In the future connected vehicle environment,the information of multiple vehicles ahead can be readily collected in real-time,such as the velocity or headway,which provides more opportunities for information exchange a...In the future connected vehicle environment,the information of multiple vehicles ahead can be readily collected in real-time,such as the velocity or headway,which provides more opportunities for information exchange and cooperative control.Meanwhile,gyroidal roads are one of the fundamental road patterns prevalent in mountainous areas.To effectively control the system,it is therefore significant to explore the evolution mechanism of traffic flow on gyroidal roads under a connected vehicle environment.In this paper,we present a new continuum model with the average velocity of multiple vehicles ahead on gyroidal roads.The stability criterion and KdV-Burger equation are deduced via linear and nonlinear stability analysis,respectively.Solving the above KdV-Burger equation yields the density wave solution,which explores the formation and propagation property of traffic jams near the neutral stability curve.Simulation examples verify that the model can reproduce complex phenomena,such as shock waves and rarefaction waves.The analysis of the local cluster effect shows that the number of vehicles ahead and the radius information,and the slope information of gyroidal roads can exert a great influence on traffic jams.The effect of the first and second terms are positive,while the last term is negative.展开更多
The driver’s characteristics(e.g.,timid and aggressive)has been proven to greatly affect the traffic flow performance,whereas the underlying assumption in most of the existing studies is that all drivers are homogene...The driver’s characteristics(e.g.,timid and aggressive)has been proven to greatly affect the traffic flow performance,whereas the underlying assumption in most of the existing studies is that all drivers are homogeneous.In the real traffic environment,the drivers are distinct due to a variety of factors such as personality characteristics.To better reflect the reality,we introduce the penetration rate to describe the degree of drivers’heterogeneity(i.e.,timid and aggressive),and proceed to propose a generalized heterogeneous car-following model with different driver’s characteristics.Through the linear stability analysis,the stability conditions of the proposed heterogeneous traffic flow model are obtained based on the perturbation method.The impacts of the penetration rate of drivers with low intensity,the average value and standard deviation of intensity parameters characterizing two types of drivers on the stability of traffic flow are analyzed by simulation.Results show that higher penetration of aggressive drivers contributes to traffic flow stability.The average value has a great impact on the stability of traffic flow,whereas the impact of the standard deviation is trivial.展开更多
Car taillights are ubiquitous during the deceleration process in real traffic,while drivers have a memory for historical information.The collective effect may greatly affect driving behavior and traffic flow performan...Car taillights are ubiquitous during the deceleration process in real traffic,while drivers have a memory for historical information.The collective effect may greatly affect driving behavior and traffic flow performance.In this paper,we propose a continuum model with the driver's memory time and the preceding vehicle's taillight.To better reflect reality,the continuous driving process is also considered.To this end,we first develop a unique version of a car-following model.By converting micro variables into macro variables with a macro conversion method,the micro carfollowing model is transformed into a new continuum model.Based on a linear stability analysis,the stability conditions of the new continuum model are obtained.We proceed to deduce the modified KdV-Burgers equation of the model in a nonlinear stability analysis,where the solution can be used to describe the propagation and evolution characteristics of the density wave near the neutral stability curve.The results show that memory time has a negative impact on the stability of traffic flow,whereas the provision of the preceding vehicle's taillight contributes to mitigating traffic congestion and reducing energy consumption.展开更多
基金supported by Guangdong Basic and Applied Research Foundation(Project No.2022A1515010948,2019A1515111200,2019A1515110837,2023A1515011696)the National Science Foundation of China(Project No.72071079,52272310).
文摘In the future connected vehicle environment,the information of multiple vehicles ahead can be readily collected in real-time,such as the velocity or headway,which provides more opportunities for information exchange and cooperative control.Meanwhile,gyroidal roads are one of the fundamental road patterns prevalent in mountainous areas.To effectively control the system,it is therefore significant to explore the evolution mechanism of traffic flow on gyroidal roads under a connected vehicle environment.In this paper,we present a new continuum model with the average velocity of multiple vehicles ahead on gyroidal roads.The stability criterion and KdV-Burger equation are deduced via linear and nonlinear stability analysis,respectively.Solving the above KdV-Burger equation yields the density wave solution,which explores the formation and propagation property of traffic jams near the neutral stability curve.Simulation examples verify that the model can reproduce complex phenomena,such as shock waves and rarefaction waves.The analysis of the local cluster effect shows that the number of vehicles ahead and the radius information,and the slope information of gyroidal roads can exert a great influence on traffic jams.The effect of the first and second terms are positive,while the last term is negative.
基金supported by the Regional Joint Fund for Foundation and Applied Research Fund of Guangdong Province,China(Grant No.2019A1515111200)Youth Innovation Talents Funds of Colleges and Universities in Guangdong Province,China(Grant No.2018KQNCX287)+2 种基金the Science and Technology Program of Guangzhou,China(Grant No.201904010202)the National Science Foundation of China(Grant No.72071079)the Science and Technology Program of Guangdong Province,China(Grant No.2020A1414010010).
文摘The driver’s characteristics(e.g.,timid and aggressive)has been proven to greatly affect the traffic flow performance,whereas the underlying assumption in most of the existing studies is that all drivers are homogeneous.In the real traffic environment,the drivers are distinct due to a variety of factors such as personality characteristics.To better reflect the reality,we introduce the penetration rate to describe the degree of drivers’heterogeneity(i.e.,timid and aggressive),and proceed to propose a generalized heterogeneous car-following model with different driver’s characteristics.Through the linear stability analysis,the stability conditions of the proposed heterogeneous traffic flow model are obtained based on the perturbation method.The impacts of the penetration rate of drivers with low intensity,the average value and standard deviation of intensity parameters characterizing two types of drivers on the stability of traffic flow are analyzed by simulation.Results show that higher penetration of aggressive drivers contributes to traffic flow stability.The average value has a great impact on the stability of traffic flow,whereas the impact of the standard deviation is trivial.
基金jointly supported by the Foundation and Applied Research Funds Project of Guangdong,China(Project No.2019A1515111200)the Youth Innovation Talents Funds of Colleges and Universities in Guangdong Province(Project Nos.2018KQNCX287,2019KTSCX008)+1 种基金the Science and Technology Program of Guangzhou,China(Project No.201904010202)the National Science Foundation of China(Project No.61703165)。
文摘Car taillights are ubiquitous during the deceleration process in real traffic,while drivers have a memory for historical information.The collective effect may greatly affect driving behavior and traffic flow performance.In this paper,we propose a continuum model with the driver's memory time and the preceding vehicle's taillight.To better reflect reality,the continuous driving process is also considered.To this end,we first develop a unique version of a car-following model.By converting micro variables into macro variables with a macro conversion method,the micro carfollowing model is transformed into a new continuum model.Based on a linear stability analysis,the stability conditions of the new continuum model are obtained.We proceed to deduce the modified KdV-Burgers equation of the model in a nonlinear stability analysis,where the solution can be used to describe the propagation and evolution characteristics of the density wave near the neutral stability curve.The results show that memory time has a negative impact on the stability of traffic flow,whereas the provision of the preceding vehicle's taillight contributes to mitigating traffic congestion and reducing energy consumption.