Motorway incident detection using probe vehicles
Motorway incident detection using probe vehicles
Vehicles that collect data from a traffic stream of which they are part (i.e. probe vehicles) have been shown to provide reliable and cost-effective real-time travel information. This paper presents a probe-vehicle-based algorithm designed to detect incidents on motorways. The algorithm is based on a bivariate analysis model (BEAM) using two variables: the average travel times of probe vehicles, and the travel time differences between adjacent time intervals. The premise of the model is that link travel times increase more rapidly as a result of a change in capacity (i.e. when an incident occurs) than as a result of a change in demand. The statistical principles of bivariate analysis have been used to study the relationships between the two variables in incident and non-incident conditions. Four motorway road links with field data have been used to test the feasibility of the model with 99% and 99.9% coverage contours respectively. The model achieved an average incident detection rate of 89.5% with a false alarm rate of 0.71% using the 99% coverage contour. The average incident detection rate was 73.7% with a false alarm rate of 0.57% using the 99.9% coverage contour.
transport management, safety & hazards
11-15
Li, Y.
d53810d0-bc88-491d-b315-9b9273d7bf52
McDonald, M.
cd5b31ba-276b-41a5-879c-82bf6014db9f
1 February 2005
Li, Y.
d53810d0-bc88-491d-b315-9b9273d7bf52
McDonald, M.
cd5b31ba-276b-41a5-879c-82bf6014db9f
Li, Y. and McDonald, M.
(2005)
Motorway incident detection using probe vehicles.
Proceedings of the Institution of Civil Engineers - Transport, 158 (1), .
(doi:10.1680/tran.158.1.11.57825).
Abstract
Vehicles that collect data from a traffic stream of which they are part (i.e. probe vehicles) have been shown to provide reliable and cost-effective real-time travel information. This paper presents a probe-vehicle-based algorithm designed to detect incidents on motorways. The algorithm is based on a bivariate analysis model (BEAM) using two variables: the average travel times of probe vehicles, and the travel time differences between adjacent time intervals. The premise of the model is that link travel times increase more rapidly as a result of a change in capacity (i.e. when an incident occurs) than as a result of a change in demand. The statistical principles of bivariate analysis have been used to study the relationships between the two variables in incident and non-incident conditions. Four motorway road links with field data have been used to test the feasibility of the model with 99% and 99.9% coverage contours respectively. The model achieved an average incident detection rate of 89.5% with a false alarm rate of 0.71% using the 99% coverage contour. The average incident detection rate was 73.7% with a false alarm rate of 0.57% using the 99.9% coverage contour.
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Published date: 1 February 2005
Keywords:
transport management, safety & hazards
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Local EPrints ID: 53652
URI: http://eprints.soton.ac.uk/id/eprint/53652
ISSN: 0965-092X
PURE UUID: fa41baf4-70b1-4f3d-a214-36c9a8b69740
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Date deposited: 23 Jul 2008
Last modified: 15 Mar 2024 10:41
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Author:
Y. Li
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