Modeling Automobile Interference due to Midblock Pedestrian Activity on Urban Street Segments
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 144, Issue 1
Abstract
The 2010 highway capacity manual (HCM) provides an approach to estimate the mutual between pedestrians and automobiles at signalized intersections. However, the manual provides little guidance for capturing the interactions between pedestrians and automobiles at unsignalized midblock pedestrian crosswalks on urban street segments. The movements of vehicles on urban streets can be significantly impacted by midblock delays and stops. One of the performance measures in evaluating automobile performance on urban street segments is the travel speed. The manual computes the segment travel speed based on the segment length, the segment running time, and the control delay. Friction conditions, such as the midblock pedestrian crossings, interfere with the traffic flow on urban street segments and therefore increase the segment running time, which consequently lowers the travel speed and the level of service (LOS) of the segment. The frequency of the interference to vehicles is related to the frequency of the arrival of pedestrians and the flow of vehicles. This paper develops and evaluates a model to estimate the frequency of midblock pedestrian interference to vehicles at unsignalized midblock crosswalks on urban street segments, using the traffic volume, the pedestrian volume, and the median type and posted speed limit as the independent variables. The results show that the traffic volume and the pedestrian volume are the most significant models.
Get full access to this article
View all available purchase options and get full access to this article.
References
Andreou, S. A., Marks, D. H., and Clark, R. M. (1987a). “A new methodology for modeling break failure patterns in deteriorating water distribution systems: Theory.” Adv. Water Res., 10(1), 11–20.
Andreou, S. A., Marks, D. H., and Clark, R. M. (1987b). “A new methodology for modeling break failure patterns in deteriorating water distribution systems: Theory.” Adv. Water Res., 10(1), 2–10.
Baltes, M., and Chu, X. (2002). “Pedestrian level of service for midblock street crossings.” Transp. Res. Rec., 1818, 125–133.
Fitzpatrick, K., Brewer, M. A., and Turner, S. (2002). “Another look at pedestrian walking speed.” Transp. Res. Rec., 1982, 21–29.
Forde, A., and Maina, E. (2017). “Validation and sensitivity analysis of a developed midblock vehicular delay model.” J. Transp. Eng. Part A: Syst., 143(7), in press.
Giukema, S. D., and Coffelt, J. P. (2009). “Practical considerations in statistical modeling of count data for infrastructure systems.” J. Infrastruct. Syst., 172–178.
Hauer, E. (2001). “Over dispersion in modeling accidents on road section and in empirical Bayesian estimation.” Accid. Anal. Prev., 33(6), 799–808.
TRB (Transportation Research Board). (2010). “Highway Capacity Manual.” National Research Council, Washington, DC.
Hilbe, J. M. (2011). Negative binomial regression, 2nd Ed., Cambridge Univ., Cambridge, U.K.
Knoblauch, R. L., Nitzburg, M., and Seifert, R. L. (2001). “Pedestrian crosswalk case studies: Richmond, Virginia; Buffalo, New York; Stillwater, Minnesota.” Center for Applied Research for Federal Highway Administration, Washington, DC.
Liu, H., Davidson, R. A., Rosowsky, D. V., and Stedinger, J. R. (2005). “Negative binomial regression of electric power outages in hurricanes.” J. Infrastruct. Syst., 258–267.
Lord, D. (2006). “Modeling motor vehicle crashes using Poisson-gamma models: Examining the effects of low sample mean values and small sample size on estimation of the fixed dispersion parameter.” Accid. Anal. Prev., 38(4), 751–766.
Lord, D., Washington, S. P., and Ivan, J. N. (2005). “Poisson, Poisson-gamma, and zero-inflated regression models of motor vehicle crashes: Balancing statistical fit and theory.” Accid. Anal. Prev., 37(1), 35–46.
Lu, L., Ren, G., Wang, W., Chan, C. Y., and Wang, J. (2016). “A cellular automaton simulation model for pedestrian and vehicle interaction behaviors at unsignalized mid-block crosswalks.” Accid. Anal. Prev., 95, 425–437.
McKay, M. D., Beckman, R. J., and Conover, W. J. (1979). “Comparison of three methods for selecting values of input variables in the analysis of output from a computer code.” Technometrics, 21(2), 239–245.
Mitman, M. F., Cooper, D., and DuBose, B. (2010). “Driver and pedestrian behavior at uncontrolled crosswalks in Tahoe basin recreation area of California.” Transp. Res. Rec., 2198, 23–31.
Mitman, M. F., Ragland, D. R., and Zeeger, C. V. (2008). “Marked crosswalk dilemma: Uncovering some missing links in a 35-year debate.” Transp. Res. Rec., 2073, 86–93.
Montgomery, D. C., and Peck, E. A. (1992). Introduction to linear regression analysis, Wiley, New York.
Nitzburg, M., and Knoblauch, R. L. (2001). “An evaluation of high-visibility crosswalk treatment.” FHWA-RD-00-105, Clearwater, FL.
Oh, J., and Washington, K. C. (2004). “Development of accident prediction models for rural highway intersections.” Transp. Res. Rec., 1897, 18–27.
Patil, G. R., and Pawar, D. S. (2015). “Pedestrian temporal and spatial gap acceptance at mid-block street crossing in developing world.” J. Saf. Res., 52, 39–46.
SAS 9.3 [Computer software]. SAS Institute, Inc., Cary, NC.
Shi, J., Chen, Y., Ren, F., and Rong, J. (2007). “Research on pedestrian behavior and traffic characteristics at un-signalized mid-block crosswalk: Case study in Beijing.” Transp. Res. Rec., 2038, 23–33.
Turner, S., Fitpatrick, K., Brewer, M., and Park, E. S. (2006). “Motorist yielding to pedestrians at unsignalized intersections: Findings from a national study on improving pedestrian safety.” Transp. Res. Rec., 1982, 1–12.
Yao, S., Loo, B. P. Y., and Lam, Y. (2015). “Measures of activity-based pedestrian exposure to the risk of vehicle-pedestrian collisions: Space-time path vs. potential path tree.” Accid. Anal. Prev., 75, 320–332.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 144 • Issue 1 • January 2018
Copyright
©2017 American Society of Civil Engineers.
History
Received: Nov 3, 2016
Accepted: Aug 8, 2017
Published online: Oct 28, 2017
Published in print: Jan 1, 2018
Discussion open until: Mar 28, 2018
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.