Traffic congestion causes detrimental effects on economy and society in terms of travel time delay, increased vehicle collision risk and increased air pollution. To tackle that, new intelligent transportation systems are being developed. One of these emerging technologies comprise automated driving systems. Adaptive Cruise Control (ACC), enabling a vehicle to follow its leader automatically, is an automated driving system which has been available in the vehicle market. Literature shows that traffic flow performance may not significantly benefit from ACC due to traffic instability and large headways. As an extension of ACC, Cooperative ACC is designed to improve traffic stability and throughput by using Vehicle-to-Vehicle (V2V) communication. Thanks to the anticipation of the downstream traffic, a short following gap can be realized by CACC which is highly expected to considerably increase road capacities. Before CACC vehicle is allowed and promoted in the market, it is crucial for policy makers and road operators to gain insights into the traffic flow impacts of CACC systems. Existing studies show that CACC can increase traffic throughput at high vehicle market penetration. However, the realistic effects of CACC on traffic flow have not been adequately revealed because the behaviour of CACC vehicles has not been realistically modelled. The multiple CACC driving modes, the degraded operation to ACC and the human driver take-over control when it is out of the CACC operational design domain, have not yet been explicitly included in existing CACC impact studies. A scientific gap prevails in modelling the complex CACC behaviour and investigating its actual influence on traffic flow especially at realistic networks with a single bottleneck and interacting bottlenecks.@en

Cooperative Adaptive Cruise Control (CACC) systems have the potential to increase roadway capacity and mitigate traffic congestion thanks to the short following distance enabled by inter-vehicle communication. However, due to limitations in acceleration and deceleration capabilities of CACC systems, deactivation and switch to ACC or human-driven mode will take place when conditions are outside the operational design domain. Given the lack of elaborate models on this interaction, existing CACC traffic flow models have not yet been able to reproduce realistic CACC vehicle behaviour and pay little attention to the influence of system deactivation on traffic flow at bottlenecks. This study aims to gain insights into the influence of CACC on highway operations at merging bottlenecks by using a realistic CACC model that captures driver-system interactions and string length limits. We conduct systematic traffic simulations for various CACC market penetration rates (MPR) to derive free-flow capacity and queue discharge rate of the merging section and compare these to the capacity of a homogeneous pipeline section. The results show that an increased CACC MPR can indeed increase the roadway capacity. However, the resulting capacity in the merging bottleneck is much lower than the pipeline capacity and capacity drop persists in bottleneck scenarios at all CACC MPR levels. It is also found that CACC increases flow heterogeneity due to the switch among different operation modes. A microscopic investigation of the CACC operational mode and trajectories reveals a close relation between CACC deactivation, traffic congestion and flow heterogeneity.@en

Cooperative Adaptive Cruise Control (CACC) systems can increase roadway capacity, but the benefits are marginal at low market penetration rates (MPRs). Thus, a CACC dedicated lane is considered to group CACC vehicles for efficient traffic stream. Concepts of converting existing High Occupancy Vehicle (HOV) lanes into CACC lanes emerge, which leverages the infrastructural facilities and experience with HOV lanes. However, it is unclear to which extent changing HOV lanes to CACC lanes can influence freeway operations. This study examines the traffic flow impacts of converting HOV lanes into CACC lanes regarding CACC MPRs on a complex freeway corridor with multiple interacting bottlenecks in California. A simulation model capable of reproducing flow characteristics with HOV lane and CACC systems is employed for the assessment. Special attention is paid to macroscopic congestion patterns, CACC lane utilization, travel time reliability and CACC operation characteristics. The results show that converting to CACC lanes at low MPRs ( % 1 )30 can exacerbate congestion in general purpose lanes, whereas at mediate CACC MPRs (40%–50%) the congestion is drastically alleviated due to a large share of traffic carried by CACC lanes.@en

Adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC) are important technologies for the achievement of vehicle automation, and their effect on traffic systems generally is evaluated with microscopic traffic simulations. A successful simulation requires realistic vehicle behavior and minimal vehicle collisions. However, most existing ACC-CACC simulation studies used simplified models that were not based on real vehicle response. The studies rarely addressed collision avoidance in the simulation. The study presented in this paper developed a realistic and collision-free car-following model for ACC-CACC vehicles. A multiregime model combining a realistic ACC-CACC system with driver intervention for vehicle longitudinal motions is proposed. This model assumes that a human driver resumes vehicle control either according to his or her assessment or after a collision warning asks the driver to take over. The proposed model was tested in a wide range of scenarios to explore model performance and collision possibilities. The testing scenarios included three regular scenarios of stop-and-go, approaching, and cut-out maneuvers, as well as two extreme safetyconcerned maneuvers of hard brake and cut-in. The simulation results show that the proposed model is collision free in the full-speed-range operation with leader accelerations within -1 to 1 m/s2 and in approaching and cut-out scenarios. Those results indicate that the proposed ACC-CACC car-following model can produce realistic vehicle response without causing vehicle collisions in regular scenarios for vehicle string operations.@en

Realistic microscopic traffic simulation is essential for prospective evaluation of the potential impacts of new traffic control strategies. Freeway corridors with interacting bottlenecks and dedicated lanes generate complex traffic flow phenomena and congestion patterns, which are difficult to reproduce with existing microscopic simulation models. This paper discusses two alternative driving behavior models that are capable of modeling freeways with multiple bottlenecks and dedicated lanes over an extended period with varying demand levels. The models have been calibrated using archived data from a complicated 13-mile long section of the northbound SR99 freeway near Sacramento, California, for an 8-hour time period in which the traffic fluctuated from free-flow to congested conditions. The corridor includes multiple bottlenecks, multiple entry and exit ramps, and an HOV lane. Calibration results show extremely good agreement between field data and model predictions. The models have been cross-validated and produced similar macroscopic traffic performance. The main behavior that should be captured for successful modeling of such a complex corridor includes the anticipative and cooperative driver behavior near merges, lane preference in presence of dedicated lanes, and variations in desired headway along the corridor.@en