  • motion pattern learning
  • surrogate measures of safety

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Objectives of Current Study

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1.

Identify points of discontinuity

2.

Collect video data at discontinuity and control sites

a)

change in cycling facility side

b)

change in type of cycling facility

3.

Extract and classify road user trajectories from video data

4.

Analyse cyclist behaviour using motion pattern learning

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Study various strategies adopted by cyclists when faced with discontinuities

6.

Assess cyclist safety through speed and other surrogate measures of safety

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Methodology

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  • Identify points of discontinuity in Montreal using methodology proposed by

(10)

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Methodology

End of cycling facilities and changes in cycling facility type in Montreal, QC

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  • Collect video data at eight locations with four discontinuity and four control

sites: four of the locations are presented here

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Methodology

Location of two discontinuity and control sites selected for video data collection in Montreal, QC

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Methodology

Locations for video data collection: Change in cycling facility side

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Methodology

Locations for video data collection: Change in cycling facility type and End of cycling facility

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Methodology

Video analysis steps for obtaining road user type and trajectory

Cyclist behaviour analysis Video analysis

Feature tracking Feature grouping Road user classification Trajectory clustering Classified trajectories Motion patterns with high cyclist proportions

B

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  • Motion pattern learning: clustering of the dataset into more homogeneous

subsets using the longest common subsequence (LCSS) similarity measure

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Methodology

Motion pattern learning results showing all road user maneuvers

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Discussion of Results: Cyclist Behavior

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Cyclist maneuvers at site with discontinuity (left) and control site (right)

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Cyclist Behavior at Discontinuity

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Cyclist maneuvers at site with discontinuity: Movements from Southwest to Northeast

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Cyclist Behavior at Control Site

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Cyclist maneuvers at control site: Movements from Northeast to Southwest

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Cyclist Behavior at Discontinuity

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Cyclist maneuvers at control site: Movements from Northeast to Southwest

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Discussion of Results: Cyclist Behavior

Cyclist maneuvers at side with discontinuity (left) and control site (right)

  • Turning left from separate cycling facility into designated roadway
  • left: two way road
  • right: one way road

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Discussion of Results: Cyclist Behavior

Cyclist maneuvers at side with discontinuity (left) and control site (right)

  • Left: turning left from road into separate cycling facility
  • Right: turning left from separate cycling facility to separate cycling facility

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  • Assess cyclist safety by:
  • obtaining speed information of all road users from the collected video data for safety

analysis

  • obtain conflict measures between cyclist and other road users

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Next Step

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Conclusion

  • Although many studies have looked into cyclist behaviour in different

situations and conditions, discontinuities have been overlooked

  • The use of cyclist trajectory clustering provided valuable information on

the microscopic maneuvers of cyclists

  • More maneuvers were observed by cyclists at discontinuities
  • Given the variability in cyclist maneuvers, vehicles and pedestrian face

unexpected movements from cyclists

  • Future work: analyzing more sites to draw stronger conclusions

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References

1.

World Health Organization. 2016. “Road Traffic Injuries.” Retrieved September 15, 2016 (http://www.who.int/mediacentre/factsheets/fs358/en/).

2.

Transport Canada. 2013. “Canadian Motor Vehicle Traffic Collision Statistics: 2013.” Retrieved July 2, 2015 (http://www.tc.gc.ca/media/documents/roadsafety/cmvtcs2013_eng.pdf).

3.

Nosal, T., and L. F. Miranda‐Moreno. 2014. “The Effect of Weather on the Use of North American Bicycle Facilities: A Multi‐City Analysis Using Automatic Counts.” Transportation Research Part A: Policy and Practice 66:213–25.

4.

Yan, X., M. Ma, H. Huang, M. Abdel‐Aty, and C. Wu. 2011. “Motor Vehicle‐Bicycle Crashes in Beijing: Irregular Maneuvers, Crash Patterns, and Injury Severity.” Accident Analysis & Prevention 43(5):1751–58. Retrieved July 24, 2014 (http://www.ncbi.nlm.nih.gov/pubmed/21658503).

5.

Pucher, J. A. 2000. “Making Walking and Cycling Safer: Lessons from Europe.” Transportation Quarterly 54:25–50.

6.

Nabavi‐Niaki, M. S., N. Saunier, and L. F. Miranda‐Moreno. 2017. “Analysis of Cyclist Behaviour at Cycling Network Discontinuities Using Computer Vision”. Accepted for the Transportation Research Board 96th Annual Meeting.

7.

Dill, J., and J. Gliebe. 2008. “Understanding and Measuring Bicycling Behavior: A Focus on Travel Time and Route Choice.” Portland, Oregon. Retrieved June 18, 2015. (http://scholar.google.co.uk/citations?view_op=view_citation&hl=en&user=GNyEzcMAAAAJ&citation_for_view=GNyEzcM AAAAJ:UeHWp8X0CEIC).

8.

Ehrgott, M., J. Y. T. Wang, A. Raith, and C. van Houtte. 2012. “A Bi‐Objective Cyclist Route Choice Model.” Transportation Research Part A: Policy and Practice 46(4):652–63. Retrieved May 31, 2015 (http://linkinghub.elsevier.com/retrieve/pii/S0965856411001844).

9.

Garrard, J., G. Rose, and S. Kai Lo. 2008. “Promoting Transportation Cycling for Women: The Role of Bicycle Infrastructure.” Preventive medicine 46(1):55–59. Retrieved March 1, 2015 (http://www.ncbi.nlm.nih.gov/pubmed/17698185).

10.

Mekuria, M. C., P. G. Furth, and H. Nixon. 2012. Low‐Stress Bicycling and Network Connectivity.

11.

Nabavi‐Niaki, M. S., N. Saunier, and L. F. Miranda‐Moreno. 2016. “A Methodology to Quantify Discontinuities in a Cycling Network ‐ Case Study in Montreal Boroughs.” Transportation Research Board 95th Annual Meeting.

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Questions?

This research project is funded by the Fonds de Recherche du Québec – Nature et Technologies (FRQNT) ICTCT, Lund 2016