Energy Consumption Optimization of Connected and Autonomous Vehicles Based on Cooperative Perception in Ramp Overflow Scene

Abstract

The congestion caused by ramp overflow has an essential impact on the energy consumption of autonomous vehicles. It is urgent to solve the energy waste of ramp overflow on connected and autonomous vehicles and improve the energy utilization rate. Aiming at the traffic congestion caused by ramp overflow, this paper obtains the data of autonomous vehicles and traffic flow based on vehicle road cooperative perception, analyzes the impact mechanism of vehicle energy consumption, and summarizes the energy consumption modes of autonomous vehicles into three categories. Second, an energy consumption evaluation framework is proposed based on the CSANS strategy. This strategy can make up for the deficiency of constructing neighborhoods within European distance, find important influencing variables on connected and autonomous vehicles’ energy consumption, and accurately capture the manifold characteristics of energy consumption data. Finally, flow control is carried out from the macro perspective of traffic engineering to optimize ramp overflow’s impact on autonomous vehicles’ energy consumption. Through multiple groups of experiments, it has been found that it can effectively reduce the energy consumption of autonomous vehicles.