scholarly journals A Modified Car-following Model Considering Traffic Density and Acceleration of Leading Vehicle

2020 ◽  
Vol 10 (4) ◽  
pp. 1268
Author(s):  
Xudong Cao ◽  
Jianjun Wang ◽  
Chenchen Chen
Keyword(s):  
Traffic Flow ◽  
Linear Stability Theory ◽  
Traffic Density ◽  
Neutral Stability ◽  
Difference Model ◽  
Velocity Difference ◽  
Car Following ◽  
Car Following Model ◽  
The Difference ◽  
Improved Model

Although the difference between the velocity of two successive vehicles is considered in the full velocity difference model (FVDM), more status information from preceding vehicles affecting the behavior of car-following has not been effectively utilized. For improving the performance of the FVDM, an extended modified car-following model taking into account traffic density and the acceleration of a leading vehicle (DAVD, density and acceleration velocity difference model) is presented under the condition of vehicle-to-vehicle (V2V) communications. Stability in the developed model is derived through applying linear stability theory. The curves of neutral stability for the improved model indicate that when the driver pays more attention to the traffic status in front, the traffic flow stability region is larger. Numerical simulation illustrates that traffic flow disturbance could be suppressed by gaining more information on preceding vehicles.

A New Car-Following Model with the Consideration of the Leader’s Acceleration

2015 ◽  
Vol 738-739 ◽  
pp. 489-492
Author(s):  
Tong Zhou ◽  
Yu Xuan Li ◽  
Zhan Wei Bai
Keyword(s):  
Numerical Simulation ◽  
Traffic Flow ◽  
Linear Stability ◽  
Linear Stability Theory ◽  
Difference Model ◽  
Velocity Difference ◽  
Optimal Velocity ◽  
New Model ◽  
Car Following ◽  
Car Following Model

Based on the optimal velocity difference model (for short, OVDM) proposed by Peng et al., a new car-following model is presented by considering the leading cars’ acceleration. The linear stability condition of the new model is obtained by using the linear stability theory. Numerical simulation shows that the new model can avoid the disadvantage of negative velocity occurred in the OVDM by adjusting the coefficient of the leaders acceleration and can stabilize traffic flow more effectively.

An extended car-following model incorporating the effects of driver’s memory and mean expected velocity field in ITS environment

2021 ◽  
pp. 2150095
Author(s):  
Hua Kuang ◽  
Fang-Hua Lu ◽  
Feng-Lan Yang ◽  
Guang-Han Peng ◽  
Xing-Li Li
Keyword(s):  
Velocity Field ◽  
Traffic Flow ◽  
Linear Stability Theory ◽  
Traffic Density ◽  
Neutral Stability ◽  
New Model ◽  
Car Following ◽  
Car Following Model ◽  
The Mean ◽  
The Stability

In this paper, an extended car-following model is proposed to simulate traffic flow with consideration of incorporating the effects of driver’s memory and mean expected velocity field in ITS (i.e. intelligent transportation system) environment. The neutral stability condition of the new model is derived by applying the linear stability theory. Compared with the optimal velocity model and the full velocity difference model, the stability region of the new model can be significantly enlarged on the phase diagram, and the anticipating motion information of more vehicles ahead can further enhance traffic stability. Furthermore, the mean expected velocity field effect plays a more important role than that of driver’s memory effect in improving the stability of traffic flow. Nonlinear analysis is also conducted by using the reductive perturbation method, and the mKdV equation near the critical point is obtained to describe the evolution properties of traffic density waves. Numerical simulation results show that the coupling effect of driver’s memory and the mean expected velocity field can suppress the traffic jam effectively, which is in good agreement with the analytical result.

Analysis of drivers' characteristics in car-following theory

2014 ◽  
Vol 28 (24) ◽  
pp. 1450191 ◽  
Author(s):  
Geng Zhang ◽  
Di-Hua Sun ◽  
Hui Liu ◽  
Min Zhao
Keyword(s):  
Numerical Simulation ◽  
Traffic Flow ◽  
Mkdv Equation ◽  
Reductive Perturbation Method ◽  
Linear Stability Theory ◽  
Traffic Density ◽  
Car Following ◽  
Car Following Model ◽  
The Stability ◽  
The Impact

In recent years, the influence of drivers' behaviors on traffic flow has attracted considerable attention according to Transportation Cyber Physical Systems. In this paper, an extended car-following model is presented by considering drivers' timid or aggressive characteristics. The impact of drivers' timid or aggressive characteristics on the stability of traffic flow has been analyzed through linear stability theory and nonlinear reductive perturbation method. Numerical simulation shows that the propagating behavior of traffic density waves near the critical point can be described by the kink–antikink soliton of the mKdV equation. The good agreement between the numerical simulation and the analytical results shows that drivers' characteristics play an important role in traffic jamming transition.

