Journal of Jilin University(Engineering and Technology Edition) ›› 2025, Vol. 55 ›› Issue (11): 3583-3592.doi: 10.13229/j.cnki.jdxbgxb.20240144

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Modeling and simulation of freeway heterogeneous traffic flow in connected and autonomous vehicle environment

Guo-zhu CHENG(),Yong-sheng CHEN   

  1. School of Civil Engineering and Transportation，Northeast Forestry University，Harbin 150040，China
  • Received:2024-02-04 Online:2025-11-01 Published:2026-02-03

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Abstract:

To explore the impact of mixed driving for human-driven vehicles （HDV） and Connected and autonomous vehicles （CAV） on traffic flow， a freeway heterogeneous traffic flow model was established. The enhanced intelligent driver model （EIDM） was utilized to describe the car-following behavior of HDV， and the EIDM model was improved to describe the car-following behavior of CAV considering the headway， speed difference and acceleration of multi-vehicles. Then， the minimizing overall braking induced by lane changes （MOBIL） model was utilized to describe the lane-changing behavior of HDV， and the game theory is introduced to consider multi-vehicle competition and cooperation， autonomous and cooperative lane-changing models of CAV were established. Through simulation experiments， the rationality of the model was evaluated and the operation characteristics of heterogeneous traffic flow were analyzed. The research shows that compared with existing models， the model built in this paper demonstrates significant advantages in traffic flow stability and driving comfort. The increase of CAV penetration rate is conducive to the improvement of traffic capacity， especially when the CAV penetration rate is greater than 0.4， the effect is more significant.

Key words: engineering of communications and transportation system, intelligent transportation system, heterogeneous traffic flow, cooperative lane-changing, game theory

CLC Number: 

  • U495

Fig.1

Lane-changing scenario"

Fig.2

Cooperative lane-changing between the TV and LV"

Table 1

Lane-changing game payoff matrix of TV and LV"

原前车
换道不换道
目标车辆换道uTV，11， uLV，11uTV，12， uLV，12
目标车辆不换道uTV，21， uLV，21uTV，22， uLV，22

Fig.3

Cooperative lane-changing between the TV and TLV"

Table 2

Lane-changing game payoff matrix of TV and TLV"

邻前车
换道不换道
目标车辆换道uTV，11， uTLV，11uTV，12， uTLV，12
目标车辆不换道uTV，21， uTLV，21uTV，22， uTLV，22

Fig.4

Cooperative lane-changing between the TV， LV and TLV"

Table 3

Lane-changing game payoff matrix of TV， LV and TLV"

原前车
换道不换道换道不换道
邻前车换道邻前车不换道
目标车辆换道uTV，111， uLV，111， uTLV，111uTV，121， uLV，121， uTLV，121uTV，112， uLV，112， uTLV，112uTV，122， uLV，122， uTLV，122
目标车辆不换道uTV，211， uLV，211， uTLV，211uTV，221， uLV，221， uTLV，221uTV，212， uLV，212， uTLV，212uTV，222， uLV，222， uTLV，222

Table 4

Types of car-following and lane-changing in combination models"

组合模型跟驰模型换道模型
HDVCAVHDVCAV
现有模型［20］IDM模型IDM模型+CACC模型STCA模型MOBIL模型
组合模型1IDM模型［23］CIDM模型［25］MOBIL模型［26］CMOBIL模型［27］
组合模型2EIDM模型［24］CEIDM模型MOBIL模型CMOBIL模型
组合模型3EIDM模型CEIDM模型MOBIL模型CMOBIL自主换道模型+GT协同换道模型

Table 5

Simulation model parameters"

参数小客车大货车
HDVCAVHDVCAV
T/s1.51.1，0.62.01.1，0.6
长，宽/m，m5，1.85，1.810，2.010，2.0
vf/（km·h-1）1201208585
s0/m2244
a/（m·s-2）1.41.40.70.7
b/（m·s-2）2222
δ4444
Δa/（m·s-2）0.30.30.30.3
ζ0.100.100.100.10
bsafe/（m·s-2）-3-3-3-3

Fig.5

Lane speed dispersion"

Fig.6

Number of lane-changing"

Fig.7

Number of braking vehicles and average deceleration"

Fig.8

Fundamental diagram of heterogeneous traffic flow"

Table 6

Traffic flow characteristic data"

CAV渗透率临界密度/（pcu·km-1）临界速度/（ km·h-1）通行能力/（pcu·h-1）通行能力提升率/%
0.05663.793 569-
0.25469.023 7605.35
0.45673.254 07314.12
0.65977.414 53827.15
0.86879.475 41951.84
1.010466.756 94194.48

Fig.9

Lane space-time trajectory graph"

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