Delayed Car-Following Dynamics for Human and Robotic Drivers

2011 ◽  
Author(s):  
Ga´bor Orosz ◽  
Jeff Moehlis ◽  
Francesco Bullo
Keyword(s):  
Nonlinear Function ◽  
Nonlinear Behavior ◽  
Velocity Model ◽  
Cruise Control ◽  
Optimal Velocity ◽  
Car Following ◽  
High Frequency Oscillations ◽  
Computer Controlled ◽  
The Stability ◽  
Theoretical Results

A general class of car-following models is analyzed where the longitudinal acceleration of a vehicle is determined by a nonlinear function of the distance to the vehicle in front, their velocity difference, and the vehicle’s own velocity. The driver’s response to these stimuli includes the driver reaction time that appears as a time delay in governing differential equations. The linear stability of the uniform flow is analyzed for human-driven and computer-controlled (robotic) vehicles. It is shown that the stability conditions are equivalent when considering ring-road and platoon configurations. It is proven that time delays result in novel high-frequency oscillations that manifest themselves as short-wavelength traveling waves. The theoretical results are illustrated using an optimal velocity model where the nonlinear behavior is also revealed by numerical simulations. The results may lead to better understanding of multi-vehicle dynamics and allow one to design cooperative autonomous cruise control algorithms.

OPTIMAL VELOCITY MODEL WITH RELATIVE VELOCITY

2006 ◽  
Vol 17 (01) ◽  
pp. 65-73 ◽  
Author(s):  
SHIRO SAWADA
Keyword(s):  
Nonlinear Analysis ◽  
Relative Velocity ◽  
Velocity Model ◽  
Fundamental Diagram ◽  
Optimal Velocity ◽  
Traffic Jam ◽  
Optimal Velocity Model ◽  
Linear And Nonlinear ◽  
The Stability ◽  
Good Agreement

The optimal velocity model which depends not only on the headway but also on the relative velocity is analyzed in detail. We investigate the effect of considering the relative velocity based on the linear and nonlinear analysis of the model. The linear stability analysis shows that the improvement in the stability of the traffic flow is obtained by taking into account the relative velocity. From the nonlinear analysis, the relative velocity dependence of the propagating kink solution for traffic jam is obtained. The relation between the headway and the velocity and the fundamental diagram are examined by numerical simulation. We find that the results by the linear and nonlinear analysis of the model are in good agreement with the numerical results.

scholarly journals A New Car-Following Model with Consideration of Dynamic Safety Distance

2018 ◽  
Vol 2018 ◽  
pp. 1-5
Author(s):  
Tao Wang ◽  
Jing Zhang ◽  
Guangyao Li ◽  
Keyu Xu ◽  
Shubin Li
Keyword(s):  
Traffic Flow ◽  
Velocity Model ◽  
Safe Distance ◽  
Optimal Velocity ◽  
New Model ◽  
Car Following ◽  
Optimal Velocity Model ◽  
Safety Distance ◽  
Car Following Model ◽  
The Impact

In the traditional optimal velocity model, safe distance is usually a constant, which, however, is not representative of actual traffic conditions. This paper attempts to study the impact of dynamic safety distance on vehicular stream through a car-following model. Firstly, a new car-following model is proposed, in which the traditional safety distance is replaced by a dynamic term. Then, the phase diagram in the headway, speed, and sensitivity spaces is given to illustrate the impact of a variable safe distance on traffic flow. Finally, numerical methods are conducted to examine the performance of the proposed model with regard to two aspects: compared with the optimal velocity model, the new model can suppress traffic congestion effectively and, for different safety distances, the dynamic safety distance can improve the stability of vehicular stream. Simulation results suggest that the new model is able to enhance traffic flow stability.

