Jian Gao
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Jian Gao has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Jin Tian
School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China
1 shared publication - Li Gong
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
1 shared publication - Neng Wang
School of Management Science and Real Estate, Chongqing University, Chongqing 400045, China
1 shared publication - Yujin Zhang
Shanghai University of Engineering Science
1 shared publication Zhilin Gao
Changjiang Geotechnical Engineering Co., Ltd., Wuhan
1 shared publication
Latest Publications
- Open Access
- 21 April 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (8) , 3498
An Innovative Cooperative Driving Strategy for Signal-Free Intersection Navigation with CAV Platoons
We present an innovative cooperative driving strategy known as Dynamic Resequencing and Platooning (DRP) designed to ensure the safe and efficient traversal of Connected and Automated Vehicles (CAVs) through signal-free intersections. By employing a Resequencing and Platooning Algorithm (RPA) grounded in state transition networks and CAV platooning, the optimal crossing sequence for CAVs is ascertained within a finite time. Through the utilization of a decentralized energy-optimal control framework, optimal trajectories are devised for CAVs, thereby facilitating optimal coordination among them. Simulation results underscore the substantial performance benefits of the DRP strategy compared to traffic light, First-In-First-Out (FIFO), and Local Dynamic Resequencing (LDR) strategies, with notable reductions observed in both travel delay and fuel consumption.
- 21 April 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (8) , 3498
Open AccessAn Innovative Cooperative Driving Strategy for Signal-Free Intersection Navigation with CAV Platoons
We present an innovative cooperative driving strategy known as Dynamic Resequencing and Platooning (DRP) designed to ensure the safe and efficient traversal of Connected and Automated Vehicles (CAVs) through signal-free intersections. By employing a Resequencing and Platooning Algorithm (RPA) grounded in state transition networks and CAV platooning, the optimal crossing sequence for CAVs is ascertained within a finite time. Through the utilization of a decentralized energy-optimal control framework, optimal trajectories are devised for CAVs, thereby facilitating optimal coordination among them. Simulation results underscore the substantial performance benefits of the DRP strategy compared to traffic light, First-In-First-Out (FIFO), and Local Dynamic Resequencing (LDR) strategies, with notable reductions observed in both travel delay and fuel consumption.
- 1 January 2023
- Published by Curran Associates, Inc.
- p. 812-817
Discussion on the Layout of Geological Radar Detection Lines for Tunnel Advanced Geological Prediction under Complex Geological Conditions - Taking a Drilling and Blasting Tunnel Section of Guangdong Water Resources Allocation Project in Beibu Gulf Rim as an Example
- 1 January 2023
- Published by Curran Associates, Inc.
- p. 812-817
Discussion on the Layout of Geological Radar Detection Lines for Tunnel Advanced Geological Prediction under Complex Geological Conditions - Taking a Drilling and Blasting Tunnel Section of Guangdong Water Resources Allocation Project in Beibu Gulf Rim as an Example