Abstract

The recent emergence of automatic vehicle identification technology (AVI) for use in electronic toll collection has provided an opportunity to develop automatic incident detection (AID) methods that rely on individual vehicle travel time data instead of loop detector data. The performances of three AVI-based AID algorithms are examined. Travel time data for testing of the algorithms were obtained by simulating a 12-km section of the collector facility of Highway 401 in Toronto, Ontario, Canada. The performances of the three AVI-based AID algorithms are compared with the performance of a leading loop detector–based algorithm, which was independently tested with similar simulated data. The AID performance results indicate that AVI-based AID algorithms can provide incident detection performance similar to that of existing loop detector-based AID methods.

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