학술논문

Effect of Number of Lanes on Traffic Characteristics of Reinforcement Learning Based Autonomous Driving
Document Type
Periodical
Source
IEEE Access Access, IEEE. 11:80199-80206 2023
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Road transportation
Autonomous vehicles
Road traffic
Q-learning
Optimization
Task analysis
Behavioral sciences
Reinforcement learning
Lane detection
Traffic control
Number of highway lanes
autonomous vehicles
reinforcement learning
traffic characteristics
Language
ISSN
2169-3536
Abstract
Traffic characteristics such as signalized intersections and high vehicle density combined with low vehicle speeds account for 12-55% increase in commute time. Increasing the number of lanes in the highway infrastructure can help increase the highway capacity and consequently reduce the associated commute delay. However, due to human-related features such as driver behavior and vehicle interaction as well as induced demand, it is recommended to limit the number of highway lanes to four. Recently, in view of the rising discussion regarding the deployment of Autonomous Vehicles (AVs), it is important to study the effect of the number of highway lanes on traffic characteristics with respect to AVs. This will provide insights into the full potential of AVs in terms of reducing commute time as well as provide crucial insights into the design of future road networks. Therefore, in this study, RL-based AV frameworks are developed to investigate the effect of the number of highway lanes on traffic characteristics. Specifically, we study the effect of the number of lanes on traffic characteristics in terms of travel speed, collision, and driving on the right-most lane. Results with two well-known RL-based AV frameworks simulated on highways with lanes ranging from 2 to 8 and increasing vehicle count respectively show improved traffic characteristics as the number of lanes increases. However, improvement depends on the RL algorithm employed.