Traffic stability of a car-following model considering driver’s desired velocity

2015 ◽  
Vol 29 (19) ◽  
pp. 1550097 ◽  
Author(s):  
Geng Zhang ◽  
Di-Hua Sun ◽  
Wei-Ning Liu ◽  
Hui Liu
Keyword(s):  
Traffic Flow ◽  
Linear Stability ◽  
Mkdv Equation ◽  
Reductive Perturbation Method ◽  
Linear Stability Theory ◽  
Stable Region ◽  
Traffic Density ◽  
Car Following ◽  
Car Following Model ◽  
Velocity Effect

In this paper, a new car-following model is proposed by considering driver’s desired velocity according to Transportation Cyber Physical Systems. The effect of driver’s desired velocity on traffic flow has been investigated through linear stability theory and nonlinear reductive perturbation method. The linear stability condition shows that driver’s desired velocity effect can enlarge the stable region of traffic flow. From nonlinear analysis, the Burgers equation and mKdV equation are derived to describe the evolution properties of traffic density waves in the stable and unstable regions respectively. Numerical simulation is carried out to verify the analytical results, which reveals that traffic congestion can be suppressed efficiently by taking driver’s desired velocity effect into account.

scholarly journals The Car Following Model with Relative Speed in Front on the Three-Lane Road

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Zichu Gao ◽  
Ning Zhang ◽  
Livia Mannini ◽  
Ernesto Cipriani
Keyword(s):  
Traffic Flow ◽  
Traffic Safety ◽  
Traffic Management ◽  
Real Life ◽  
Mkdv Equation ◽  
Linear Stability Theory ◽  
Neutral Stability ◽  
Nonlinear Stability Analysis ◽  
Car Following ◽  
Car Following Model

An improved car following model on one road with three lanes is presented in this paper, which considers the relative velocity in front on the main lane and the left and the right adjacent lanes. The stability criterion and neutral stability curve are obtained by linear stability theory. The nonlinear stability analysis is investigated further to get the solution of the modified Korteweg-de Vries (mKdV) equation and get the three areas of stability, metastability, and unstability. The new LRVD model (left and right lane velocity difference model) with bigger stable area can stabilize middle lane traffic flow better, which is proved by the linear theory, nonlinear theory, and the simulation. The LRVD model shows if drivers on the middle lane pay more attention to more cars in front on the two side lanes on the three-lane road, the middle lane traffic flow is certain to be more stable in real life. On the complex three-lane road, if intelligent traffic management system based on the huge traffic data for drivers is applied in real life, it is very helpful to ensure traffic safety, which is also the trend of transportation development in future.

scholarly journals A New Continuum Model considering Driving Behaviors and Electronic Throttle Effect on a Gradient Highway

2020 ◽  
Vol 2020 ◽  
pp. 1-22
Author(s):  
Yulei Jiao ◽  
Rongjun Cheng ◽  
Hongxia Ge
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Continuum Model ◽  
Density Wave ◽  
Linear Stability Theory ◽  
Flow Density ◽  
Neutral Stability ◽  
Electronic Throttle ◽  
Car Following ◽  
Car Following Model

In order to explore the potential impact of sloping road on traffic flow, an improved car-following model considering electronic throttle (ET) dynamics and driver’s driving characteristics on slope is proposed. Based on the improved car-following model, a new continuum model is established through the conversion relationship between microscopic variables and macroscopic variables. Firstly, the stability condition of the model is obtained by using the linear stability theory, after that the evolution process of traffic flow density wave near the neutral stability curve is studied by using the nonlinear analysis method, and we also get the improved KdV-Burgers equation. At the same time, numerical experiments and experimental verification of the model are carried out; the theoretical analysis and numerical results show that the ET effect and aggressive driving of drivers play an important role in alleviating traffic congestion to a certain extent.

