This study creates a sequential approach to represent the dynamic update forecast of accident duration. This procedure includes two Artificial Neural Network-based models. Model A is used to forecast the duration time at the instant of accident notification while Model B provides multi-period updates of duration time after the moment of accident notification. These two models together provide a sequential forecast of accident duration from the accident notification to the accident site clearance. With these two models, the estimated duration time can be provided by plugging in relevant traffic data as soon as an incident is reported. This study shows very promising practical applicability of the proposed models in the Intelligent Transportation Systems context.
|Title of host publication||Road Traffic|
|Subtitle of host publication||Safety, Modeling and Impacts|
|Publisher||Nova Science Publishers, Inc.|
|Number of pages||19|
|Publication status||Published - 2009 Jan 1|
All Science Journal Classification (ASJC) codes