no code implementations • 7 Dec 2021 • Yongkang Liu, Ziran Wang, Kyungtae Han, Zhenyu Shou, Prashant Tiwari, John H. L. Hansen
To advance the development of visual guidance systems, we introduce a novel vision-cloud data fusion methodology, integrating camera image and Digital Twin information from the cloud to help intelligent vehicles make better decisions.
no code implementations • 22 Nov 2020 • Zhenyu Shou, Xu Chen, Yongjie Fu, Xuan Di
We show that the routing behavior of intelligent agents is shown to converge to the classical notion of predictive dynamic user equilibrium (DUE) when traffic environments are simulated using dynamic loading models (DNL).
no code implementations • 8 Jul 2020 • Yongkang Liu, Ziran Wang, Kyungtae Han, Zhenyu Shou, Prashant Tiwari, John H. L. Hansen
With the rapid development of intelligent vehicles and Advanced Driving Assistance Systems (ADAS), a mixed level of human driver engagements is involved in the transportation system.
no code implementations • 23 Jun 2020 • Zhenyu Shou, Ziran Wang, Kyungtae Han, Yongkang Liu, Prashant Tiwari, Xuan Di
Behavior prediction plays an essential role in both autonomous driving systems and Advanced Driver Assistance Systems (ADAS), since it enhances vehicle's awareness of the imminent hazards in the surrounding environment.
no code implementations • 17 Feb 2020 • Zhenyu Shou, Xuan Di
In the second case study, an optimal toll charge of $5. 1 is solved using BO, which improves the objective of city planners by 7. 9%, compared to that without any toll charge.
no code implementations • 23 May 2019 • Zhenyu Shou, Xuan Di, Jieping Ye, Hongtu Zhu, Hua Zhang, Robert Hampshire
Vacant taxi drivers' passenger seeking process in a road network generates additional vehicle miles traveled, adding congestion and pollution into the road network and the environment.