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KAZA-OLAY TESPİT ALGORİTMALARINA GENEL BAKIŞ

VIEW OF INCIDENT DETECTION ALGORITHMS

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Abstract (2. Language): 
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.
Abstract (Original Language): 
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.
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REFERENCES

References: 

Ahmed, M.S., Cook, A.R. (1977): ―Analysis of freeway traffic time-series data using BoxJenkins 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 in PATH, , February.
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.
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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.

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