Lane‐changing and freeway capacity: A Bayesian inference stochastic model

Abstract

This article presents a new stochastic computational model for determining freeway capacity reduction as a result of lane-changing activity. The probability density function for the maximum flow that can be sustained on a freeway for a given lanechanging level is obtained. The results can be used to support freeway management strategies aiming to mitigate the negative consequences of lane-changing in freeway capacity. A pilot test using empirical data obtained from the B-23 freeway accessing the city of Barcelona proves the validity of the modeling approach.

Improving traffic efficiency at merge bottleneck: a combined variable speed limit and logic rule-based lane change control approach

“…Traffic control measures are therefore required to improve traffic efficiency and reduce the risk of traffic accidents in the bottleneck. The emergence of congested queues upstream of the bottleneck is accompanied by a capacity drop problem, which are mainly due to vehicle lane changing and bounded acceleration [1] .…”

Adaptive approximate Bayesian computation by subset simulation for structural model calibration

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