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This study examines the impacts of cooperative adaptive cruise control (CACC) and cooperative lane changing (CLC) on the delay and the riding comfort in autonomous car–autonomous truck (AC–AT) mixed traffic at a freeway merging area. For this task, AC–AT mixed traffic on a 5.25 km section of freeway was analyzed using the Aimsun Next microscopic traffic simulation. The effects of different CACC parameters and CLC on the average speed and acceleration distributions as the measures of delay and riding comfort, respectively, were evaluated. It was found that (1) lower sensitivity to the lead vehicle reduced the merging time, (2) shorter time gaps between autonomous vehicles and between platoons decreased the delay, and (3) longer time gaps reduced the delay at higher percentage of ATs. These results demonstrate that the delay of AC–AT mixed traffic at a freeway merging area can be reduced and riding comfort can be increased by adjusting CACC parameters. [ABSTRACT FROM AUTHOR]

This study develops a differential variable speed limit (DVSL) which assigns different speed limits for car and truck, and varies speed limits based on traffic conditions. The proposed DVSL algorithm changes speed limits in real time based on truck percentage and occupancy immediately upstream of the ramp and the average speed of the control road sections upstream of the ramp. DVSL algorithm also considers spatial coordination of speeds, which gradually changes the speed limits in successive road sections upstreamof the ramp when the severe congestion occurs. The study tested the impacts of DVSL and three other speed limit strategies on delay and safety for a section of the Gardiner Expressway in Toronto, Canada using the VISSIM traffic simulation model. The other strategies are 1) uniform speed limit (USL), 2) differential speed limit for car and truck (DSL), and 3) USL & DSL (U&D) e i.e., USL at low truck percentage and DSL at high truck percentage. It was found that DVSL showed the lowest delays for both car and truck among the four strategies. This is mainly because DVSL increased the spacing between vehicles in the right lane upstream of the on-ramp and facilitated vehicles' merging into the mainline freeway. It was also found that DVSL showed the lowest likelihood of rear-end crash between the lead and following vehicles among the four strategies. This study demonstrates that the proposed DVSL algorithm can better control car and truck speeds to reduce delay and improve safety of car-truck mixed traffic flow on freeways. [ABSTRACT FROM AUTHOR]

This paper makes use of a probabilistic model that predicts the likelihood of crashes (crash potential) on freeways on the basis of traffic flow conditions, in real-time crash prevention. The model was developed using incident logs and loop detector data collected over a 13-month period on the Gardiner Expressway in Toronto. Previous work suggested that an increase in levels of traffic turbulence generally yields high crash potential. Traffic turbulence was defined in terms of a series of crash precursors that represent traffic conditions that were present prior to crash occurrence. To apply the model in crash prevention, the link needs to be established between crash potential and real-time safety intervention. The objective of this paper is to explore this link for different thresholds of crash potential. The paper discusses the guidelines for evaluating the safety benefit of one crash prevention strategy (variable speed limits) and suggests the risk-based evaluation framework for real-time traffic control. [ABSTRACT FROM AUTHOR]