Journal of Shandong University(Engineering Science) ›› 2022, Vol. 52 ›› Issue (6): 23-29.doi: 10.6040/j.issn.1672-3961.0.2022.068

• Transportation Engineering—Special Issue for Intelligent Transportation • Previous Articles     Next Articles

Eco-driving model for connected and automated vehicle platoons using the traffic capacity remainder

Shaowei YU1,4(),Ruiling QIN2,Jingjing GUAN2,Can JI1,Shuo FENG3,Rui JIANG2,*(),Yingning LIU1   

  1. 1. School of Transportation Engineering, Chang′an University, Xi′an 710064, Shaanxi, China
    2. School of Information Engineering, Chang′an University, Xi′an 710064, Shaanxi, China
    3. School of Engineering Machinery, Chang′an University, Xi′an 710064, Shaanxi, China
    4. Key Laboratory of Transport Industry of Management, Control and Cycle Repair Technology for Traffic Network Facilities in Ecological Security Barrier Area, Chang′an University, Xi′an 710064, Shaanxi, China
  • Received:2022-02-19 Online:2022-12-20 Published:2022-12-23
  • Contact: Rui JIANG E-mail:swyu2020@126.com;jiangrui@bjtu.edu.cn

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Abstract:

Aiming at the problems of capacity remainder and high fuel consumption on unsaturated urban and rural traffic roads, this paper proposed an eco-driving model for connected and automated platoons using the capacity remainder, which considered the two goals of fuel economy and traffic capacity, and obtained the optimal speed profiles by solving optimization, to guide a series of small-sized platoons smoothly through the unsaturated urban and rural traffic corridors. In order to improve the computational efficiency of the proposed eco-driving model, this paper proposed an approximate speed optimization model and used genetic algorithm. In order to verify the performance of the proposed model, three control strategies were defined to test the model. The simulation results showed that compared with Strategy 1, Strategy 2 could reduce fuel consumption by 49.4%, increased traffic capacity by 200%, and reduced remaining green time by 14.7%; Strategy 3 could reduce 59.5% of fuel consumption, increased traffic capacity by 200%, and reduced remaining green time by 23.5%. Compared with Strategy 2, Strategy 3 could reduce fuel consumption by 20% without affecting traffic capacity by reducing remaining green time by 10.3% and the average speed by 5.2%. The results showed that when there was traffic capacity remainder at the signalized intersection, the fuel economy could be significantly improved by adjusting the vehicle speed curve to make full use of the traffic capacity remainder.

Key words: intelligent transportation, eco-driving, connected and automated vehicle platoons, the traffic capacity remainder, prediction-based optimization strategy

CLC Number: 

  • U495

Fig.1

Study scenario"

Fig.2

Schematic diagram of the test road"

Table 1

Simulation parameter setting"

交叉口名称 绿灯时长/s 红灯时长/s 停车线距车辆起点距离/m
第一个交叉口 60 80 0
第二个交叉口 49 5 832
第三个交叉口 63 29 1151

Table 2

Fuel consumption under different strategies  mL"

控制方案 F1 F2 F
1 1 201.457 5 1 060.594 7 2 263.052 2
2 694.386 0 450.622 8 1 145.008 8
3 694.386 0 221.079 5 915.465 5

Table 3

Capacity under different strategies  辆"

控制方案 V1 V2 V1
1 12 4 4
2 12 12 12
3 12 12 12

Table 4

Average speed under different strategies  km/h"

控制方案 ${\bar v}$1 ${\bar v}$2 ${\bar v}$
1 53.095 0 50.745 0 51.920 0
2 62.121 4 55.879 6 59.000 5
3 62.121 4 49.693 1 55.907 3

Fig.3

Travel time-fuel consumption-average speed"

Table 5

Remaining green times  s"

控制方案 t2 t3
1 0 34
2 0 29
3 0 26
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