Theoretical analysis of bifurcations in a microscopic traffic model accounting for optimal velocity

Wang, Yuqing; Yan, Bowen; Zhou, Cancan; Chu, Xing-Jian; Zhang, Dechen; Li, Weikang; Wang, Jixin; Fang, Chenhao; Jia, Bin; Gao, Ziyou

doi:10.1142/s021798491750244x

Cited by 31 publications

(3 citation statements)

References 31 publications

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“…Wang et al [26] developed a CFS model attributable to vehicle spacing with both lower and upper bounds. Moreover, Wang et al [27] proposed another CFS model incorporating factors of driver's reaction time and maximum acceleration. Different from the above models, Yang et al [28] proposed a new CFS model based on field data.…”

Section: Introductionmentioning

confidence: 99%

An Improved Car-Following Speed Model considering Speed of the Lead Vehicle, Vehicle Spacing, and Driver’s Sensitivity to Them

Jiao

Zhang

et al. 2020

Journal of Advanced Transportation

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This paper introduces an improved car-following speed (CFS) model that simultaneously considers speed of the lead vehicle, vehicle spacing, and driver’s sensitivity to them. Specifically, the proposed model extends the Helbing-Tilch model and Yang et al. model developed based on the principle of grey relational analysis where vehicle spacing is considered as the primary factor contributing to car-following speed choices. A computational experiment is conducted for model calibration using vehicle spacing, speed, and acceleration data derived from vehicle trajectory data of the Next Generation Simulation (NGSIM) project sponsored by the Federal Highway Administration (FHWA). It shows that speed of the lead vehicle and vehicle spacing significantly affect speed of the lag vehicle. Further, model validation is carried out using an independent NGSIM dataset by comparing vehicle speed predictions made by the calibrated CFS model with Helbing-Tilch model and Yang et al. model as benchmarks. Compared with speed prediction results of the benchmark models, mean relative errors, root mean square errors, and equal coefficient of speed predictions of the CFS model have reduced by 72.41% and 61.85%, 70.14% and 57.99%, and 33.15% and 14.48%, respectively. The findings of model validation reveal that the CFS model could improve the accuracy of speed predictions in the car-following process.

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Section: Introductionmentioning

confidence: 99%

An Improved Car-Following Speed Model considering Speed of the Lead Vehicle, Vehicle Spacing, and Driver’s Sensitivity to Them

Jiao

Zhang

et al. 2020

Journal of Advanced Transportation

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“…[1][2][3][4] In general, the complex network can be divided into small world networks, [5] self-similarity ones, [6] regular ones, [7] partly or wholly heterogeneous one. [8] It is capable of modelling real physical or engineering phenomena like traffic flow, [9][10][11][12][13][14][15] the transcription of mRNA, [16] the directional motion of active particles, [17][18][19][20][21][22][23][24][25] etc., which leads the technology networks, [26] social networks, [27] financial network, [28][29][30][31][32][33][34][35][36][37][38][39] biological networks, etc. to emerge.…”

Section: Introductionmentioning

confidence: 99%

Theoretical analyses of stock correlations affected by subprime crisis and total assets: Network properties and corresponding physical mechanisms*

Shi-Zhao

Wang

2019

Chinese Phys. B

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In the field of statistical mechanics and system science, it is acknowledged that the financial crisis has a profound influence on stock market. However, the influence of total asset of enterprise on stock quote was not considered in the previous studies. In this work, a modified cross-correlation matrix that focuses on the influence of total asset on stock quote is introduced into the analysis of the stocks collected from Asian and American stock markets, which is different from the previous studies. The key results are obtained as follows. Firstly, stock is more greatly correlated with big asset than with small asset. Secondly, the higher the correlation coefficient among stocks, the larger the eigenvector is. Thirdly, in different periods, like the pre-subprime crisis period and the peak of subprime crisis period, Asian stock quotes show that the component of the third eigenvector of the cross-correlation matrix decreases with the asset of the enterprise decreasing. Fourthly, by simulating the threshold network, the small network constructed by 10 stocks with large assets can show the large network state constructed by 30 stocks. In this research we intend to fully explain the physical mechanism for understanding the historical correlation between stocks and provide risk control strategies in the future.

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“…In order to replicate the evolution of traffic, there is the need for a mathematical modeling of the traffic flow [13][14][15][16][17][18][19][20]. In this regard, scholars have examined a (a) E-mail: poonamr.maths@mdurohtak.ac.in (corresponding author) variety of car-following models [21][22][23][24][25][26] recently, and these models are used to examine the effects of various factors on the traffic flow. But, in comparison to conventional traffic scenarios, it is found that the driver's car-following behavior and the traffic patterns of the following vehicles demonstrated different features.…”

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confidence: 99%

Impact of driver's advanced reaction time in car-following model with optimal velocity deviation under V2X environment

Yadav,

Siwach,

Redhu

2023

EPL

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The vehicle-to-everything (V2X) technology has made a significant advancement in the field of intelligent transportation in recent years. When operating a vehicle in a V2X environment, the driver can get real-time updates on the motion of nearby vehicles. In a real-world traffic situation, there is always some deviation between the actual and anticipated traffic information, and this deviation will undoubtedly have a significant effect on traffic flow. Drivers always maintain the flow of traffic by taking some time to assess and decide how the drivers in front of them are behaving behind the car in the traffic system. As a result, by taking into account the driver's advanced reaction time and optimal deviation in a V2X environment, a novel car-following model is developed and the effects of these parameters on the traffic flow are examined. In order to determine the stability requirements for the new model, the linear and nonlinear stability of the proposed model is examined using the perturbation methods. Studies have found that when the driver's reaction time and the velocity deviation are optimized, it can reduce the amplitude of the stability curve, thus enlarging the area of more stable motion. Also, the numerical simulation supports the theoretical research by showing that the new model may effectively reduce traffic congestion and improve the stability of traffic flow as the influence of these factors on the traffic flow increases.

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Theoretical analysis of bifurcations in a microscopic traffic model accounting for optimal velocity

Cited by 31 publications

References 31 publications

An Improved Car-Following Speed Model considering Speed of the Lead Vehicle, Vehicle Spacing, and Driver’s Sensitivity to Them

An Improved Car-Following Speed Model considering Speed of the Lead Vehicle, Vehicle Spacing, and Driver’s Sensitivity to Them

Theoretical analyses of stock correlations affected by subprime crisis and total assets: Network properties and corresponding physical mechanisms*

Impact of driver's advanced reaction time in car-following model with optimal velocity deviation under V2X environment

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