One of the expected features for the automated vehicles in the near future is CooperativeAdaptive Cruise Control (CACC) systems. CACC systems are one of the main applications forthe connected vehicles initiative of the USDOT for providing better connectivity, safety andefficient mobility in transportation. It is expected in the future that many (or most) of the vehicleswill be fully automated; thus the movements of these vehicles can be optimized. Accordingly,this paper presents a new tool for optimizing the movements of autonomous vehicles throughintersections: iCACC (intersection management using CACC). The iCACC controller controlsvehicle trajectories entering an intersection to avoid collisions while minimizing the intersectiondelay. In order to validate the proposed algorithm, four intersection control scenarios wereanalyzed, namely: a traffic signal, an all-way stop control (AWSC), a roundabout, and the iCACCcontroller, considering different traffic demand levels ranging from a volume-to-capacity ratio of0.27 to 0.91. Two measures of effectiveness were considered: average vehicle delay and fuelconsumption. The simulated results showed savings in delay and fuel consumption of the order of90 and 45 percent, respectively compared to AWSC and traffic signal control. Delays for theroundabout and the iCACC controller were comparable. The simulation results showed that fuelconsumption for the iCACC controller was, on average, 33%, 45% and 11% lower than the fuelconsumption for the traffic signal control, AWSC and roundabout scenarios, respectively.
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