Modeling and Evaluating Traffic Flow at Sag Curves When Imposing Variable Speed Limits on Connected Vehicles

2018 ◽  
Vol 2672 (20) ◽  
pp. 193-202 ◽  
Author(s):  
Reza Vatani Nezafat ◽  
Ehsan Beheshtitabar ◽  
Mecit Cetin ◽  
Elizabeth Williams ◽  
George F. List
Keyword(s):  
Traffic Flow ◽  
Optimization Method ◽  
Driver Model ◽  
Traffic Density ◽  
Connected Vehicles ◽  
Market Penetration ◽  
Car Following ◽  
Simulation Based ◽  
Variable Speed Limits ◽  
Car Following Model

Sag curves, road segments where the gradient changes from downwards to upwards, generally reduce the roadway capacity and cause congestion. This results from a change in longitudinal driving behavior when entering a sag curve as drivers tend to reduce speeds or increase headways as vehicles reach the uphill section. In this research, a control strategy is investigated through manipulating the speed of connected vehicles (CVs) in the upstream of the sag curve to avoid the formation of bottlenecks caused by the change in driver behavior. Traffic flow along a sag curve is simulated using the intelligent driver model (IDM), a time-continuous car-following model. A feedback control algorithm is developed for adjusting the approach speeds of CVs so that the throughput of the sag curve is maximized. Depending on the traffic density at the sag curve, adjustments are made for the speeds of the CVs. A simulation-based optimization method using a meta-heuristic algorithm is employed to determine the critical control parameters. Various market penetration rates for CVs are also considered in the simulations. Even at relatively low market penetration rates (e.g., 5–10%), significant improvements in travel times and throughput are observed.

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 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.

Effect of current vehicle’s interruption on traffic stability in cooperative car-following theory

2017 ◽  
Vol 31 (34) ◽  
pp. 1750317 ◽  
Author(s):  
Geng Zhang ◽  
Hui Liu
Keyword(s):  
Numerical Simulation ◽  
Traffic Flow ◽  
Density Wave ◽  
Negative Influence ◽  
Mkdv Equation ◽  
Traffic Density ◽  
New Model ◽  
Car Following ◽  
Car Following Model ◽  
The Impact

To reveal the impact of the current vehicle’s interruption information on traffic flow, a new car-following model with consideration of the current vehicle’s interruption is proposed and the influence of the current vehicle’s interruption on traffic stability is investigated through theoretical analysis and numerical simulation. By linear analysis, the linear stability condition of the new model is obtained and the negative influence of the current vehicle’s interruption on traffic stability is shown in the headway-sensitivity space. Through nonlinear analysis, the modified Korteweg–de Vries (mKdV) equation of the new model near the critical point is derived and it can be used to describe the propagating behavior of the traffic density wave. Finally, numerical simulation confirms the analytical results, which shows that the current vehicle’s interruption information can destabilize traffic flow and should be considered in real traffic.

Analytical studies on an extended car following model for mixed traffic flow with slow and fast vehicles

2016 ◽  
Vol 27 (01) ◽  
pp. 1650004 ◽  
Author(s):  
Zhipeng Li ◽  
Xun Xu ◽  
Shangzhi Xu ◽  
Yeqing Qian ◽  
Juan Xu
Keyword(s):  
Standard Deviation ◽  
Traffic Flow ◽  
Maximum Velocity ◽  
Traffic Density ◽  
Extended Model ◽  
Mixed Traffic ◽  
Car Following ◽  
Mixed Traffic Flow ◽  
Average Maximum ◽  
Car Following Model

The car-following model is extended to take into account the characteristics of mixed traffic flow containing fast and slow vehicles. We conduct the linear stability analysis to the extended model with finding that the traffic flow can be stabilized with the increase of the percentage of the slow vehicle. It also can be concluded that the stabilization of the traffic flow closely depends on not only the average value of two maximum velocities characterizing two vehicle types, but also the standard deviation of the maximum velocities among all vehicles, when the percentage of the slow vehicles is the same as that of the fast ones. With increase of the average maximum velocity, the traffic flow becomes more and more unstable, while the increase of the standard deviation takes negative effect in stabilizing the traffic system. The direct numerical results are in good agreement with those of theoretical analysis. Moreover, the relation between the flux and the traffic density is investigated to simulate the effects of the percentage of slow vehicles on traffic flux in the whole density regions.

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.

An extended car-following model accounting for two preceding vehicles with mixed maximum velocity

2021 ◽  
pp. 2150238
Author(s):  
Rongjun Cheng ◽  
Shihao Li ◽  
Hongxia Ge
Keyword(s):  
Theoretical Analysis ◽  
Traffic Flow ◽  
Density Wave ◽  
Maximum Velocity ◽  
Mkdv Equation ◽  
Traffic Density ◽  
Driving Experience ◽  
Car Following ◽  
Car Following Model ◽  
On The Road

In reality, the types of vehicles running on the road and the driving experience of different drivers are probably different. Thus, the maximum velocity of each vehicle is usually different. Moreover, common driving experience indicates that drivers not only pay attention to the motion status of individual preceding vehicle in their view. With that in mind, an extended car-following model accounting for two preceding vehicles with mixed maximum velocity is constructed in this study. For analyzing the traffic flow’s evolution more accurately, theoretical and numerical analyses are conducted. In theoretical analysis, the model’s stability condition is inferred by using the control theory, and the mKdV equation is also derived to depict the propagation of traffic density wave by means of nonlinear analysis. Numerical experiments are performed to verify the correctness of theoretical analysis and to make a detailed analysis concerning the influences of factors considered on traffic flow. Theoretical and experimental results indicate that increasing the higher maximum velocity and the appearing probability of a car having higher maximum velocity is not conducive to traffic flow stability, and compared to only considering individual preceding vehicle’s motion status, it is obvious that the traffic flow with mixed maximum velocity is more stable when two preceding vehicles’ motion status is considered.

The effects of drivers’ aggressive characteristics on traffic stability from a new car-following model

2016 ◽  
Vol 30 (18) ◽  
pp. 1650243 ◽  
Author(s):  
Guanghan Peng ◽  
Li Qing
Keyword(s):  
Stability Analysis ◽  
Nonlinear Analysis ◽  
Traffic Flow ◽  
Linear Stability Analysis ◽  
Stable Condition ◽  
Mkdv Equation ◽  
Stable Region ◽  
Car Following ◽  
Car Following Model ◽  
The Stability

In this paper, a new car-following model is proposed by considering the drivers’ aggressive characteristics. The stable condition and the modified Korteweg-de Vries (mKdV) equation are obtained by the linear stability analysis and nonlinear analysis, which show that the drivers’ aggressive characteristics can improve the stability of traffic flow. Furthermore, the numerical results show that the drivers’ aggressive characteristics increase the stable region of traffic flow and can reproduce the evolution and propagation of small perturbation.

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