Investigating cyclist interaction behavior through a controlled laboratory experiment

Yufei Yuan, Winnie Daamen, Bernat Goñi-Ros, Serge Hoogendoorn

Abstract


Nowadays, there is a need for tools to support city planners in assessing the performance of cycling infrastructure and managing bicycles and mixed flows. Microscopic and macroscopic bicycle traffic models can be used to fulfill this need. However, fundamental knowledge on individual cyclist interaction behavior (which should underpin these models) is hardly available in literature. Detailed bicycle traffic data are necessary if we want to gain insight into cyclist interaction behavior and develop sound behavioral theories and models. Laboratory experiments have been proven to be one of the most effective ways to collect detailed traffic data. For this reason, a controlled experiment aimed to investigate cyclist interaction behavior has been carried out at Delft University of Technology. This paper describes the experimental design, the resulting microscopic bicycle trajectories, and some preliminary results regarding one of the most common interaction situations: the bidirectional interaction. The preliminary results reveal how and to what extent cyclists interact in bidirectional cycling. It is found that cyclists perform a clearly-visible evading (collision avoidance) maneuver when they have face-to-face encounters. During these maneuvers, changes in speed and displacements in the lateral direction are observed. Cyclists start to deviate from their original path when they are around 30 m from each other, and they strongly prefer passing on the right-hand side. Moreover, the expectation of gender differences in cycling behavior reported in the literature is confirmed: our results show that women generally cycle more slowly than men and deviate more from their intended paths in face-to-face encounters. More observations will be available in the next stage of data analysis. These findings can be used to formulate improved microscopic bicycle traffic models for infrastructure design and policy development.

Full Text:

PDF

References


Amsterdam-Municipality, Jaarverslag. (2011). 2011 annual report. Amsterdam: Department of Infrstructure, Traffic and Transport.

Andresen, E., Chraibi, M., Seyfried, A., & Huber, F. (2014). Basic driving dynamics of cyclists. In M. Behrisch, D. Krajzewicz, & M. Weber (eds.), Simulation of urban mobility: First International Conference, SUMO 2013. Revised selected papers (p. 18–32). Berlin, Germany: Springer Berlin Heidelberg.

Botma, H., & Papendrecht, H. (1991). Traffic operation of bicycle traffic. Transportation Research Record: Journal of the Transportation Research Board, 1320, 65–72.

Daamen, W., Hoogendoorn, S. P. (2003). Experimental research of pedestrian walking behavior. Transportation Research Record: Journal of the Transportation Research Board, 1828, 20–30.

Daamen, W., Hoogendoorn, S. P., Campanella, M., & Versluis, D. (2012). Interaction behavior between individual pedestrians. In U. Weidmann, U. Kirsch, & M. Schreckenberg (eds.), Pedestrian and evacuation dynamics (p. 1305–1314).

Cham, Switzerland: Springer International Publishing.

Duives, D., Daamen, W., & Hoogendoorn, S. P. (2012). Trajectory analysis of pedestrian crowd movements at a Dutch music festival. In U. Weidmann, U. Kirsch, & M. Schreckenberg (eds.), Pedestrian and evacuation dynamics (p. 151–166). Cham, Switzerland: Springer International Publishing.

Emond, C., Tang, W., &, Handy, S. (2009). Explaining gender difference in bicycling behavior. Transportation Research Record: Journal of the Transportation Research Board, 2125, 16–25.

Gould, G., & Karner, A. (2009). Modeling bicycle facility operation: Cellular automaton approach. Transportation Research Record: Journal of the Transportation Research Board, 2140, 157–64.

Heesch, K. C., Sahlqvist, S., & Garrard, J. (2012). Gender differences in recreational and transport cycling: A cross-sectional mixed-methods comparison of cycling patterns, motivators, and constraints. International Journal of Behavioral Nutrition and Physical Activity, 9(1), 106.

Henderson, L. F., & Lyons, D. J. (1972). Sexual differences in human crowd motion. Nature, 240(5380), 353–355.

Homburger, W. S. (1976). Capacity of bus routes, and of pedestrian and bicycle facilities. Berkeley, CA: Institute of Transportation Studies.

