Active lane management for intelligent connected vehicles in weaving areas of urban expressway

Purpose–This paper aims to use activefine lane management methods to solve the problem of congestion in a weaving area and provide theoretical and technical support for traffic control under the environment of intelligent connected vehicles(ICVs)in the future.Design/methodology/approach–By analyzing the traffic capacities and traffic behaviors of domestic and foreign weaving areas and combining them withfield investigation,the paper proposes the active andfine lane management methods for ICVs to optimal driving behavior in a weaving area.The VISSIM simulation of trafficflow vehicle driving behavior in weaving areas of urban expressways was performed using research data.The influence of lane-changing in advance on the weaving area was evaluated and a conflict avoidance area was established in the weaving area.The activefine lane management methods applied to a weaving area were verified for different scenarios.Findings–The results of the study indicate that ICVs complete their lane changes before they reach a weaving area,their time in the weaving area does not exceed the specified time and the delay of vehicles that pass through the weaving area decreases.Originality/value–Based on the vehicle group behavior,this paper conducts a simulation study on the active traffic management control-oriented to ICVs.The research results can optimize the management of lanes,improve the traffic capacity of a weaving area and mitigate traffic congestion on expressways.

Evaluation of fog warning system on driving under heavy fog condition based on driving simulator

Purpose–Heavy fog results in low visibility,which increases the probability and severity of traffic crashes,and fog warning system is conducive to the reduction of crashes by conveying warning messages to drivers.This paper aims at exploring the effects of dynamic message sign(DMS)of fog warning system on driver performance.Design/methodology/approach–First,a testing platform was established based on driving simulator and driver performance data under DMS were collected.The experiment route was consisted of three different zones(i.e.warning zone,transition zone and heavy fog zone),and mean speed,mean acceleration,mean jerk in the whole zone,ending speed in the warning zone and transition zone,maximum deceleration rate and mean speed reduction proportion in the transition zone and heavy fog zone were selected.Next,the one-way analysis of variance was applied to test the significant difference between the metrics.Besides,drivers’subjective perception was also considered.Findings–The results indicated that DMS is beneficial to reduce speed before drivers enter the heavy fog zone.Besides,when drivers enter a heavy fog zone,DMS can reduce the tension of drivers and make drivers operate more smoothly.Originality/value–This paper provides a comprehensive approach for evaluating the effectiveness of the warning system in adverse conditions based on the driving simulation test platform.The method can be extended to the evaluation of vehicle-to-infrastructure technology in other special scenarios.