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A Probabilistic Approach to Driver Assistance for Delay Reduction at Congested Highway Lane Drops

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Document pages: 18 pages

Abstract: This paper proposes an onboard advance warning system based on aprobabilistic prediction model that advises vehicles on when to change lanesfor an upcoming lane drop. Using several traffic- and driver-related parameterssuch as the distribution of inter-vehicle headway distances, the predictionmodel calculates the likelihood of utilizing one or multiple lane changes tosuccessfully reach a target position on the road. When approaching a lane drop,the onboard system projects current vehicle conditions into the future and usesthe model to continuously estimate the success probability of changing lanesbefore reaching the lane-end, and advises the driver or autonomous vehicle tostart a lane changing maneuver when that probability drops below a certainthreshold. In a simulation case study, the proposed system was used on asegment of the I-81 interstate highway with two lane drops - transitioning fromfour lanes to two lanes - to advise vehicles on avoiding the lane drops. Theresults indicate that the proposed system can reduce average delay by up to 50 and maximum delay by up to 33 , depending on traffic flow and the ratio ofvehicles equipped with the advance warning system.

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