Hoogendoorn, S. P., & Daamen, W. (2016). Bicycle headway modeling and its applications. Proceedings of the Transportation Research Board 95th Annual Meeting, Washington DC.

Huber, M., Su, Y.-H., Krüger, M., Faschian, K., Glasauer, S., & Hermsdörfer, J. (2014). Adjustments of speed and path when avoiding collisions with another pedestrian. PLoS ONE, 9(2), 1–13.

Knoppers, P., Van Lint, J. W. C., & Hoogendoorn, S. P. (2012). Automatic stabilization of aerial traffic images. Proceedings of the Transportation Research Board 91st Annual Meeting, Washington, DC.

Krizek, K. J., Johnson, P. J., & Tilahun, N. (2005). Gender differences in bicycling behavior and facility preferences. Research on Women’s Issues in Transportation, 2, 31–40.

Ma, X., & Luo, D. (2016). Modeling cyclist acceleration process for bicycle traffic simulation using naturalistic data. Transportation Research Part F: Traffic Psychology and Behavior, 40, 130–144.

Moussaïd, M., Helbing, D., Garnier, S., Johansson, A., Combe, M, & Theraulaz, G. (2009). Experimental study of the behavioral mechanisms underlying self-organization in human crowds. Proceedings of the Royal Society of London B: Biological Sciences, 276(1668), 2755–2762.

Navin, F. P. D. (1994). Bicycle traffic flow characteristics: Experimental results and comparisons. ITE Journal, 64(3), 31–37.

Raksuntorn, W., & Khan, S. (2003). Saturation flow rate, start-up lost time, and capacity for bicycles at signalized intersections. Transportation Research Record: Journal of the Transportation Research Board, 1852, 105–13.

Rasmussen, J. (1986). Information processing and human-machine interaction: An approach to cognitive engineering. New York: Elsevier Science Inc.

Schleinitz, K., Petzoldt, T., Franke-Bartholdt, L., Krems, J. F., & Gehlert, T. (2017). The German naturalistic cycling study—Comparing cycling speed of riders of different e-bikes and conventional bicycles. Safety Science, 92, 290–97.

Seriani, S., Fernandez, R., & Hermosilla, E. (2015). Experimental study for estimating capacity of cycle lanes. Transportation Research Procedia, 8, 192–203.

Seyfried, A., Steffen, B., Passon, O., & Klingsch, W. (2009). New insights into pedestrian flow through bottlenecks. Transportation Science, 43(3), 395–406.

Shepherd, R. (1994). Road and path quality for cyclists. Proceedings of the 17th ARRB Conference, Queensland, Australia.

Sugiyama, Y., Fukui, M., Kikuchi, M., Hasebe, K., Nakayama, A., Nishinari, K., Tadaki, S., & Yukawa, S. (2008). Traffic jams without bottlenecks—experimental evidence for the physical mechanism of the formation of a jam. New Journal of Physics, 10(3), 033001.

Tian, W., Ma., J, Song, W. G., & Liddle, J. (2012). Experimental study of pedestrian behaviors in a corridor based on digital image processing. Fire Safety Journal, 47, 8–15.

Twaddle, H., & Grigoropoulos, G. (2016). Modeling the speed, acceleration, and deceleration of bicyclists for microscopic traffic simulation. Transportation Research Record: Journal of the Transportation Research Board, 2587, 8–16.

Vansteenkiste, P., Cardon, G., D'Hondt, E., Philippaerts, R., & Lenoir, M. (2013). The visual control of bicycle steering: The effects of speed and path width. Accident Analysis & Prevention, 51, 222–227.

Yang, J. M. (1985). Bicycle traffic in China. Transportation Quarterly, 39(1), 93–107.

Zamanov, M. (2012). Estimation of fundamental diagram of bicycle traffic flow using observations on bicycle lanes in Delft. Delft: Delft University of Technology.




DOI: http://dx.doi.org/10.5198/jtlu.2018.1155


Copyright (c) 2018 Yufei Yuan, Winnie Daamen, Bernat Goñi-Ros, Serge Hoogendoorn