OVERVIEW OF INCIDENT DETECTION ALGORITHMS

Year 2010, Volume: 12 Issue: 1, 33 - 45, 01.01.2010

İlgın Yaşar

Abstract

Urban congestion is a growing national problem that affects our mobility. Delay
experienced by travelers in Turkey is due to both recurring congestion caused by high traffic
volume and non-recurring congestion results from incidents such as crashes, vehicle
breakdowns, weather, special events, construction and maintenance activities. In the United
States, approximately one-half of the delay is caused by nonrecurring congestion (Bertini,
2004; Lindley, 1986; Bertini, 2001). Therefore many urban areas are actively pursuing
congestion management strategies, especially those associated with non-recurrent congestion.
Incident detection is a crucial as it determines the reliability and efficiency of the whole
incident management system. This study focuses on available incident detection algorithms
that are designed to improve mobility and enhance safety by rapidly responding to incidents

Keywords

Incident detection algorithms, non-recurring congestion, incident management.

KAZA-OLAY TESPİT ALGORİTMALARINA GENEL BAKIŞ

Abstract

Kentsel trafik sıkışıklığı, ulaşımı olumsuz etkileyen ve giderek ciddileşen ulusal bir
sorundur. Türkiye’de yolcuların maruz kaldığı gecikme, hem aşırı yoğun trafik gibi
tekrarlayan hem de kaza, hava şartları, özel durumlar, yol yapım ve onarım çalışmaları gibi
tekrarlanmayan olaylardan kaynaklanmaktadır. A.B.D.’de, yolcuların harcadığı toplam
bekleme süresine yaklaşık yarısı tekrarlanmayan sıkışıklıklar neden olmaktadır (Bertini, 2004;
Lindley, 1986; Bertini, 2001). Dolayısıyla, birçok kentsel bölgede sıkışıklık yönetim
stratejileri, özellikle de tekrarlanmayan sıkışıklıklarla alakalı olanlar aktif olarak
kullanılmaktadır. Sıkışıklık yönetimi için en geçerli yöntemlerden biri kaza-olay yönetimidir.
Kaza-olay tespiti, kaza-olay yönetiminin güvenilirliğini ve etkinliğini belirlediği için önemi
büyüktür. Bu çalışma, şehir yollarında güvenliği iyileştirmek ve mobiliteyi arttırmak için
kaza-olaylara hızlı bir şekilde karşılık verilmesini amaçlayan mevcut kaza-olay tespit
algoritmaları hakkında bilgi sağlayacaktır.

Keywords

Kaza-olay tespit algoritmaları, tekrarlanmayan trafik sıkışıklıkları, kaza-olay yönetimi.

