A real-time optimal cooperative lane change strategy via V2V communication

Safety, which is in danger by careless maneuvers, is the most significant aspect of driving due to the health of passengers. The lane-changing procedure (LCP) could result in an accident provided that the driver miscalculates other vehicle positions and velocities. Consequently, automation and vehicle-to-vehicle (V2V) communication, which is a way of exchanging information between cars, have become increasingly popular owing to improving safety. Besides, real-time implementation of a fast strategy dealing with such an amount of information seems to be essential in a high-speed maneuver. This article presents a novel approach to complete the process considering optimality and safety without a huge volume of computation. This means that a constrained-optimization problem (COP) is examined to find datasets and discover simpler correlations that are effortless to implement in the real world. Ultimately, the dataset is incorporated with a model predictive controller and the effectiveness of the strategy is validated in the Siemens PreScan (R) platform. Moreover, the results show that the presented method is effective for a simple, safe, comfortable, and efficient lane-changing maneuver.