Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (6): 1315-1323.doi: 10.13229/j.cnki.jdxbgxb20210028

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Coordinated control method of variable speed limit in on⁃ramp area considering safety distance

Wen-jing WU1(),Yong-bin ZHAN1,Li-li YANG1(),Run-chao CHEN2   

  1. 1.College of Transportation,Jilin University,Changchun 130022,China
    2.Xiamen Urban Planning & Design Institute Co. ,Ltd. ,Xiamen 361012,China
  • Received:2021-01-13 Online:2022-06-01 Published:2022-06-02
  • Contact: Li-li YANG E-mail:wuwj@jlu.edu.cn;yanglili@jlu.edu.cn

Abstract:

To improve the problem of traffic congestion in merging area, the paper describes the lane changing characteristics and trajectories of vehicles in on-ramp area, the calculation model of minimum safe spacing for vehicles meeting the demand of vehicle merging is proposed. First, the calculation model is incorporated into the control framework of variable speed limit. The coordinated control method and model of variable speed limit in on-ramp area under the intelligent network environment are constructed by applying model predictive control method. Then,the simulation environment is built by using cellular automata to realize the speed control of connected vehicle in upstream control area. Finally,the ramp and main road vehicle arrival rate is set in 27 scenarios according to low, medium and high, and traffic volume, speed, density and travel time are selected as evaluation indexes. The traffic conditions of on-ramp area under control are analyzed through simulation. The simulation results show that the on-ramp vehicle arrival rate affects the implementation effect of the control strategy. When the density is low, the effect is not significant; when the density is medium, the advantage of the control strategy is reflected; when the density is high, the strategy is invalid.

Key words: engineering of communication and transportation system, variable speed limit, model predictive control, safe spacing, connected vehicle

CLC Number: 

  • U491.4

Fig.1

Diagram of the position of vehicle Mbefore lane change"

Fig.2

Boundary collision point C between the lane changing vehicle M and the leading vehicle Ld"

Fig.3

Boundary collision point C between the lane changing vehicle M and the following vehicle Fd"

Fig.4

Control area diagram"

Fig.5

Control flow"

Fig.6

Schematic diagram of fitness value changing with iteration number"

Fig.7

Simulation scenario of ramp confluence control strategy under network environment"

Table 1

Ramp entry probability pin2=0.2"

主线进车概率pin1控制策略流量/(veh·h-1速度/(km·h-1密度/(veh·km-1·lane-1行程时间/s
0.2ICV-NC1 53496.778.3947 267
ICV-C1 54697.817.6746 682
0.5ICV-NC2 29891.5012.6168 541
ICV-C2 32394.7612.2764 385
1ICV-NC3 20887.6921.6576 553
ICV-C3 28090.3219.7575 526

Table 2

Ramp entry probability pin2=0.5"

主线进车概率pin1控制策略流量/(veh·h-1速度/(km·h-1密度/(veh·km-1·lane-1行程时间/s
0.2ICV-NC2 31091.529.8953 561
ICV-C2 47793.919.2152 688
0.5ICV-NC3 24580.6721.3573 120
ICV-C3 30580.4217.3268 243
1ICV-NC3 43866.9837.9586 423
ICV-C3 59671.4232.9685 547

Table 3

Ramp entry probability pin2=1"

主线进车概率pin1控制策略流量/(veh·h-1速度/(km·h-1密度/(veh·km-1·lane-1行程时间/s
0.2ICV-NC3 05985.6511.8762 468
ICV-C3 13184.3212.4368 618
0.5ICV-NC3 19261.6229.12106 589
ICV-C3 25464.8432.62115 695
1ICV-NC3 01763.4735.35125 638
ICV-C3 16158.5834.32142 033

Fig.8

When pin1=1,pin2=1,traffic flow conditions in the confluence area"

Fig.9

When pin1=1,pin2=1,traffic velocityconditions in confluence area"

Fig.10

When pin1=1,pin2=1,traffic densityconditions in confluence area"

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