References

• Ahmed, M.S., Cook, A.R. (1977): ―Analysis of freeway traffic time-series data using Box- Jenkins techniques‖, Transportation Research Record, No. 722, TRB, National Research Council, pp. 1-9.
• Balke, K.N. (1993): ―An evaluation of existing incident detection algorithms‖, Research Report, FHWA/TX-93/1232-20, Texas Transportation Institute, the Texas A&M University System, College Station, TX.
• Balke, K., Dudek, C.L., Mountain, C.E. (1996): ―Using probe-measured travel time to detect major freeway incidents in Houston, Texas‖, Transportation Research Record, No. 1554, TRB, National Research Council, pp. 213-220.
• Bell, M.G.H., Thancanamootoo, S. (1986): ―Automatic incident detection in urban road networks‖, Proceedings of Planning and Transport Research and Computation (PTRC) Summer Annual Meeting, University of Sussex, UK, pp. 175-185.
• Bertini, R., Rose, M., El-Geneidy, A. (2004): ―Using Archived Data to Measure Operational Benefits of ITS Investments: Region 1 Incident Response Program‖, Research Report sponsored by Oregon Department of Transportation.
• Bertini, R., Tantiyanugulchai, S., Anderson, E., Lindgren, R., Leal, M. (2001): ―Evaluation of Region 2 Incident Response Program Using Archived Data‖, Portland State University, Transportation Research Group, Research Report.
• Bhandari, N., Koppelman, F.S., Schofer, J.L., Sethi, V., Ivan, J.N. (1995): ―Arterial incident detection integrating data from multiple sources‖, Transportation Research Record, No. 1510, TRB, National Research Council, pp. 60-69.
• Black, J., Sreedevi, I. (2001): ―Automatic incident detection algorithms‖, ITS Decision Database
• Detection/aida.html>, February. PATH,
• Chang, E.C.-P., Wang, S.-H. (1994): ―Improved freeway incident detection using fuzzy set theory‖, Transportation Research Record, No. 1453, TRB, National Research Council, pp.75- 82.
• Collins, J.F., Hopkins, C.M., Martin, J.A. (1979): ―Automatic incident detection—TRRL algorithms HIOCC and PATREG‖, TRRL Supplementary Report, No. 526, Crowthorne, Berkshire, U.K.
• Cook, A.R., Cleveland, D.E. (1974): ―Detection of freeway capacity-reducing incidents by trafficstream measurements‖, Transportation Research Record, No. 495, TRB, National Research Council, pp. 1-11.
• Dudek, C.L., Messer, C.J., Nuckles, N.B. (1974): ―Incident detection on urban freeway‖, Transportation Research Record, No. 495, TRB, National Research Council, pp. 12-24.
• Fambro, D.B., Ritch, G.P. (1979): ―Automatic detection of freeway incidents during low volume conditions‖, Report No. FHWA/TX-79/23-210-1, Texas Transportation Institute, Texas A&M University System, College Station, TX.
• Gall, A.I., Hall, F.L. (1989): ―Distinguishing between incident congestion and recurrent congestion:a proposed logic‖, Transportation Research Record, No. 1232, TRB, National Research Council, pp. 1-8.
• Hellinga, B., Knapp, G. (2000): ―Automatic vehicle identification technology-based freeway incident detection‖, Transportation Research Record, No. 1727, TRB, National Research Council, pp. 142-153.
• Hsiao, C.-H., Lin, C.-T., Cassidy, M. (1994): ―Application of fuzzy logic and neural Networks to automatically detect freeway traffic incidents‖, Journal of Transportation Engineering, Vol. 120, No. 5, ASCE, pp. 753-772.
• Ivan, J.N., Schofer, J.L., Koppelman, F.S., Massone, L.L.E. (1995): ―Real-time data fusion for arterial street incident detection using neural networks‖, Transportation Research Record, No. 1497, TRB, National Research Council, pp. 27-35.
• Khan, S.I., Ritchie, S.G. (1998): ―Statistical and neural classifiers to detect traffic operational problems on urban arterials‖, Transportation Research Part C, Vol. 6, No. 3, pp. 291-314.
• Lee, S., Krammes, R.A., Yen, J. (1998): ―Fuzzy-logic-based incident detection for signalized diamond interchanges‖, Transportation Research Part C, Vol. 6, No. 3, pp. 359-377.
• Lee, Y.-I., Hwang, J.-H. (2001): ―Development of a logit-based incident detection algorithm for urban streets‖, Preprint CD-ROM, the 80th TRB Annual Meeting, Transportation Research Board, National Research Council, Washington D.C., January.
• Levin, M., Krause, G.M. (1978): ―Incident detection:a Bayesian approach‖, Transportation Research Record, No. 682, TRB, National Research Council, pp. 52-58.
• Lindley, J.A. (1987): ―Urban Freeway Congestion: Quantification of the Problem and Effectiveness of Potential Solutions‖, ITE Journal, Jan., pp. 27–32
• Lindley, J. A. (1986): ―Qualification of Urban Freeway Congestion and Analysis of Remedial Measures‖, Report RD/87-052. FHWA, U.S. Department of Transportation.
• Mak, C.L., Fan, H.S.L. (2007): ―Development of Dual-Station Automated Expressway Incident Detection Algorithms‖, IEEE Transactions on Intelligent Transportation Systems 8(3), pp. 480-490
• Mak, C.L., Fan, H.S.L. (2005): ―Transferability of expressway incident detection algorithms to Singapore and Melbourne‖, J. Transp. Eng., vol. 131, no. 2, pp. 101–111.
• Masters, P.H., Lam, J.K., Wong, K. (1991): ―Incident detection algorithms of COMPASS— an advanced traffic management system‖, Proceedings of Vehicle Navigation and Information Systems Conference, Part 1, SAE, Warrendale, PA, October, pp. 295-310.
• Michalopoulos, P.G. (1991): ―Vehicle detection video through image processing: the Autoscope system‖, IEEE Transactions on Vehicular Technology, Vol. 40, No. 1, IEEE, pp. 21-29.
