Dispersion Effect in Left-Turning Bicycle Traffic and Its Influence on Capacity of Left-Turning Vehicles at Signalized Intersections
Abstract
Bicycle traffic passing through intersections exhibits a dispersion effect that can influence the movements of nearby vehicles. The primary objective of this study was to investigate the dispersion effect in left-turning bicycle traffic at signalized intersections and to evaluate the effect's influence on the capacity of left-turning vehicles. Characteristics of the dispersion effect were investigated in 20 h of video data collected in Nanjing, China. A Poisson model was estimated to evaluate the factors contributing to platoon width of left-turning bicycle traffic. The impacts of platoon width on the capacity and delay of left-turning vehicles also were evaluated. Results showed that several factors, including the number of left-turning electric bicycles (e-bicycles) and conventional bicycles arriving during the red light period and the directional factor, significantly affected the platoon width of left-turning bicycle traffic. Sensitivity analysis results indicated that the platoon was widest when the number of left-turning e-bicycles divided by the number of total left-turning bicycles arriving per cycle was about 60%. An adjustment factor that accounted for the impacts of left-turning bicycles on the capacity of left-turning vehicles was proposed. Increasing the platoon width of left-turning bicycles from three to eight reduced the left-turning vehicle capacity about 19% and increased the capacity of all left-turning traffic around 25%.
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References
1. Karel M., Robert B. N., and Kunreuther H. Short-Run and Long-Run Policies for Increasing Bicycle Transportation for Daily Commuter Trips. Transport Policy, Vol. 2, No. 1, 1995, pp. 67–79.
2. Shan X. A Research on Urban Bicycle Transportation Rational Ridership and Road Resource Allocation. PhD dissertation. Southeast University, Nanjing China, 2007.
3. Dill J. Bicycling for Transportation and Health: The Role of Infrastructure. Journal of Public Health Policy, Vol. 30, 2009, pp. S95–S110.
4. Pucher J., Buehler R., and Seinen M. Bicycling Renaissance in North America? An Update and Re-Appraisal of Cycling Trends and Policies. Transportation Research Part A: Policy and Practice, Vol. 45, No. 6, 2011, pp. 451–475.
5. Pucher J., and Buehler R. Analysis of Bicycling Trends and Policies in Large North American Cities: Lessons for New York. Final report. Region 2 University Transportation Research Center, New York, 2011.
6. Pucher J., and Buehler R. Why Canadians Cycle More Than Americans: A Comparative Analysis of Bicycling Trends and Policies. Transportation Policy, Vol. 13, No. 3, 2006, pp. 265–279.
7. Shaheen S. A., Guzman S., and Zhang H. Bikesharing in Europe, the Americas, and Asia: Past, Present, and Future. In Transportation Research Record: Journal of the Transportation Research Board, No. 2143, Transportation Research Board of the National Academies, Washington, D.C., 2010, pp. 159–167.
8. Pucher J., and Buehler R. Cycling for Everyone: Lessons from Europe. In Transportation Research Record: Journal of the Transportation Research Board, No. 2074, Transportation Research Board of the National Academies, Washington, D.C., 2008, pp. 58–65.
9. John P., Dill J., and Handy S. Infrastructure, Programs and Policies to Increase Bicycling: An International Review. Preventive Medicine, Vol. 50, 2010, pp. S106–S125.
10. Yang C., Wang W., Li Z., and Zhao Y. The Changing Trends of Bicycle Usage in China: Macrolevel Analysis. Presented at 92nd Annual Meeting of the Transportation Research Board, Washington, D.C., 2013.
11. Weinert J. X., Ma C. T., and Cherry C. R. The Transition to Electric Bikes in China: History and Key Reasons for Rapid Growth. Transportation, Vol. 34, 2007, pp. 301–318.
12. Lin S., He M., Tan Y., and He M. Comparison Study on Operating Speeds of Electric Bicycles and Bicycles: Experience from Field Investigation in Kunming, China. In Transportation Research Record: Journal of the Transportation Research Board, No. 2048, Transportation Research Board of the National Academies, Washington, D.C., 2008, pp. 52–59.
13. Cherry C. R., and Cervero R. Use Characteristics and Mode Choice Behavior of Electric Bike Users in China. Transport Policy, Vol. 14, No. 3, 2007, pp. 247–257.
14. Wang Y., Wei G., Zhu X., and Pei Y. Capacity of Bicycle Platoon Flow at Two-Phase Signalized Intersection Case Analysis of Xi'an City. Promet—Traffic and Transportation, Vol. 23, No. 3, 2011, pp. 177–186.
15. Cherry C. R., Weinert J. X., and Yang X. Comparative Environmental Impacts of Electric Bikes in China. Transportation Research Part D: Transport and Environment, Vol. 14, No. 5, 2009, pp. 281–290.
16. Zhao D., Wang W., Li C., Li Z., Fu P., and Hu X. Modeling of Passing Events in Mixed Bicycle Traffic with Cellular Automata. In Transportation Research Record: Journal of the Transportation Research Board, No. 2387, Transportation Research Board of the National Academies, Washington, D.C., 2013, pp. 26–34.
17. Conway A., Cheng J., Peters D., and Nicholas L. Characteristics of Multimodal Conflicts in Urban On-Street Bicycle Lanes. In Transportation Research Record: Journal of the Transportation Research Board, No. 2387, Transportation Research Board of the National Academies, Washington, D.C., 2013, pp. 93–101.
18. Bai L., Liu P., Chen Y., Zhang X., and Wang W. Comparative Analysis of the Safety Effects of Electric Bikes at Signalized Intersections. Transportation Research Part D: Transport and Environment, Vol. 20, 2013, pp. 48–54.
19. Cherry C. R., Hill T. Q., and Jian X. Assessing Countermeasures Designed to Reduce Hazards Between Bike Lane Occupants and Right-Turning Automobiles in China. Journal of Transportation Safety and Security, Vol. 4, 2013, pp. 277–294.
20. Chen X., Shao C., and Yue H. Influence of Bicycle Traffic on Capacity of Typical Signalized Intersection. Tsinghua Science and Technology, Vol. 12, No. 2, 2007, pp. 198–203.
21. Highway Capacity Manual 2010. Transportation Research Board of the National Academies, Washington, D.C., 2010.
22. Washington S., Karlaftis M., and Mannering F. Statistical and Econometric Methods for Transportation Data Analysis. Chapman & Hall/CRC, Boca Raton, Fla., 2003.
23. Harris D., Zhao Y., and Hardin J. W. Modeling Under-dispersed Count Data with Generalized Poisson Regression. Stata Journal, Vol. 12, No. 4, 2012, pp. 736–747.
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Article first published online: January 1, 2014
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