Open AccessSimulation study on the effect of automated driving in a road network environment
Author(s) -
Wang Qi,
Li Li,
Hou Dezao,
Li Zhiheng,
Hu Jianming
Publication year - 2020
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2019.0395
Subject(s) - automation , transport engineering , workload , hotspot (geology) , floating car data , traffic flow (computer networking) , cruise control , computer science , traffic bottleneck , traffic optimization , engineering , traffic congestion , control (management) , computer network , artificial intelligence , mechanical engineering , geophysics , geology , operating system
Automated driving, which is considered to be able to reduce driving workload, enhance driving safety and improve traffic efficiency, has become a research hotspot in recent years. It is believed that traffic flow will consist of manual vehicles and automated vehicles at different automation levels in the near future. Researchers have carried out many studies on mixed traffic; most of them focus on the highway scenario. However, the majority of traffic occurs in urban/suburban road networks, which contains many different scenarios, such as expressways, merging/diverging areas, signalised intersections, trunk roads, branch roads, etc. To evaluate the effect of automated driving in a more realistic way, the authors first take adaptive cruise control (ACC) and cooperative ACC as representatives of automated driving. Then, the authors make simulations at the road network level and investigate macroscopic fundamental diagram in different scenarios. Results show that compared to a highway, the improvement of traffic flow is significantly limited in the road network.