Quantifying Freeway Capacity Reductions by Rainfall Intensities Based on Stochastic Nature of Flow Breakdown

Authors: Hoyoung Lee, Dong-Kyu Kim, Seung-Young Kho, R. Eddie Wilson

Abstract:

This study quantifies a decrement in freeway capacity during rainfall. Traffic and rainfall data were gathered from Highway Agencies and Wunderground weather service. Three inter-urban freeway sections and its nearest weather stations were selected as experimental sites. Capacity analysis found reductions of maximum and mean pre-breakdown flow rates due to rainfall. The Kruskal-Wallis test also provided some evidence to suggest that the variance in the pre-breakdown flow rate is statistically insignificant. Potential application of this study lies in the operation of real time traffic management schemes such as Variable Speed Limits (VSL), Hard Shoulder Running (HSR), and Ramp Metering System (RMS), where speed or flow limits could be set based on a number of factors, including rainfall events and their intensities.

Keywords: Capacity randomness, flow breakdown, freeway capacity, rainfall.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1131333

References:

[1] Agarwal, M., Maze, T. H., and Souleyrette, R. R. (2006). The weather and its impact on urban freeway traffic operations, 85th Transportation Research Board Annual Meeting, Washington D.C.
[2] Kleitsch, K. L. and D. E. Cleveland. (1971). The Effect of Rainfall on Freeway Capacity. Report TrS-6. Highway Safety Research Institute, University of Michigan, Ann Arbor, Michigan.
[3] Smith, B. L., Byrne, K. G., Copperman, R. B., Hennessy, S. M., and Goodall, N. J. (2004). An Investigation into the Impact of Rainfall on Freeway Traffic Flow, Transportation Research Board, Washington, D.C.
[4] Chung, E., Ohtani, O., Warita, H., Kuwahara, M., and Morita, H. (2006). Does weather affect highway capacity. 5th International Symposium on Highway Capacity and Quality of Service, Yakoma, Japan.
[5] Brilon, W., Geistefeldt, J., and Regler, M. (2005). Reliability of freeway traffic flow: a stochastic concept of capacity. Proceedings of 16th International Symposium on Transportation and Traffic Theory. 125-144.
[6] Transportation Research Board. (2010). Highway Capacity manual. Transportation Research Board. Washington D.C.
[7] Department for Transport. (2010). Road Statistics 2009: Traffic, Speed and congestion.
[8] Smith, B. L., and Ulmer J. M. (2003). Freeway Traffic Flow Rate Measurement: Investigation into Impact of Measurement Time interval. Journal of Transportation Engineering, ASCE, 29, 3, 223-229.
[9] Banks, J. (2006). New Approach to Bottleneck Capacity Analysis: Final Report. UCB-ITS-PRR-2006-13. California PATH, Institute of Transportation Studies, University of California, Berkeley.
[10] Jia. Z., Varaiya, P., Chen, C., Petty, K., and Skabardonis, A. (2000). Congestion, Excess Demand, and Effective Capacity in California Freeways.
[11] Lorenz, M. and Elefteriadou, L. (2001). Defining Freeway Capacity as a Function of Breakdown Probability. Transportation Research Record, 1776, 43-51.
[12] Kerner, B. S. (1999). The Physics of Traffic. Physics World, 12, 25-30.