An extended optimal velocity difference model in a cooperative driving system

2015 ◽  
Vol 26 (05) ◽  
pp. 1550054
Author(s):  
Jinliang Cao ◽  
Zhongke Shi ◽  
Jie Zhou
Keyword(s):  
Traffic Flow ◽  
Linear Stability Theory ◽  
Difference Model ◽  
Optimal Velocity ◽  
Driving System ◽  
Cooperative Driving ◽  
Proposed Model ◽  
De Vries ◽  
The Stability ◽  
Theoretical Results

An extended optimal velocity (OV) difference model is proposed in a cooperative driving system by considering multiple OV differences. The stability condition of the proposed model is obtained by applying the linear stability theory. The results show that the increase in number of cars that precede and their OV differences lead to the more stable traffic flow. The Burgers, Korteweg–de Vries (KdV) and modified Korteweg–de Vries (mKdV) equations are derived to describe the density waves in the stable, metastable and unstable regions, respectively. To verify these theoretical results, the numerical simulation is carried out. The theoretical and numerical results show that the stabilization of traffic flow is enhanced by considering multiple OV differences. The traffic jams can be suppressed by taking more information of cars ahead.

Analysis of within-host CHIKV dynamics models with general incidence rate

2018 ◽  
Vol 11 (05) ◽  
pp. 1850062 ◽  
Author(s):  
Ahmed M. Elaiw ◽  
Taofeek O. Alade ◽  
Saud M. Alsulami
Keyword(s):  
Global Stability ◽  
Incidence Rate ◽  
Sufficient Conditions ◽  
Nonlinear Function ◽  
Steady States ◽  
Positive Steady States ◽  
Latently Infected ◽  
The Stability ◽  
Dynamics Models ◽  
Theoretical Results

In this paper we study the stability analysis of two within-host Chikungunya virus (CHIKV) dynamics models. The incidence rate between the CHIKV and the uninfected monocytes is modeled by a general nonlinear function. The second model considers two types of infected monocytes (i) latently infected monocytes which do not generate CHIKV and (ii) actively infected monocytes which produce the CHIKV particles. Sufficient conditions are found which guarantee the global stability of the positive steady states. Using the Lyapunov function, we established the global stability of the steady states of the models. The theoretical results are confirmed by numerical simulations.

scholarly journals An Extended Car-Following Model at Signalised Intersections

2018 ◽  
Vol 2018 ◽  
pp. 1-26 ◽  
Author(s):  
Hongxing Zhao ◽  
Ruichun He ◽  
Changxi Ma
Keyword(s):  
Velocity Model ◽  
Measured Data ◽  
Velocity Difference ◽  
Optimal Velocity ◽  
Car Following ◽  
Optimal Velocity Model ◽  
Trajectory Simulation ◽  
Car Following Model ◽  
Point Data ◽  
Isolated Point

An extended car-following model is proposed on the basis of experimental analysis to improve the performance of the traditional car-following model and simulate a microscopic car-following behaviour at signalised intersections. The new car-following model considers vehicle gather and dissipation. Firstly, the parameters of optimal velocity, generalised force and full velocity difference models are calibrated by measured data, and the problems and causes of the three models are analysed with a realistic trajectory simulation as an evaluation criterion. Secondly, an extended car-following model based on the full optimal velocity model is proposed by considering the vehicle gather and dissipation. The parameters of the new car-following model are calibrated by the measured data, and the model is compared with comparative models on the basis of isolated point data and the entire car-following process. Simulation results show that the optimal velocity, generalised force, and full velocity difference models cannot effectively simulate a microscopic car-following behaviour at signalised intersections, whereas the new car-following model can avoid a collision and has a high fit degree for simulating the measured data of the car-following behaviour at signalised intersections.

A REVISED STOCHASTIC OPTIMAL VELOCITY MODEL CONSIDERING THE VELOCITY GAP WITH A PRECEDING VEHICLE

2011 ◽  
Vol 22 (09) ◽  
pp. 1005-1014 ◽  
Author(s):  
KEIZO SHIGAKI ◽  
JUN TANIMOTO ◽  
AYA HAGISHIMA
Keyword(s):  
Velocity Model ◽  
Model Parameters ◽  
Fundamental Diagram ◽  
Cellular Automata Model ◽  
Optimal Velocity ◽  
Car Following ◽  
Proposed Model ◽  
Preceding Vehicle ◽  
Long Time ◽  
Car Following Model

The stochastic optimal velocity (SOV) model, which is a cellular automata model, has been widely used because of its good reproducibility of the fundamental diagram, despite its simplicity. However, it has a drawback: in SOV, a vehicle that is temporarily stopped takes a long time to restart. This study proposes a revised SOV model that suppresses this particular defect; the basic concept of this model is derived from the car-following model, which considers the velocity gap between a particular vehicle and the preceding vehicle. A series of simulations identifies the model parameters and clarifies that the proposed model can reproduce the three traffic phases: free, jam, and even synchronized phases, which cannot be achieved by the conventional SOV model.

