2007PROCEEDINGS OF THE 14TH WORLD CONGRESS ON INTELLIGENT TRANSPORT SYSTEMS (ITS), HELD BEIJING, OCTOBER 2007Requires access

Summary of freeway traffic incident duration prediction algorithms

Wei Wang, Shunxin Yang

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Abstract

Duration prediction is one of the most important steps of the overall incident management process. The real-time decisions regarding the resources needed to clear and manage the incident and information given to travelersall depend on the knowledge of incident duration. An accurate and reliable estimation of incident duration contributes a lot to the efficiency of incident management operation and the Advanced Traveler Information System (ATIS). This paper reviews several major researches on incident data analysis and duration to summarize the methodologies and conclusions in each study. And the objective of this paper is to integrate the previous models to develop a forecasting model that can predict the duration of Chinese freeway incident, which can facilitate incident management and support traveler decisions. For the covering abstract see ITRD E140665.

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What this paper is about

Duration prediction is one of the most important steps of the overall incident management process. The real-time decisions regarding the resources needed to clear and manage the incident and information given to travelersall depend on the knowledge of incident duration. An accurate and reliable estimation of incident duration contributes a lot to the efficiency of incident management operation and the Advanced Traveler Information System (ATIS). This paper reviews several major researches on incident data analysis and duration to summarize the methodologies and conclusions in each study. And the objective of this paper is to integrate the previous models to develop a forecasting model that can predict the duration of Chinese freeway incident, which can facilitate incident management and support traveler decisions. For the covering abstract see ITRD E140665.

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Available abstract

Duration prediction is one of the most important steps of the overall incident management process. The real-time decisions regarding the resources needed to clear and manage the incident and information given to travelersall depend on the knowledge of incident duration. An accurate and reliable estimation of incident duration contributes a lot to the efficiency of incident management operation and the Advanced Traveler Information System (ATIS). This paper reviews several major researches on incident data analysis and duration to summarize the methodologies and conclusions in each study. And the objective of this paper is to integrate the previous models to develop a forecasting model that can predict the duration of Chinese freeway incident, which can facilitate incident management and support traveler decisions. For the covering abstract see ITRD E140665.

Key concepts: Duration (music), Incident management, Computer science, Process (computing), Operations research, Incident report, Transport engineering, Data mining

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