scholarly journals Modeling of Car-Following Required Safe Distance Based on Molecular Dynamics

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Dayi Qu ◽  
Xiufeng Chen ◽  
Wansan Yang ◽  
Xiaohua Bian
Keyword(s):  
Molecular Dynamics ◽  
Traffic Simulation ◽  
Safe Distance ◽  
Microscopic Traffic Simulation ◽  
Car Following ◽  
Before And After ◽  
Car Following Model ◽  
The Relationship

In car-following procedure, some distances are reserved between the vehicles, through which drivers can avoid collisions with vehicles before and after them in the same lane and keep a reasonable clearance with lateral vehicles. This paper investigates characters of vehicle operating safety in car following state based on required safe distance. To tackle this problem, we probe into required safe distance and car-following model using molecular dynamics, covering longitudinal and lateral safe distance. The model was developed and implemented to describe the relationship between longitudinal safe distance and lateral safe distance under the condition where the leader keeps uniform deceleration. The results obtained herein are deemed valuable for car-following theory and microscopic traffic simulation.

A new car-following model considering recurrent neural network

2019 ◽  
Vol 33 (26) ◽  
pp. 1950304 ◽  
Author(s):  
Chen Hua
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Relative Velocity ◽  
Road Traffic ◽  
Safe Distance ◽  
Velocity Difference ◽  
Car Following ◽  
Depth Analysis ◽  
Car Following Model ◽  
The Relationship

A new car-following model is proposed based on recurrent neural network (RNN) to effectively describe the state change and road traffic congestion while the vehicle is moving. The model firstly gives a full velocity difference car-following model according to the driver’s reaction sensitivity and relative velocity, and then takes the vehicle position and velocity as the input parameters to optimize the safe distance between the front and rear vehicles in the car-following model based on RNN model. Finally, the effectiveness of the above model is validated by building a simulation experiment platform, and an in-depth analysis is conducted on the relationship among influencing factors, e.g., relative velocity, reaction sensitivity, headway, etc. The results reveal that, compared with traditional car-following models, the model can quickly analyze the relationship between initial position and velocity of the vehicle in a shorter time and thus obtain a smaller safe distance. In the case of small velocity difference between the front and rear vehicles, the running velocity of the front and rear vehicles is relatively stable, which is conducive to maintaining the headway.

scholarly journals An Extended Car-Following Model in Connected and Autonomous Vehicle Environment: Perspective from the Cooperation between Drivers

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Shenzhen Ding ◽  
Xumei Chen ◽  
Zexin Fu ◽  
Fei Peng
Keyword(s):  
Traffic Simulation ◽  
Autonomous Vehicle ◽  
Significant Heterogeneity ◽  
Mixed Traffic ◽  
Trajectory Data ◽  
Data Set ◽  
Microscopic Traffic Simulation ◽  
Car Following ◽  
Proposed Model ◽  
Car Following Model

The development of connected and autonomous vehicle (CAV) technology has received increasing attention in recent years. Although car-following behavior in mixed traffic with CAVs and human-driven vehicles (HDVs) is a core component of microscopic traffic simulation, intelligent traffic systems, etc., the current study of car-following behavior in mixed traffic has some limitations. Furthermore, actual data do not support its applicability to the Chinese traffic environment. To address this gap, this paper designs and organizes a car-following experiment in mixed traffic in Beijing, extracts the trajectory data of CAVs and HDVs based on video recognition, and reconstructs the extracted trajectory data using the Lagrangian theory and Kalman filter theory to ensure the accuracy of the data. Based on this data set, this paper develops an extended car-following model. The model considers the cooperation between drivers by reformulating the prospect theory (PT). The root mean square percentage error (RMSPE) is selected to calibrate and validate the parameters of the proposed model, and the results show that there is significant heterogeneity between CAVs and HDVs in mixed traffic, and the proposed model captures this heterogeneity well. The model presented in this paper provides theoretical support for microscopic traffic simulation in mixed traffic.

scholarly journals Introducing Road Surface Conditions into a Microscopic Traffic Simulation

10.29007/cqps ◽  
2019 ◽  
Author(s):  
Thomas Weber ◽  
Patrick Driesch ◽  
Dieter Schramm
Keyword(s):  
Traffic Simulation ◽  
Surface Condition ◽  
Road Surface ◽  
Automated Driving ◽  
Microscopic Traffic Simulation ◽  
Surface Conditions ◽  
Main Research ◽  
Car Following ◽  
The Road ◽  
Car Following Model

The introduction of highly automated driving functions is one of the main research and development efforts in the automotive industry worldwide. In the early stages of the development process, suppliers and manufacturers often wonder whether and to what extend the potential of the systems under development can be estimated in a cheap and timely manner. In the context of a current research project, a sensor system for the detection of the road surface condition is to be developed and it is to be investigated how such a system can be used to improve higher level driving functions. This paper presents how road surface conditions are introduced in various elements of the microscopic traffic simulation such as the actual network, the network editor, a device for detection, and an adaptation of the standard Krauß car following model. It is also shown how the adaptations can subsequently affect traffic scenarios. Furthermore, a summary is given how this preliminary work integrates into the larger scope of using SUMO as a tool in the process of analyzing the effectiveness of a road surface condition sensor.

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.

scholarly journals Microscopic Simulation of Cruising for Parking of Trucks as a Measure to Manage Freight Loading Zone

2019 ◽  
Vol 11 (5) ◽  
pp. 1276 ◽  
Author(s):  
Clélia Lopez ◽  
Chuan-Lin Zhao ◽  
Stéphane Magniol ◽  
Nicolas Chiabaut ◽  
Ludovic Leclercq
Keyword(s):  
Cost Function ◽  
Traffic Simulation ◽  
Microscopic Simulation ◽  
Microscopic Traffic Simulation ◽  
Research Results ◽  
The Real ◽  
Real Network ◽  
Last Mile ◽  
Simulation Based ◽  
The Relationship

This paper investigated economic truck parking behavior to implement comprehensive Freight Loading Zone (FLZ) policies. We assumed that the delivery trucks can only park on FLZ. The proposed contribution is to quantify the cruising for parking time of trucks. We used a microscopic traffic simulation based on a Manhattan network and the real network of Lyon (France). This paper explored the relationship between the searching time, the parking probabilities and the region’s parking density. Based on research results, an application to last mile cost function is proposed.

AN EXTENDED MACROSCOPIC MODEL FOR TRAFFIC FLOW ON A HIGHWAY WITH SLOPES

2013 ◽  
Vol 24 (09) ◽  
pp. 1350061 ◽  
Author(s):  
JIANZHONG CHEN ◽  
ZHONGKE SHI ◽  
YANMEI HU ◽  
LEI YU ◽  
YUAN FANG
Keyword(s):  
Traffic Flow ◽  
Small Perturbation ◽  
Gravitational Force ◽  
Slope Angle ◽  
Macroscopic Model ◽  
Car Following ◽  
Proposed Model ◽  
Car Following Model ◽  
Simulation Results ◽  
The Relationship

In this paper, we present an extended car-following model with consideration of the gravitational force. A new macroscopic model taking into account the slope effects is developed using the relationship between the microscopic and macroscopic variables. The proposed model is applied to reflect the effect of the slope on uniform flow, traffic waves and small perturbation. The simulation results demonstrate that both the angle and the length of the slope have important impacts on traffic flow. The effect of the slope becomes more significant with the increase of the slope angle.

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