Studying Car-Following Dynamics on the Basis of the HighD Dataset

2020 ◽  
Vol 2674 (8) ◽  
pp. 813-822
Author(s):  
Valentina Kurtc
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Velocity Model ◽  
Driver Model ◽  
Good Precision ◽  
Optimal Velocity ◽  
Car Following ◽  
Optimal Velocity Model ◽  
Position Time Series ◽  
Vehicle Trajectory

A large-scale naturalistic vehicle trajectory dataset from German highways, highD, was used to investigate the car-following behavior of individual drivers. These data include trajectories of 110,000 vehicles recorded for a duration of 16.5 h. Solving a nonlinear optimization problem, the intelligent driver model and the optimal velocity model with two leaders in interaction were calibrated by minimizing the deviations between the observed and simulated gaps when following the prescribed leading vehicle. The obtained calibration errors ranged between 5.2% and 6.9%, which were slightly lower than previous findings. This was explained by the shorter highD trajectories, predominantly free-flow traffic, and the good precision metrics of this dataset. The optimal velocity model with multivehicle anticipation resulted in lower calibration errors. This confirmed that natural drivers take into account several leading vehicles ahead. The ratio between interdriver and intradriver variability was investigated by performing global and platoon calibrations. Intradriver variation accounted for a larger portion of the calibration errors than interdriver variation. We analyzed the acceleration time-series of the natural highD and artificial drivers using simulations of two car-following models. A new cumulative measure, proportional to the energy of the follower’s position time-series curve, was calculated both for natural and modeled drivers. Human drivers had higher energy and demonstrated more acceleration fluctuations, sometimes behaving irrationally. In contrast, artificial drivers followed the logical rules incorporated in the model, resulting in a smoother acceleration profile. This led to less fuel consumption and gas emissions.

scholarly journals Stability Analysis of Train Movement with Uncertain Factors

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
JingJing Ye ◽  
KePing Li ◽  
XueDong Jiang
Keyword(s):  
Relaxation Time ◽  
Stability Analysis ◽  
Fuzzy Theory ◽  
Traffic Model ◽  
Optimal Velocity ◽  
Car Following ◽  
Proposed Model ◽  
Car Following Model ◽  
Simulation Results ◽  
The Stability

We propose a new traffic model which is based on the traditional OV (optimal velocity) car-following model. Here, some realistic factors are regarded as uncertain quantity, such as the headway distance. Our aim is to analyze and discuss the stability of car-following model under the constraint of uncertain factors. Then, according to the principle of expected value in fuzzy theory, an improved OV traffic model is constructed. Simulation results show that our proposed model can avoid collisions effectively under uncertain environment, and its stability can also be improved. Moreover, we discuss its stability as some parameters change, such as the relaxation time.

An Extended Optimal Velocity Model of Traffic Flow with Backward Power Cooperation

2013 ◽  
Vol 336-338 ◽  
pp. 561-565
Author(s):  
Kang Li Chen ◽  
Zhi Peng Li
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Velocity Model ◽  
Mkdv Equation ◽  
Reductive Perturbation Method ◽  
Linear Stability Theory ◽  
Traffic Density ◽  
Unstable Region ◽  
Optimal Velocity ◽  
The Stability

In this paper, an extended traffic flow model which considers the strategy of the backward power cooperation is proposed by taking account of the power assist of the nearest rear car. The stability condition of the new model is derived by using the linear stability theory with finding that the power assist of the nearest rear car can stabilize the traffic flow and efficiently suppress traffic jams. Moreover, the modified Korteweg-de Vries (mKdV) equation is derived to describe the traffic density waves in the unstable region by using the reductive perturbation method and nonlinear analysis..

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