Analysis of impact of elderly drivers on traffic safety using ANN based 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.

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Effect of Imitation Phenomenon on Two-lane Traffic Safety in Fog Weather

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16193709 ◽

2019 ◽

Vol 16 (19) ◽

pp. 3709 ◽

Cited By ~ 1

Author(s):

Tan ◽

Gong ◽

Qin

Keyword(s):

Numerical Simulations ◽

Traffic Flow ◽

Traffic Safety ◽

Initial Velocity ◽

Influence Factors ◽

Influence Coefficient ◽

Car Following ◽

Vehicle Collision ◽

Car Following Model ◽

Perturbation Propagation

A neighboring lane’s vehicles are potentially important influence factors of traffic safety. In fog weather, drivers will automatically imitate the behaviors demonstrated by other vehicles in the neighboring lane. To illustrate the effect of the imitation phenomenon on traffic safety, this paper develops an extended two-lane car-following model in fog weather. Numerical simulations are carried out to study the effect of imitation on multiple-vehicle collision induced by a sudden stop, as well as perturbation propagation when a small perturbation is added to the uniform traffic flow. The results indicate that the number of collisions depends on the influence coefficient of neighboring lane’s vehicles, sensitivity, headway and initial velocity. Furthermore, the number of crumpled vehicles decreases when the imitation phenomenon is taken into account. In addition, lower vehicular velocity in the neighboring lane can reduce the magnitude of acceleration and fluctuation of headway. The perturbation can be absorbed under certain given conditions regarding the imitation phenomenon. Therefore, traffic safety can be improved by considering the effect of the imitation phenomenon on two-lane traffic flow in fog weather. The findings in this study can provide a theoretical reference for the development of multi-lane intermittent release measures in fog weather.

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Modeling Car-Following Behaviour of Turning Movements at Intersections with Consideration of Turning Radius

Journal of Advanced Transportation ◽

10.1155/2020/8884797 ◽

2020 ◽

Vol 2020 ◽

pp. 1-9

Author(s):

Fulu Wei ◽

Yongqing Guo ◽

Pan Liu ◽

Zhenggan Cai ◽

Qingyin Li ◽

...

Keyword(s):

Traffic Safety ◽

Maximum Velocity ◽

Sensitivity Coefficient ◽

Simulation Software ◽

Force Coefficient ◽

Optimal Velocity ◽

Car Following ◽

Car Following Model ◽

Turning Radius ◽

The Stability

In order to deeply analyze and describe the characteristics of car-following behaviour of turning vehicles at intersections, the features and application conditions of classic car-following models were analyzed firstly. And then, through analysing the relationship between the maximum velocity of car-following vehicles and the turning radius of intersection, the differences in key variables between turning and straight car-following behaviour were identified. On the basis of Optimal Velocity (OV) model, a Turning Optimal Velocity (TOV) car-following model with consideration of turning radius and sideway force coefficient at intersections was developed. PreScan simulation was employed to build the scene of turning car-following process at an intersection. Based on linear stability analysis, the stability conditions of the TOV model were derived. And it was found that (1) the turning radius has a significant effect on the car-following behaviour of turning vehicles at intersections; (2) with the increase of the distance between vehicles, the driver’s response sensitivity coefficient increases and then decreases and reaches the maximum value when the distance reaches the minimum safe distance; (3) with the increase of turning radius, the stability of the car-following fleet tends to decrease, and it is more likely to become a stop-and-go traffic flow. In addition, the numerical simulation results indicate that the TOV model can describe the car-following behaviour of turning vehicles more accurately with consideration of turning radius. The findings of this study can be used in the development of microscopic traffic simulation software and for improving traffic safety at intersections.

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A Space-Based Car-Following Model: Development and Application for Managed Motorway System Safety Evaluation

Future Transportation ◽

10.3390/futuretransp1030024 ◽

2021 ◽

Vol 1 (3) ◽

pp. 443-465

Author(s):

Kaveh Bevrani ◽

Edward Chung ◽

Pauline Teo

Keyword(s):

Traffic Safety ◽

Intelligent Transportation Systems ◽

Simulation Models ◽

Transportation Systems ◽

Speed Limit ◽

Variable Speed ◽

Driver Behaviour ◽

Car Following ◽

Micro Simulation ◽

Car Following Model

Traffic safety studies need more than what the current micro-simulation models can provide, as they presume that all drivers exhibit safe behaviors. Therefore, existing micro-simulation models are inadequate to evaluate the safety impacts of managed motorway systems such as Variable Speed Limits. All microscopic traffic simulation packages include a core car-following model. This paper highlights the limitations of the existing car-following models to emulate driver behaviour for safety study purposes. It also compares the capabilities of the mainstream car-following models, modelling driver behaviour with precise parameters such as headways and time-to-collisions. The comparison evaluates the robustness of each car-following model for safety metric reproductions. A new car-following model, based on the personal space concept and fish school model is proposed to simulate more accurate traffic metrics. This new model is capable of reflecting changes in the headway distribution after imposing the speed limit from variable speed limit (VSL) systems. This model can also emulate different traffic states and can be easily calibrated. These research findings facilitate assessing and predicting intelligent transportation systems effects on motorways, using microscopic simulation.

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Extended Desired Safety Margin Car-Following Model That Considers Variation of Historical Perceived Risk and Acceptable Risk

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198118773884 ◽

2018 ◽

Vol 2672 (20) ◽

pp. 86-97 ◽

Cited By ~ 2

Author(s):

Junjie Zhang ◽

Yunpeng Wang ◽

Guangquan Lu

Keyword(s):

Traffic Safety ◽

Perceived Risk ◽

Dynamic Performance ◽

External Disturbance ◽

Safety Margin ◽

Cruise Control ◽

Acceptable Risk ◽

Car Following ◽

Gray Correlation ◽

Car Following Model

In this paper, an extended desired safety margin (DSM) car-following model is proposed by accounting for the effect of the variation of historical perceived risk and acceptable risk in terms of the DSM model. By conducting gray correlation analysis, an investigation is carried out into whether the variation of historical perceived risk and acceptable risk has important effects on the acceleration or deceleration of a target vehicle based on a real-vehicle test platform. Through simulated results, the dynamic performance of an extended DSM model is investigated in comparison with the DSM model. Conclusions show that the extended DSM model can better reflect the characteristics of traffic flow compared with the DSM model, and can improve the performance of the vehicle in the start, stop, and car-following processes. Numerical simulations further demonstrate that the extended DSM model can improve traffic safety via the changes of time-to-collision and safety margin when external disturbance is introduced into the leading vehicle. Thus, historical information about target vehicles should be considered to improve the performance of car-following in adaptive cruise control (ACC) and automotive platoon driving.

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