Impact of Freeway Geometric and Incident Characteristics on Incident Detection
Publication: Journal of Transportation Engineering
Volume 122, Issue 6
Abstract
The potential improvement in incident detection can be achieved by examining the major factors that may influence incident rates and incident detection rates. The subsections of the central I-4 corridor were grouped by geometric characteristics including horizontal alignment (straight or curved) and vertical alignment (upgrade, level, or downgrade); and also by presence of ramps (on-ramps, off-ramps, or none). It was found that subsections with off-ramps have significantly higher incident rate and incident detection rate than subsections with on-ramps or with no ramps. It was also found that upgrade subsections have significantly higher incident rate than level or downgrade subsections. However, no significant difference in incident detection rate was found between these subsections. Based on the study results and to improve performance of incident detection algorithms on I-4, the subsections were regrouped by two factors: horizontal alignment and presence of ramps.
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References
1.
Al-Deek, H., Cryer, J., Ishak, S., Khan, A., and Yarid, J. (1995). LOVATS: Loop output verification and algorithm testing system, user manual, text version, parts I and II . Dept. Civ. and Envir. Engrg., University of Central Florida, Orlando, Fla.
2.
Athol, P. (1965). “Interdependence of certain operational characteristics within a moving traffic stream.”Hwy. Res. Rec. 72, Transp. Res. Board, Washington, D.C., 58–87.
3.
Forbes, J. F.(1992). “Identifying incident congestion.”ITE J., 62(6), 17–22.
4.
Gall, A., and Hall, F. (1990). “Distinguishing between incident congestion and recurrent congestion: A proposed logic.”Transp. Res. Rec. 1232, Transp. Res. Board, Washington, D.C., 1–8.
5.
Hall, F., Shi, Y., and Atala, G. (1993). “On-line testing of the McMaster incident detection algorithm under recurrent congestion.”Transp. Res. Rec. No. 1394, Transp. Res. Board, Washington, D.C., 1–7.
6.
Hsio, C. H., Lin, C. T., and Cassidy, M.(1994). “Application of fuzzy logic and neural networks to automatically detect freeway traffic incidents.”J. Transp. Engrg., ASCE, 120(5), 753–770.
7.
Levin, M., and Krause, G. (1979a). “Incident-detection algorithms, Part-1. Off-line evaluation.”Transp. Res. Rec. 722, Transp. Res. Board, Washington, D.C., 49–58.
8.
Levin, M., and Krause, G. (1979b). “Incident-detection algorithms, Part-2. On-line evaluation.”Transp. Res. Rec. 722, Transp. Res. Board, Washington, D.C., 58–64.
9.
Lindley, J.(1987). “Urban freeway congestion: Quantification of the problem and effectiveness of potentail solutions.”ITE J., 57(1), 27–32.
10.
Menenhall, W., and Sincich, T. (1993). A second course in business statistics: Regression analysis . 4th Ed., Maxwell, McMillan Publ. Co., Toronto, Canada.
11.
Payne, H. (1976). “Development and testing of incident-detection algorithms: Vol. 1, summary of results.”Federal Hwy. Admin., Rep. FHWA-RD-76-19, Washington, D.C.
12.
Payne, H., Helfenbein, E., and Knobel, H. (1976). “Development and testing of incident-detection algorithms: Vol. 2, research methodology and detailed results.”Federal Hwy. Admin., Rep. FHWA-RD-76-20, Washington, D.C.
13.
Payne, H., and Knobel, H. (1976). “Development and testing of incident-detection algorithms: Vol. 3, users guidelines.”Federal Hwy. Admin., Rep., FHWA-RD-76-21, Washington, D.C.
14.
Payne, H., and Tignor, S. (1978). “Freeway incident detection algorithms based on decision trees with states.”Transp. Res. Rec. 682, Transp. Res. Board, Washington, D.C., 30–37.
15.
Persaud, B., and Hall, F.(1989). “Catastrophe theory and patterns in 30-second freeway traffic data—implications for incident detection.”Transp. Res. A, 23(2), 103–113.
16.
Ritchie, S. G., and Ruey, L. C. (1993). “Simulation of freeway incident detection using artificial neural networks.”Transp. Res. C, 1(3), 203– 217.
17.
Stephanedes, Y. J., and Athanassios, P. C.(1993). “Freeway incident detection through filtering.”Transp. Res. C, 1(3), 219–233.
18.
Sumner, R., et al. (1983). “Chapter 11 of Incident Detection Algorithms.”Freeway Management Handbook, Vol. 2., Dept. of Transp., Federal Highway Administration, Washington, D.C.
19.
Tignor, S., and Payne, H.(1977). “Improved freeway incident-detection algorithms.”Public Roads, 41(1), 32–40.
20.
West, J. (1969). “Proposed real-time surveillance and control systems for Los Angeles.”Final Rep., Los Angeles, Freeway Operations Dept., District 7, California Div. of Hwys.
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Copyright © 1996 American Society of Civil Engineers.
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Published online: Nov 1, 1996
Published in print: Nov 1996
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