Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/28912
Title: Incident detection based on short-term travel time forecasting
Authors: Lam, WHK 
Tam, ML
Sumalee, A
Li, CL 
Chen, W 
Kwok, SK
Li, Z 
Ngai, EWT 
Issue Date: 2008
Source: Proceedings of the 13th International Conference of Hong Kong Society for Transportation Studies: Transportation and Management Science, 2008, p. 83-92 How to cite?
Abstract: Prediction of short-term future traffic condition is an important element for route guidance and incident management systems. In this paper, a solution algorithm is proposed for short-term travel time forecasting in congested urban roads of Hong Kong. The travel times in the next 5-minute interval are predicted by using the historical travel time estimates together with their updated temporal variance-covariance relationships. The territory-wide historical travel time database is generated by the real-time travel information system (RTIS) using the automatic vehicle identification data available in Hong Kong. Based on the travel time forecasts and the RTIS travel time estimates, traffic incident can be detected by comparing their differences on the road section before and after the incident. Case studies are presented to evaluate the performance of the proposed algorithms for short-term travel time prediction and incident detection.
Description: 13th International Conference of Hong Kong Society for Transportation Studies: Transportation and Management Science, Kowloon, 13-15 December 2008
URI: http://hdl.handle.net/10397/28912
ISBN: 9789889884734
Appears in Collections:Conference Paper

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