Journal of Jilin University(Engineering and Technology Edition) ›› 2021, Vol. 51 ›› Issue (6): 2051-2060.doi: 10.13229/j.cnki.jdxbgxb20200569

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Coordinated speed control of connected mixed traffic flow based on trajectory

Yan-feng JIA1(),Da-yi QU1(),Lu LIN1,Rong-han YAO2,Xiao-long MA3   

  1. 1.School of Mechanical and Automotive Engineering，Qingdao University of Technology，Qingdao 266520，China
    2.School of Transportation & Logistics，Dalian University of Technology，Dalian 116024，China
    3.National Urban Road Traffic Equipment Intelligent Engineering Technology Research Center，Qingdao 266033，China
  • Received:2020-07-28 Online:2021-11-01 Published:2021-11-15
  • Contact: Da-yi QU E-mail:771210072@qq.com;dyqu@263.net

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Abstract:

In order to reduce the adverse impact of vehicle stop and go, a single-lane speed coordination control strategy based on the trajectory is proposed. Firstly, the information collected by road-side units is used to offset and modify the trajectories of Connected Autonomous Vehicles (CAVs) in downstream vehicle clusters to predict the trajectory of Human-driving Vehicle (HV). Then, the velocity distribution of upstream CAVs are planned, so that they can merge into the downstream traffic flow at a more reasonable and smooth speed.; The numerical simulation results show that, within the designed range of 0%~25% CAV permeability and 575 m~975 m bottleneck start position, the higher the permeability, the farther the bottleneck start position, and the smoother the CAV speed guidance curve, the stronger the inhibition of speed oscillation. At the same time, it proves that the speed coordinated control strategy can effectively reduce the fluctuation of traffic flow, improve driver's comfort and overall efficiency of vehicle queue.

Key words: engineering of communication and transportation system, connected mixed traffic flow, trajectory prediction, speed coordination, numerical simulation

CLC Number: 

  • U491

Fig.1

Schematic diagram of scene building"

Fig.2

Traffic information to be obtained"

Fig.3

Correction of offset trajectory near pend"

Fig.4

Connection merging points"

Fig.5

Modified offset trajectory"

Fig.6

First speed of CAV guidance process of upstream vehicle cluster"

Fig.7

Deceleration curves"

Fig.8

Acceleration curves"

Fig.9

Simulation results under different conditions"

Fig.10

Several different speed guide curves"

Table 1

Time of last vehicle to reach same positionunder different CAV penetration rates"

CAV渗透率/%时间/s减少率/%
500 m600 m700 m
0（参照组）125.1129.2133.2-
5123.9127.5131.81.16
10121.4125.3129.52.90
15119.5123.6127.44.41
20117.6121.6125.55.90
25115.5120.2124.37.10

Table 2

Acceleration of first CAV at different timecorresponding to different lB values"

时间点/s瓶颈开始不同位置处的加速度/（m·s-2）
575 m775 m975 m
最值差2.311.560.19
30-0.25-0.18-0.13
35-0.42-0.21-0.05
40-0.68-0.34-0.02
45-0.41-0.230.00
500.090.050.02
551.631.220.06
600.160.070.04
650.080.050.02
700.040.020.01
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