Reducing gasoline consumption in mixed connected automated vehicles environment: A joint optimization framework for traffic signals and vehicle trajectory

2020 ◽  
Vol 265 ◽  
pp. 121836 ◽  
Author(s):  
Zhihong Yao ◽  
Bin Zhao ◽  
Tengfei Yuan ◽  
Haoran Jiang ◽  
Yangsheng Jiang
2021 ◽  
Vol 13 (16) ◽  
pp. 9482
Author(s):  
Yuanyuan Wu ◽  
Feng Zhu

The concept of signal-free management at road junctions is tailored for Connected and Automated Vehicles (CAVs), in which the conventional signal control is replaced by various right-of-way assignment policies. First-Come-First-Served (FCFS) is the most commonly used policy. In most proposed strategies, although the traffic signals are replaced, the organization of vehicle trajectory remains the same as that of traffic lights. As a naturally signal-free strategy, roundabout has not received enough attention. A key motivation of this study is to theoretically compare the performance of signalized intersection (I-Signal), intersection using FCFS policy (I-FCFS), roundabout using the typical major-minor priority pattern (R-MM), and roundabout adopting FCFS policy (R-FCFS) under pure CAVs environment. Queueing theory is applied to derive the theoretical formulas of the capacity and average delay of each strategy. M/G/1 model is used to model the three signal-free strategies, while M/M/1/setup model is used to capture the red-and-green light switch nature of signal control. The critical safety time gaps are the main variables and are assumed to be generally distributed in the theoretical derivation. Analytically, I-Signal has the largest capacity benefiting from the ability to separate conflict points in groups, but in some cases it will have higher delay. Among the other three signal-free strategies, R-FCFS has the highest capacity and the least average control delay, indicating that the optimization of signal-free management of CAVs based on roundabout setting is worthy of further study.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yangsheng Jiang ◽  
Bin Zhao ◽  
Meng Liu ◽  
Zhihong Yao

Connected and automated vehicles (CAVs) trajectories not only provide more real-time information by vehicles to infrastructure but also can be controlled and optimized, to further save travel time and gasoline consumption. This paper proposes a two-level model for traffic signal timing and trajectories planning of multiple connected automated vehicles considering the random arrival of vehicles. The proposed method contains two levels, i.e., CAVs’ arrival time and traffic signals optimization, and multiple CAVs trajectories planning. The former optimizes CAVs’ arrival time and traffic signals in a random environment, to minimize the average vehicle’s delay. The latter designs multiple CAVs trajectories considering average gasoline consumption. The dynamic programming (DP) and the General Pseudospectral Optimal Control Software (GPOPS) are applied to solve the two-level optimization problem. Numerical simulation is conducted to compare the proposed method with a fixed-time traffic signal. Results show that the proposed method reduces both average vehicle’s delay and gasoline consumption under different traffic demand significantly. The average reduction of vehicle’s delay and gasoline consumption are 26.91% and 10.38%, respectively, for a two-phase signalized intersection. In addition, sensitivity analysis indicates that the minimum green time and free-flow speed have a noticeable effect on the average vehicle’s delay and gasoline consumption.


2020 ◽  
Vol 53 (2) ◽  
pp. 14966-14971
Author(s):  
Musa Furkan Keskin ◽  
Bile Peng ◽  
Balazs Kulcsar ◽  
Henk Wymeersch

2021 ◽  
Vol 127 ◽  
pp. 103126
Author(s):  
Hari Hara Sharan Nagalur Subraveti ◽  
Anupam Srivastava ◽  
Soyoung Ahn ◽  
Victor L. Knoop ◽  
Bart van Arem

Author(s):  
Xie Xie ◽  
Chen He ◽  
Huixu Luan ◽  
Yangrui Dong ◽  
Kun Yang ◽  
...  

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