Anticipation Driving Behavior in Car Following Theory

2014 ◽  
Vol 505-506 ◽  
pp. 1133-1136
Author(s):  
Feng Lv ◽  
Cai Hong Ye ◽  
Hong Xia Ge
Keyword(s):  
Traffic Flow ◽  
Critical Phenomenon ◽  
Driving Behavior ◽  
Thermodynamic Theory ◽  
Analysis Method ◽  
Difference Model ◽  
Velocity Difference ◽  
Ginzburg Landau ◽  
Car Following ◽  
Car Following Model

In this paper, a new anticipation driving car-following model (AD-TVDM) is presented based on the two velocity difference model (TVDM)[1], taking into the effect of anticipation driving behavior in real world. The nature of the model is investigated by using linear and nonlinear analysis method. A thermodynamic theory is formulated to describe the phase transition and critical phenomenon in traffic flow and the time-dependent Ginzburg-Landau (TDGL) equation is derived to describe the traffic flow near the critical point.

scholarly journals Continuum Model for Traffic Flow considering Safe Driving Awareness Heterogeneity

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Youzhi Zeng ◽  
Ning Zhang
Keyword(s):  
Traffic Flow ◽  
Continuum Model ◽  
Safe Driving ◽  
Car Following ◽  
Car Following Model ◽  
The Difference ◽  
Flow Anisotropy

This paper defines the concepts of region representative vehicle and driver and region representative safe driving awareness and its heterogeneity, and, based on these concepts and a new car-following model proposed, it proposes a new continuum model for traffic flow considering region representative safe driving awareness heterogeneity. Analyses show that the new continuum model follows traffic flow anisotropy principle, and the following insights can be gotten: (1) the bigger the difference of the preceding region representative safe driving awareness coefficient minus the following region representative safe driving awareness coefficient is, the less the probability of the wrong-way travel (the negative velocity) problem in the new continuum model is; (2) when the preceding region representative safe driving awareness coefficient is not less than the following region representative safe driving awareness coefficient, there is no wrong-way travel problem in the new continuum model, and vice versa.

A New Extended Multiple Car-Following Model Considering the Backward-Looking Effect on Traffic Flow

2012 ◽  
Vol 8 (1) ◽  
Author(s):  
Shuhong Yang ◽  
Weining Liu ◽  
Dihua Sun ◽  
Chungui Li
Keyword(s):  
Numerical Simulation ◽  
Traffic Flow ◽  
Linear Stability ◽  
Intelligent Transportation System ◽  
Rapid Development ◽  
Mkdv Equation ◽  
Linear Stability Theory ◽  
Automated Driving ◽  
Car Following ◽  
Car Following Model

To make full use of the newly available information provided by the intelligent transportation system (ITS), we presented a new car-following model applicable to automated driving control, which will be realized in the near future along with the rapid development of ITS. In this model, the backward-looking effect and the information inputs from multiple leading cars in traffic flow are considered at the same time. The linear stability criterion of this model is obtained using linear stability theory. Furthermore, the nonlinear analysis method is employed to derive the modified Korteweg-de Vries (mKdV) equation, whose kink-antikink soliton solution is then used to describe the occurrence of traffic jamming transitions. The numerical simulation of the presented model is carried out. Both the analytical analysis and numerical simulation show that the traffic jam is suppressed efficiently by just considering the information of two leading cars and a following one.

Nonlinear analysis of an improved continuum model considering headway change with memory

2018 ◽  
Vol 32 (03) ◽  
pp. 1850037 ◽  
Author(s):  
Rongjun Cheng ◽  
Jufeng Wang ◽  
Hongxia Ge ◽  
Zhipeng Li
Keyword(s):  
Energy Consumption ◽  
Nonlinear Analysis ◽  
Traffic Flow ◽  
Linear Stability ◽  
Continuum Model ◽  
Density Wave ◽  
Linear Stability Theory ◽  
Traffic Density ◽  
Neutral Stability ◽  
With Memory

Considering the effect of headway changes with memory, an improved continuum model of traffic flow is proposed in this paper. By means of linear stability theory, the new model’s linear stability with the effect of headway changes with memory is obtained. Through nonlinear analysis, the KdV–Burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line. Numerical simulation is carried out to study the improved traffic flow model, which explores how the headway changes with memory affected each car’s velocity, density and energy consumption. Numerical results show that when considering the effects of headway changes with memory, the traffic jams can be suppressed efficiently. Furthermore, research results demonstrate that the effect of headway changes with memory can avoid the disadvantage of historical information, which will improve the stability of traffic flow and minimize car energy consumption.

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