Abstract
Signalized intersections play an important role in transportation efficiency and vehicle fuel economy in urban areas. This paper proposes a cooperative method of traffic signal control and vehicle speed optimization for connected automated vehicles, which optimizes the traffic signal timing and vehicles' speed trajectories at the same time. The method consists of two levels, i.e., roadside traffic signal optimization and onboard vehicle speed control. The former calculates the optimal traffic signal timing and vehicles' arrival time to minimize the total travel time of all vehicles; the latter optimizes the engine power and brake force to minimize the fuel consumption of individual vehicles. The enumeration method and the pseudospectral method are applied in roadside and onboard optimization, respectively. Simulation studies are conducted to compare the proposed method with benchmark methods. The results show significant improvement of transportation efficiency and fuel economy by the cooperation method.
| Original language | English |
|---|---|
| Article number | 8408521 |
| Pages (from-to) | 1390-1403 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Intelligent Transportation Systems |
| Volume | 20 |
| Issue number | 4 |
| DOIs | |
| State | Published - Apr 2019 |
| Externally published | Yes |
Funding
Manuscript received June 27, 2017; revised December 8, 2017, May 14, 2018, and May 26, 2018; accepted June 16, 2018. Date of publication July 9, 2018; date of current version March 29, 2019. This work was supported in part by the National Natural Science Foundation of China under Grant 51475254 and Grant 51625503, in part by the National Science and Technology Major Project under Grant 2016ZX03002019, in part by the National Science Foundation under Grant CMMI-1719551, in part by the National Key R&D Program in China under Grant 2016YFB0100906, and in part by the U.S. Department of Transportation, Tier 1 University of Transportation Center on Connected Cities for Smart Mobility towards Accessible and Resilience Transportation. The Associate Editor for this paper was I. Papamichail. (Corresponding author: Keqiang Li.) B. Xu, Y. Bian, J. Wang, S. E. Li, and K. Li are with the Department of Automotive Engineering, Tsinghua University, Beijing 100084, China, and also with the Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing 100084, China (e-mail: [email protected]; byg14@mails. tsinghua.edu.cn; [email protected]; [email protected]; likq@ tsinghua.edu.cn). This work was supported in part by the National Natural Science Foundation of China under Grant 51475254 and Grant 51625503, in part by the National Science and Technology Major Project under Grant 2016ZX03002019, in part by the National Science Foundation under Grant CMMI-1719551, in part by the National Key R and D Program in China under Grant 2016YFB0100906.
Keywords
- Traffic signal optimization
- V2I cooperation
- connected automated vehicle
- fuel consumption
- intelligent transportation systems
- travel time
- vehicle speed control