Research Article
Low-Carbon Emission Driven Traffic Speed Optimization for Internet of Vehicles
@INPROCEEDINGS{10.1007/978-3-030-73429-9_3, author={Wenjie Chen and Zhende Xiao and Zou Siming}, title={Low-Carbon Emission Driven Traffic Speed Optimization for Internet of Vehicles}, proceedings={Edge Computing and IoT: Systems, Management and Security. First EAI International Conference, ICECI 2020, Virtual Event, November 6, 2020, Proceedings}, proceedings_a={ICECI}, year={2021}, month={7}, keywords={Internet of Vehicles Speed optimization CO emissions mitigation Traffic management}, doi={10.1007/978-3-030-73429-9_3} }- Wenjie Chen
Zhende Xiao
Zou Siming
Year: 2021
Low-Carbon Emission Driven Traffic Speed Optimization for Internet of Vehicles
ICECI
Springer
DOI: 10.1007/978-3-030-73429-9_3
Abstract
Climate change has become a worldwide concern. Reducing CO2 emission is a major challenge for road transportation sector and is of critical importance. This paper, after studying and analyzing the influence of speed on vehicle CO emission, proposes a recommended speed calculation scheme based on IoV to obtain vehicle speed and traffic signal phase information. In the recommended speed scenario, the vehicle is informed of the traffic phase information before arriving at the intersection and can set and optimize the current speed. This paper analyzes the three different status of traffic lights and studies the speed that should be adopted in each status. Under the proposed scheme, the recommended speed helps the driver to reach the destination with higher driving efficiency. The average wait time at red traffic lights is shorter than at speeds that are not recommended, resulting in reduced total travel time, higher uninterrupted pass rates, and decreased vehicle fuel consumption and CO emissions.
