TY - JOUR
T1 - Integrated simulation platform for conventional, connected and automated driving
T2 - A design from cyber–physical systems perspective
AU - Jia, Dongyao
AU - Sun, Jie
AU - Sharma, Anshuman
AU - Zheng, Zuduo
AU - Liu, Bingyi
N1 - Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/3
Y1 - 2021/3
N2 - A comprehensive assessment of connected and automated driving is imperative before its large-scale deployment in reality, which can be economically and effectively implemented via a credible simulation platform. Nonetheless, the key components of traffic dynamics, vehicle modeling, and traffic environment are oversimplified in existing simulators. Current traffic simulators normally simplify the function of connected and autonomous vehicles by proposing incremental improvements to the conventional traffic flow modeling methods, which cannot reflect the characteristics of the realistic connected and autonomous vehicles. On the other hand, typical autonomous vehicle simulators only focus on individual function verification in some specific traffic scenarios, omitting the network-level evaluation by integrating both large-scale traffic networks and vehicle-to-anything (V2X) communication. This paper designs a comprehensive simulation platform for conventional, connected and automated driving from a transportation cyber–physical system perspective, which tightly combines the core components of V2X communication, traffic networks, and autonomous/conventional vehicle model. Specifically, three popular open-source simulators SUMO, Omnet++, and Webots are integrated and connected via the traffic control interface, and the whole simulation platform will be deployed in a Client/Server model. As the demonstration, two typical applications, traffic flow optimization and vehicle eco-driving, are implemented in the simulation platform. The proposed platform provides an ideal and credible testbed to explore the potential social/economic impact of connected and automated driving from the individual level to the large-scale network level.
AB - A comprehensive assessment of connected and automated driving is imperative before its large-scale deployment in reality, which can be economically and effectively implemented via a credible simulation platform. Nonetheless, the key components of traffic dynamics, vehicle modeling, and traffic environment are oversimplified in existing simulators. Current traffic simulators normally simplify the function of connected and autonomous vehicles by proposing incremental improvements to the conventional traffic flow modeling methods, which cannot reflect the characteristics of the realistic connected and autonomous vehicles. On the other hand, typical autonomous vehicle simulators only focus on individual function verification in some specific traffic scenarios, omitting the network-level evaluation by integrating both large-scale traffic networks and vehicle-to-anything (V2X) communication. This paper designs a comprehensive simulation platform for conventional, connected and automated driving from a transportation cyber–physical system perspective, which tightly combines the core components of V2X communication, traffic networks, and autonomous/conventional vehicle model. Specifically, three popular open-source simulators SUMO, Omnet++, and Webots are integrated and connected via the traffic control interface, and the whole simulation platform will be deployed in a Client/Server model. As the demonstration, two typical applications, traffic flow optimization and vehicle eco-driving, are implemented in the simulation platform. The proposed platform provides an ideal and credible testbed to explore the potential social/economic impact of connected and automated driving from the individual level to the large-scale network level.
KW - Connected and automated driving
KW - Cyber–physical system
KW - Mixed traffic flow
KW - Simulation platform
KW - V2X communication
UR - http://www.scopus.com/inward/record.url?scp=85099517493&partnerID=8YFLogxK
U2 - 10.1016/j.trc.2021.102984
DO - 10.1016/j.trc.2021.102984
M3 - Article
AN - SCOPUS:85099517493
SN - 0968-090X
VL - 124
JO - Transportation Research Part C: Emerging Technologies
JF - Transportation Research Part C: Emerging Technologies
M1 - 102984
ER -