Neural Network for Gap Acceptance at Stop‐Controlled Intersections
Publication: Journal of Transportation Engineering
Volume 120, Issue 3
Abstract
The behavior of gap acceptance by vehicles at intersections with stop signs involves the complex interaction of numerous geometric, traffic, and environmental factors. Several methods, including empirical analysis, and theoretical, logit, and probit models have been used to estimate gap acceptance at stop‐controlled intersections. In the past, neural networks have been used to examine problems involving complex interrelationship among many variables and found to perform better than conventional methods. This paper describes the development of a neural network and a binary‐logit model for predicting accepted or rejected gaps at rural, low‐volume two‐way stop‐controlled intersections. The type of control, the turning movements in both the major and minor directions, size of gap, service time, stop type, vehicular speed, queue in the minor direction, and existence of vehicle in the opposite approach were found to influence the driver's decision to accept or reject a gap. The results of the neural network and the binary‐logit model were compared with the observations recorded in the field. The results revealed that the neural network correctly predicted a higher percentage of accepted or rejected gaps than the binary‐logit model.
Get full access to this article
View all available purchase options and get full access to this article.
References
1.
Adams, W. F. (1936). “Road traffic considered as a random series.” J. Instn. of Civ. Engrs., 4, 121–130.
2.
Anderson, D. R., Sweeney, D. J., and Williams, T. A. (1990). Statistics for Business and Economics, 4th Ed., West Publishing, St. Paul, Minn.
3.
Ashton, W. D. (1971). “Gap‐acceptance problems at a traffic intersection.” Appl. Statistics Royal Statistical Soc., 20(2), 130–138.
4.
Ashworth, R. (1968). “A note on the selection of gap acceptance criteria for traffic simulation studies.” Transp. Res., 2(2), 171–175.
5.
Ashworth, R., and Bottom, C. G. (1977). “Some observations of driver gap‐acceptance at a priority intersection.” Traffic Engrg. and Control, 18(12), 569–571.
6.
Blumenfeld, D. E., and Weiss, G. H. (1979). “The effects of gap acceptance criteria on merging delay and capacity at an uncontrolled junction.” Traffic Engrg. and Control, 20(1), 16–20.
7.
Brilon, W. (1988). “Recent developments in calculation methods for unsignalized intersections in West Germany.” Proc., Int. Workshop on Intersections without Traffic Signals, Bochum, Federal Republic of Germany, 111–153.
8.
Camargo, F. A. (1990). Learning algorithms in neural networks, DCC Laboratory, Columbia University, N.Y.
9.
Catchpole, E. A., and Plank, A. W. (1986). “The capacity of a priority intersection.” Transp. Res. Board, 20(6), 441–456.
10.
Cowan, R. J. (1971). “A road with no overtaking.” Australian J. Statistics, 13(2), 94–116.
11.
Dubin, J. A., and Rivers, R. D. (1988). SST users guide, Version 2.0, Dubin and Rivers Assoc., Calif.
12.
Dunne, M. C., and Buckley, D. J. (1972). “Delays and capacities at unsignalized intersections.” Australian Road Res. Board Proc., 6(3), 345–358.
13.
Eberhart, R. C., and Dubbins, R. C. (1990). Neural network PC tools—a practical guide, Academic Press Inc., San Diego, Calif.
14.
Hewitt, R. H. (1983). “Measuring critical gap.” Transp. Sci., 17(1), 87–109.
15.
Hewitt, R. H. (1985). “A comparison between some methods of measuring critical gap.” Traffic Engrg. and Control, 26(1), 13–22.
16.
Krose, B. J. A. et al. (1991). An introduction to neural networks, 4th Edition, University of Amsterdam, Amsterdam, Holland.
17.
Kyte, M., Clemow, C., Mahfood, N., Lall, B. K., and Khisty, C. J. (1991). “Capacity and delay characteristics of two‐way stop‐controlled intersections.” Transp. Res. Board 70th Annu. Meeting, Transportation Research Board, Washington, D.C.
18.
Maze, T. (1981). “A probabilistic model of gap acceptance behavior.” Transp. Res. Record 795, Transportation Research Board, Washington, D.C., 8–13.
19.
Miller, J. A. (1971). “Nine estimators of gap‐acceptance parameters.” Proc., 5th Int. Symp. on the Theory of Traffic and Transp., 215–235.
20.
Neural computing software manual. (1991). Neural Ware Inc., Pittsburgh, Pa.
21.
Pant, P. D., Park, Y., and Neti, S. (1992). “Development of guidelines for installation of intersection control beacons.” Report No. FHWA/OH‐93/006, Ohio Department of Transportation and Federal Highway Administration, Cincinnati, Ohio.
22.
Plank, A. W. (1982). “The capacity of a priority intersection—two approaches.” Traffic Engrg. and Control, 23(2), 88–92.
23.
Polus, A. (1983). “Gap acceptance characteristics at unsignalized urban intersections.” Traffic Engrg. and Control, 24(5), 255–258.
24.
Raff, M. S., and Hart, J. W. (1950). “A volume warrant for urban stop signs.” Eno Found. for Hwy. Traffic Control, Saugatuck, Connecticut.
25.
Sinha, K. C., and Tomiak, W. W. (1971). “Gap acceptance phenomenon at stop‐controlled intersections.” Traffic Engrg., 41(7), 28–33.
26.
Solberg, P., and Oppenlander, J. C. (1966). “Lag and gap acceptance at stop‐controlled intersections.” Hwy. Res. Board 118, Highway Research Board (HRB), Washington, D.C., 58–69.
27.
Tanner, J. C. (1951). “A problem of interference between two queues.” Biometrika, 40(1), 58–69.
28.
Tanner, J. C. (1962). “A theoretical analysis of delay at uncontrolled intersections.” Biometrika, 49(2), 163–170.
29.
Troutbeck, R. J. (1988). “Current and future Australian practices for the design of unsignalized intersections.” Proc., Int. Worshop on Intersections without Traffic Signals, Bochum, Federal Republic of Germany, 1–19.
30.
Tsongos, N. G. (1969). “Comparison of day and night gap‐acceptance probabilities.” Public Road, 35(7), 157–165.
31.
Wagner, F. A. (1966). “An evaluation of fundamental driver decisions and reactions at an intersection.” Hwy. Res. Record 118, HRB, Washington, D.C., 68–84.
32.
Wasserman, P. D. (1980). Neural computing, Theory and Practice, Van Nortrand Reinhold, New York, N.Y.
Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 120 • Issue 3 • May 1994
Pages: 432 - 446
Copyright
Copyright © 1994 American Society of Civil Engineers.
History
Received: Jun 18, 1993
Published online: May 1, 1994
Published in print: May 1994
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.