The paper presents the results of an analytical study of rear-end collision-avoidance warning systems using the REAMACS program. The purpose of the exercise was to estimate the effectiveness of warning algorithms that utilize information about lead vehicle deceleration in their calculations and warn drivers when the headway to the lead vehicle falls below some minimum. REAMACS (Rear-End Accident Model And Countermeasure Simulation) generates rear-end collision situations in freeway traffic and models the effects of collision warning sytsems on rear-end crash rates. The model uses actual freeway traffic data and empirically-based analytical distributions for driver reaction time and lead car braking levels to generate the initial conditions that determine whether or not a crash occurs. Previously reported applications of the model indicate that collision warning has the potential to reduce the number of serious rear-end crashes in freeway traffic by as much as 60 %. The results suggest a significat advantage for warning algorithms using knowledge of lead vehicle deceleration, especially in more severe crashes. The addition of headway warnings also improves effectiveness, primarily in lower speed crashes, at the cost of an increase in the warning rate. Driver compliance with headway warnings is an issue.
Rear-end collision warning algoritms with headway warning and lead vehicle deceleration information
Auffahrunfall-Warnungsalgorithmus mit Abstandswarnung und Verzögerungsangaben über das vorausfahrende Fahrzeug
1995
6 Seiten, 4 Bilder, 1 Tabelle, 2 Quellen
Conference paper
English
Rear-End Collision-Warning Algorithms with Headway Warning and Lead Vehicle Deceleration Information
British Library Conference Proceedings | 1995
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