A probabilistic approach to driver assistance for delay reduction at congested highway lane drops

This paper proposes an onboard advance warning system based on a probabilistic prediction model that advises vehicles when to change lanes for upcoming lane drop. Using several traffic- and driver-related parameters such as the distribution of inter-vehicle headway distances, calculates likelihood utilizing one or multiple changes successfully reach target position road. When approaching drop, projects current vehicle conditions into future uses continuously estimate success probability changing before reaching lane-end, driver autonomous start maneuver drops below certain threshold. In simulation case study, proposed was used segment I-81 interstate highway with two – transitioning from four advise avoiding drops. The results indicate can reduce average delay by up 50% maximum 33%, depending traffic flow ratio equipped system.