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