Abstract
An effective transportation system is part of the core of a modern smart city to support various human activities. Recent developments of Connected Autonomous Vehicles (CAVs) have great impact on the automotive industry. Due to its numerous advantages, CAV is expected to get popular in the near future. While most studies focus on standalone CAV technologies, there is much potential on collective CAV control. With the connectivity and automation of CAVs, we can employ Dynamic Lane Reversal (DLR) to enable automatic lane reversal for improving the traffic. We can optimize the travel schedules of CAVs based on DLR for performance enhancement. In this paper, we proposed the Dynamic Lane Reversal-Traffic Scheduling Management (DLR- TSM) Scheme for CAVs. It collects the travel requests from the CAVs and determines their optimal schedules and routes on dynamically reversible lanes. We formulate the routing and scheduling problem as an integer linear program. We evaluate the performance of the scheme with real-world transportation data. The simulation results show that DLR-TSM can significantly improve the travel times of CAVs.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
