An improved car-following model from the perspective of driver’s forecast behavior

Liu, Dawei; Shi, Zhongke; Ai, Wenhuan

doi:10.1142/s0129183117500462

Cited by 11 publications

(3 citation statements)

References 54 publications

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“…More recently, the driver's characteristics have been found to have a significant influence on car-following behavior. Liu et al [28] demonstrated that considering the driver's short-term memory's predictive action could improve traffic flow stability in the car-following behavior. Furthermore, Zhai et al [29] presented an extended continuum model by considering the optimal velocity changes with memory.…”

Section: Introductionmentioning

confidence: 99%

An Improved Car-Following Model considering Desired Safety Distance and Heterogeneity of Driver’s Sensitivity

Zhang

Zhou

et al. 2021

Journal of Advanced Transportation

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We investigate the dynamic performance of traffic flow using a modified optimal velocity car-following model. In the car-following scenarios, the following vehicle must continuously adjust the following distance to the preceding vehicle in real time. A new optimal velocity function incorporating the desired safety distance instead of a preset constant is presented first to describe the abovementioned car-following behavior dynamically. The boundary conditions of the new optimal velocity function are theoretically analyzed. Subsequently, we propose an improved car-following model by combining the heterogeneity of driver’s sensitivity based on the new optimal velocity function and previous car-following model. The stability criterion of the improved model is obtained through the linear analysis method. Finally, numerical simulation is performed to explore the effect of the desired safety distance and the heterogeneity of driver’s sensitivity on the traffic flow. Results show that the proposed model has considerable effects on improving traffic stability and suppressing traffic congestion. Furthermore, the proposed model is compatible with the heterogeneity of driver’s sensitivity and can enhance the average velocity of traffic flow compared with the conventional model. In conclusion, the dynamic performance of traffic flow can be improved by considering the desired safety distance and the heterogeneity of driver’s sensitivity in the car-following model.

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Section: Introductionmentioning

confidence: 99%

An Improved Car-Following Model considering Desired Safety Distance and Heterogeneity of Driver’s Sensitivity

Zhang

Zhou

et al. 2021

Journal of Advanced Transportation

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show abstract

“…Car-following theory is one of the most important part of modern traffic theory. Since 1953 when Pipes [1] presented the first model, an increasing number of models have been proposed [2][3][4][5][6][7][8][9].In 2002, Jiang et al [6] presented a car-following model called full velocity difference model (FVDM).FVDM revealed the complex dynamic characteristics of traffic flow, therefore, various developed models based FVDM were proposed.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Stability and Solitary Waves for the Car-Following Model on Two Lanes

Xing

et al. 2020

IFIP Advances in Information and Communication Technology

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In this paper, Analysis of the stability and solitary waves for a carfollowing model on two lanes is carried out. The stability condition of the model is obtained by using the linear stability theory. We study the nonlinear characteristics of the model and obtain the solutions of Burgers equation, KDV equation, and MKDV equation, which can be used to describe density waves in three regions (i.e., stable, metastable and unstable), respectively. The analytical results show that traffic flow can be stabilized further by incorporating the effects come from the leading car of the nearest car on neighbor lane into carfollowing model.

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“…More recently, there has been an increasing tendency to adopt scientific methods, and try to assess all kinds of traffic phenomena by means of controlled experiments. Paralleled with ex-periments, many physical models have been proposed [1][2][3]. Most of them are hydrodynamic models which provide a macroscopic description of traffic flow.…”

Section: Introductionmentioning

confidence: 99%

Phase Plane Analysis of Traffic Phenomena with Different Input and Output Conditions

Xing

et al. 2020

IFIP Advances in Information and Communication Technology

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In this paper, the traffic flow problem is converted into a system stability problem through variable substitution and a phase plane analysis method is presented for analyzing the complex nonlinear traffic phenomena. This method matches traffic congestion with the unstable system. So these theories and methods of stability can be applied directly to solve the traffic problem. Based on an anisotropic continuum model developed by Gupta and Katiyar(GK model), this paper uses this new method to describe various nonlinear phenomena due to different input and output conditions on ramps which were rarely studied in the past. The results show that the traffic phenomena described by the new method is consistent with that described by traditional methods. Moreover, the phase plane diagram highlights the unstable traffic phenomena we are chiefly concerned about and describes the variation of density or velocity with time or sections more clearly.

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An improved car-following model from the perspective of driver’s forecast behavior

Cited by 11 publications

References 54 publications

An Improved Car-Following Model considering Desired Safety Distance and Heterogeneity of Driver’s Sensitivity

An Improved Car-Following Model considering Desired Safety Distance and Heterogeneity of Driver’s Sensitivity

Analysis of the Stability and Solitary Waves for the Car-Following Model on Two Lanes

Phase Plane Analysis of Traffic Phenomena with Different Input and Output Conditions

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