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A Literature Review on Freeway Traffic Incidents and Their Impact on Traffic Operations

DOI: 10.4236/jtts.2019.94032, PP. 504-516

Keywords: Traffic Incidents, Freeway Incident Management, Impacts of Incidents, Operational Performance Measurement

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Abstract:

Congestion on the freeway is more frequent due to several traffic incidents, namely traffic accidents, debris on the road, vehicle breakdown, and collision with guardrails than any other incidents. These, in turn, affect the operational performance of the freeway by increasing queue length, volume, and density. Consequently, effective freeway management strategies can help to minimize these impacts. The study investigates and summarizes existing studies to identify the reasons for and effects of the traffic incidents. Attention is given to the available solutions of the freeway traffic incidents management. The ultimate goal of this study is to identify the gaps which are not yet addressed to improve the operational effectiveness of the freeway. This study was conducted through a comprehensive literature review of existing refereed publications, established standards, and formal guidelines. Literature was sought through the Transport Research International Documentation (TRID) database, IEEE Transactions database, and google scholar search engine. Research focusing on freeway traffic incidents is a growing concern in transportation operations, as transportation network performance depends on it. Due to the advancement of technology, emerging vehicle technologies like connected vehicles have the potential to address these problems affecting the US transportation system and revolutionize mobility in the future. The study can serve as a reference for the researchers that are involved in freeway traffic operations.