• Mouskos, K.C., Niver, E., Lee, S., Batz, T., Dwyer, P. (1999): ―Transportation operations coordinating committee system for managing incidents and traffic: evaluation of the incident detection system‖, Transportation Research Record, No. 1679, TRB, National Research Council, pp. 50-57.
• Nam, D., Mannering, F. (2000): ―An exploratory hazard-based analysis of highway incident duration‖, Transportation Reseach Part A 34, pp.84-102.
• Parkany, A. E., Bernstein, D. (1993): ―Using VRC data for incident detection‖, Proceedings of the Pacific Rim Trans Tech Conference, The 3rd International Conference on Applications of Advanced Technologies in Transportation Engineering, Seattle, Washington, 25-28.
• Payne, H.J., Helfenbein, E.D., Knobel, H.C. (1976): ―Development and testing of incident detection algorithms, Volume 2: research methodology and detailed results‖, Report No. FHWA-RD- 76-20, FHWA, Washington D.C.
• Persaud, B.N., Hall, F.L. (1989): ―Catastrophe theory and patterns in 30-second freeway traffic data—implications for incident detection‖, Transportation Research Part A, Vol. 23, No.2, pp. 103-113.
• Petty, K.F., A. Skabardonis, Varaiya, P.P. (1997): ―Incident detection with probe vehicles: performance, infrastructure requirements and feasibility‖, Transportation Systems 1997: A Proceedings Volume from the 8th IFAC/IFIP/IFORS Symposium, Chania, Greece, June 16- 18, 1997, Vol. 1, pp. 125-130.
• Ritchie, S.G., Cheu, R.L. (1993): ―Simulation of freeway incident detection using artificial neural networks‖, Transportation Research Part C, Vol. 1, No. 3, pp. 203-217.
• Samant, A., Adeli, H. (2000): ―Feature extraction for traffic incident detection using wavelet transform and linear discriminant analysis‖, Computer-Aided Civil and Infrastructure Engineering, Vol. 15, No. 4, pp. 241-250.
• Sattayhatewa, P., Ran, B. (1999): ―Arterial incident detection: applying CUSUM chart method‖, Traffic Engineering and Control, Vol. 40, No. 12, pp. 582-585.
• Sheu, J.-B., Ritchie, S.G. (1998): ―A new methodology for incident detection and characterization on surface streets‖, Transportation Research Part C, Vol. 6, No. 3, pp. 315- 335.
• Sethi, V., Bhandari, N., Koppelman, F.S., Schofer, J.L. (1995): ―Arterial incident detection using fixed detector and probe vehicle data‖, Transportation Research Part C, Vol. 3, No. 2, pp.99-112.
• Skabordanis, A., Petty, K., Varaiya, P., Bertini, R. (1998): ―Evaluation of the freeway service patrol (FSP) in Los Angeles‖, California PATH Research Report, UCB_ITS-PRR-98-31, University of California at Berkeley.
• Stamatiadis, C., Gartner, N. H., Winn, J., Bond, R. (1998): ―Evaluation of the Massachusetts motorist assistance program[CD-ROM]‖, Proceedings of the 77th Annual Meeting of Transportation Research Board, January, Washington, DC.
• Stephanedes, Y.J., Chassiakos, A.P., Michalopoulos, P.G. (1992): ―Comparative performance evaluation of incident detection algorithms‖, Transportation Research Record, No. 1360, TRB, National Research Council, pp. 50-57.
• T.C. Bayındırlık ve İskan Bakanlığı Karayolları Genel Müdürlüğü, Stratejik Plan 2006-2010, Ağustos 2005, Ankara.
• Thancanamootoo, S., Bell, M.G.H. (1998): ―Automatic detection of traffic incidents on a signal-controlled road network‖, Research Report No. 76, Transport Operations Research Group, University of Newcastle upon Tyne, UK.
• Türkiye İstatistik Kurumu Model Yıllarına Göre Motorlu Kara Taşıt Sayısı Raporu
• Türkiye İstatistik Kurumu Motorlu Kara Taşıtları İstatistikleri Haziran 2009 Raporu
• Vecdi Diker Çalışma Grubu, İstanbul'un ulaşım ve trafik sorunu - Üçüncü çevre yolu ve boğaz geçişi bildirisi Walters, C.H., Wiles, P.B., Cooner, S.A. (1999): ―Incident detection primarily by cellular phones—an evaluation of a system for Dallas, Texas‖, Preprint CD-ROM, the 78th TRB Annual Meeting, Transportation Research Board, National Research Council, Washington D.C., January. Weil, R., Wootton, J., Garcia-Ortiz, A. (1998): ―Traffic Incident Detection: Sensors and Algorithms‖, Mathematical Computer Modelling Vol 27, No. 9-11, pp. 257-291.
• Westman, M., Litjens, R., Linnartz, J.-P. (1996): ―Integration of probe vehicle and induction loop data—estimation of travel times and automatic incident detection‖, PATH Research Report UCB-ITS-PRR-96-13, Institute of Transportation Studies, University of California, Berkeley, CA. Willsky, A.S., Chow, E.Y., Gershwin, S.B., Greene, C.S., Houpt, P., Kurkjian, A.L. (1980): ―Dynamic model-based techniques for the detection of incidents on freeways‖, IEEE Transactions on Automatic Control, Vol. 25, No. 3, pp. 347-360.
• Yardım, M.S., Erel, A. (2003): ―Türkiye Ulaştırma Sistemi İçin Veri Gereksinimi‖, TMMOB Ulaştırma Politikaları Kongresi Bildiriler Kitabı, 171-181, Ankara, 16-17 Ekim.
• Yokota, T., Weiland, R.J.: ―ITS System Architectures for Developing Countries‖, ITS Technical Note-5, http://www.worldbank.org/html/fbd/transport/roads/its.htm.
• Zhang, K., Taylor, M.A.P. (2006): ―Towards universal freeway incident detection algorithms‖, Transportation Research Part C, Vol. 14 No.2, pp. 68-80.
• Zografos, K. G., Nathanail, T., Michalopoulos, P. (1993): ―Analytical framework for minimizing freeway-incident response time‖, Journal of Transportation Engineering 119, pp. 535-49.