References

[1]  Skabardonis, A., Varaiya, P. and Petty, K. (2003) Measuring Recurrent and Nonrecurrent Traffic Congestion. Transportation Research Record: Journal of the Transportation Research Board, 1856, 118-124.
https://doi.org/10.3141/1856-12
[2]  Sullivan, E.C. (1997) New Model for Predicting Freeway Incidents and Incident Delays. Journal of Transportation Engineering, 123, 267-275.
https://doi.org/10.1061/(ASCE)0733-947X(1997)123:4(267)
[3]  Zhang, H. and Khattak, A. (2010) What Is the Role of Multiple Secondary Incidents in Traffic Operations? Journal of Transportation Engineering, 136, 986-997.
https://doi.org/10.1061/(ASCE)TE.1943-5436.0000164
[4]  Owens, N., Armstrong, A., Sullivan, P., Mitchell, C., Newton, D., Brewster, R. and Trego, T. (2010) Traffic Incident Management Handbook (No. FHWA-HOP-10-013).
http://www.ops.fhwa.dot.gov/eto_tim_pse/publications/timhandbook/tim_handbook.pdf
[5]  Hall, R.W. (1993) Non-Recurrent Congestion: How Big Is the Problem? Are Traveler Information Systems the Solution? Transportation Research Part C: Emerging Technologies, 1, 89-103.
https://doi.org/10.1016/0968-090X(93)90022-8
[6]  Systematics, C. (2005) Traffic Congestion and Reliability: Trends and Advanced Strategies for Congestion Mitigation. Final Report, Texas Transportation Institute, College Station.
http://ops.fhwa.dot.gov/congestion_report_04/index.htm
[7]  Manual on Uniform Traffic Control Devices (MUTCDs) (2009) Federal Highway Administration (FHWA).
[8]  Farradyne, P. (2000) Traffic Incident Management Handbook. Prepared for Federal Highway Administration, Office of Travel Management.
[9]  Schrank, D., Eisele, B., Lomax, T. and Bak, J. (2015) 2015 Urban Mobility Scorecard.
[10]  Thomas, K. and Dia, H. (2006) Comparative Evaluation of Freeway Incident Detection Models Using Field Data. IEE Proceedings of Intelligent Transport Systems, 153, 230-241.
https://doi.org/10.1049/ip-its:20055015
[11]  Payne, H.J. and Tignor, S.C. (1978) Freeway Incident-Detection Algorithms Based on Decision Trees with States. Transportation Research Record, 682, 30-37.
[12]  Stephanedes, Y.J. and Chassiakos, A.P. (1993) Application of Filtering Techniques for Incident Detection. Journal of Transportation Engineering, 119, 13-26.
https://doi.org/10.1061/(ASCE)0733-947X(1993)119:1(13)
[13]  Levin, M. and Krause, G.M. (1978) Incident Detection: A Bayesian Approach. Transportation Research Record, 682, 52-58.
[14]  Zhang, K. and Taylor, M.A. (2005) Towards Transferable Incident Detection Algorithms. Journal of the Eastern Asia Society for Transportation Studies, 6, 2263-2274.
[15]  Willsky, A., Chow, E., Gershwin, S., Greene, C., Houpt, P. and Kurkjian, A. (1980) Dynamic Model-Based Techniques for the Detection of Incidents on Freeways. IEEE Transactions on Automatic Control, 25, 347-360.
https://doi.org/10.1109/TAC.1980.1102392
[16]  Ahmed, S.A. (1983) Stochastic Processes in Freeway Traffic Part I. Robust Prediction Models. Traffic Engineering & Control, 24, HS-035775.
[17]  Whitson, R.H., Burr, J.H., Drew, D.R. and McCasland, W.R. (1969) Real-Time Evaluation of Freeway Quality of Traffic Service.
[18]  Persaud, B.N., Hall, F.L. and Hall, L.M. (1990) Congestion Identification Aspects of the McMaster Incident Detection Algorithm. Transportation Research Record, 1287, 167-175.
[19]  Ghosh-Dastidar, S. and Adeli, H. (2003) Wavelet-Clustering-Neural Network Model for Freeway Incident Detection. Computer-Aided Civil and Infrastructure Engineering, 18, 325-338.
https://doi.org/10.1111/1467-8667.t01-1-00311
[20]  Karim, A. and Adeli, H. (2003) Fast Automatic Incident Detection on Urban and Rural Freeways Using Wavelet Energy Algorithm. Journal of Transportation Engineering, 129, 57-68.
https://doi.org/10.1061/(ASCE)0733-947X(2003)129:1(57)
[21]  Adeli, H. and Karim, A. (2000) Fuzzy-Wavelet RBFNN Model for Freeway Incident Detection. Journal of Transportation Engineering, 126, 464-471.
https://doi.org/10.1061/(ASCE)0733-947X(2000)126:6(464)
[22]  Jin, X., Srinivasan, D. and Cheu, R.L. (2001) Classification of Freeway Traffic Patterns for Incident Detection Using Constructive Probabilistic Neural Networks. IEEE Transactions on Neural Networks, 12, 1173-1187.
https://doi.org/10.1109/72.950145
[23]  Sheu, J.-B. (2002) A Fuzzy Clustering-Based Approach to Automatic Freeway Incident Detection and Characterization. Fuzzy Sets and Systems, 128, 377-388.
https://doi.org/10.1016/S0165-0114(01)00141-5
[24]  Ritchie, S.G. and Cheu, R.L. (1993) Simulation of Freeway Incident Detection Using Artificial Neural Networks. Transportation Research Part C: Emerging Technologies, 1, 203-217.
https://doi.org/10.1016/S0968-090X(13)80001-0
[25]  Tavassoli Hojati, A., Ferreira, L., Washington, S., Charles, P. and Shobeirinejad, A. (2016) Modelling the Impact of Traffic Incidents on Travel Time Reliability. Transportation Research Part C: Emerging Technologies, 65, 49-60.
https://doi.org/10.1016/j.trc.2015.11.017
[26]  Chen, C., Skabardonis, A. and Varaiya, P. (2003) Travel-Time Reliability as a Measure of Service. Transportation Research Record: Journal of the Transportation Research Board, 1855, 74-79.
https://doi.org/10.3141/1855-09
[27]  Park, S., Rakha, H. and Guo, F. (2011) Multi-State Travel Time Reliability Model: Impact of Incidents on Travel Time Reliability. 14th International IEEE Conference on Intelligent Transportation Systems, Washington DC, 5-7 October 2011, 2106-2111.
https://doi.org/10.1109/ITSC.2011.6082874
[28]  Wright, B., Zou, Y. and Wang, Y. (2015) Impact of Traffic Incidents on Reliability of Freeway Travel Times. Transportation Research Record: Journal of the Transportation Research Board, 2484, 90-98.
https://doi.org/10.3141/2484-10
[29]  Skabardonis, A., Petty, K., Bertini, R., Varaiya, P., Noeimi, H. and Rydzewski, D. (1997) I-880 Field Experiment: Analysis of Incident Data. Transportation Research Record: Journal of the Transportation Research Board, 1603, 72-79.
https://doi.org/10.3141/1603-10
[30]  Hojati, A.T., Ferreira, L., Charles, P. and Shobeirinejad, A. (2013) Quantifying the Impacts of Traffic Incidents on Urban Freeway Speeds. 36th Australasian Transport Research Forum, Brisbane, 2-3 October 2013.
[31]  Qin, L. and Smith, B.L. (2001) Characterization of Accident Capacity Reduction (No. STL-2001-02). University of Virginia, Charlottesville.
[32]  Prevedouros, P., Halkias, B., Papandreou, K. and Kopelias, P. (2008) Freeway Incidents in the United States, United Kingdom, and Attica Tollway, Greece: Characteristics, Available Capacity, and Models. Transportation Research Record: Journal of the Transportation Research Board, 2047, 57-65.
https://doi.org/10.3141/2047-07
[33]  Chimba, D., Kutela, B., Ogletree, G., Horne, F. and Tugwell, M. (2013) Impact of Abandoned and Disabled Vehicles on Freeway Incident Duration. Journal of Transportation Engineering, 140, Article ID: 04013013.
https://doi.org/10.1061/(ASCE)TE.1943-5436.0000635
[34]  Thomas, S. and Jacko, R. (2007) Stochastic Model for Estimating Impact of Highway Incidents on Air Pollution and Traffic Delay. Transportation Research Record: Journal of the Transportation Research Board, 2011, 107-115.
https://doi.org/10.3141/2011-12

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