scholarly journals A Review of Car-Following Models and Modeling Tools for Human and Autonomous-Ready Driving Behaviors in Micro-Simulation

Smart Cities ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 314-335
Author(s):  
Hafiz Usman Ahmed ◽  
Ying Huang ◽  
Pan Lu
Keyword(s):  
Autonomous Vehicles ◽  
Adaptive Cruise Control ◽  
Cruise Control ◽  
Modeling Tools ◽  
Microscopic Traffic Simulation ◽  
Simulation Tools ◽  
Car Following ◽  
Driving Behaviors ◽  
Micro Simulation ◽  
Models And Modeling

The platform of a microscopic traffic simulation provides an opportunity to study the driving behavior of vehicles on a roadway system. Compared to traditional conventional cars with human drivers, the car-following behaviors of autonomous vehicles (AVs) and connected autonomous vehicles (CAVs) would be quite different and hence require additional modeling efforts. This paper presents a thorough review of the literature on the car-following models used in prevalent micro-simulation tools for vehicles with both human and robot drivers. Specifically, the car-following logics such as the Wiedemann model and adaptive cruise control technology were reviewed based on the vehicle’s dynamic behavior and driving environments. In addition, some of the more recent “AV-ready (autonomous vehicles ready) tools” in micro-simulation platforms are also discussed in this paper.

Autonomous Vehicles’ Car-Following Drivability Evaluation Based on Driving Behavior Spectrum Reference Model

2021 ◽  
pp. 036119812199485
Author(s):  
Xiao Qi ◽  
Ying Ni ◽  
Yiming Xu ◽  
Ye Tian ◽  
Junhua Wang ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Reference Model ◽  
Numerical Test ◽  
Safety Evaluation ◽  
Driving Behavior ◽  
Car Following ◽  
Driving Behaviors ◽  
Human Driver ◽  
Normal Human ◽  
Naturalistic Driving

A large portion of the accidents involving autonomous vehicles (AVs) are not caused by the functionality of AV, but rather because of human intervention, since AVs’ driving behavior was not properly understood by human drivers. Such misunderstanding leads to dangerous situations during interaction between AV and human-driven vehicle (HV). However, few researches considered HV-AV interaction safety in AV safety evaluation processes. One of the solutions is to let AV mimic a normal HV’s driving behavior so as to avoid misunderstanding to the most extent. Therefore, to evaluate the differences of driving behaviors between existing AV and HV is necessary. DRIVABILITY is defined in this study to characterize the similarity between AV’s driving behaviors and expected behaviors by human drivers. A driving behavior spectrum reference model built based on human drivers’ behaviors is proposed to evaluate AVs’ car-following drivability. The indicator of the desired reaction time (DRT) is proposed to characterize the car-following drivability. Relative entropy between the DRT distribution of AV and that of the entire human driver population are used to quantify the differences between driving behaviors. A human driver behavior spectrum was configured based on naturalistic driving data by human drivers collected in Shanghai, China. It is observed in the numerical test that amongst all three types of preset AVs in the well-received simulation package VTD, the brisk AV emulates a normal human driver to the most extent (ranking at 55th percentile), while the default AV and the comfortable AV rank at 35th and 8th percentile, respectively.

Evaluation of Driver Car-Following Behavior Models for Cooperative Adaptive Cruise Control Systems

2017 ◽  
Vol 2622 (1) ◽  
pp. 84-95 ◽  
Author(s):  
Mizanur Rahman ◽  
Mashrur Chowdhury ◽  
Kakan Dey ◽  
M. Rafiul Islam ◽  
Taufiquar Khan
Keyword(s):  
Vehicle Dynamics ◽  
Adaptive Cruise Control ◽  
User Acceptance ◽  
Evaluation Framework ◽  
Cruise Control ◽  
String Stability ◽  
Maximum Acceleration ◽  
Car Following ◽  
Cooperative Adaptive Cruise Control ◽  
Behavior Models

A cooperative adaptive cruise control (CACC) system targeted to obtain a high level of user acceptance must replicate the driving experience in each CACC vehicle without compromising the occupant’s comfort. “User acceptance” can be defined as the safety and comfort of the occupant in the CACC vehicle in terms of acceptable vehicle dynamics (i.e., the maximum acceleration or deceleration) and string stability (i.e., the fluctuations in the vehicle’s position, speed, and acceleration). The primary objective of this study was to develop an evaluation framework for the application of a driver car-following behavior model in CACC system design to ensure user acceptance in terms of vehicle dynamics and string stability. The authors adopted two widely used driver car-following behavior models, ( a) the optimum velocity model (OVM) and ( b) the intelligent driver model (IDM), to prove the efficacy of the evaluation framework developed in this research for CACC system design. A platoon of six vehicles was simulated for three traffic flow states (uniform speed, speed with constant acceleration, and speed with constant deceleration) with different acceleration and deceleration rates. The maximum acceleration or deceleration and the sum of the squares of the errors of the follower vehicle speed were measured to evaluate user acceptance in terms of vehicle dynamics and string stability. Analysis of the simulation results revealed that the OVM performed better at modeling a CACC system than did the IDM in terms of acceptable vehicle dynamics and string stability.

scholarly journals Time-delay feedback cooperative adaptive cruise control of connected vehicles by heterogeneous channel transmission

2019 ◽  
Vol 52 (5-6) ◽  
pp. 369-378 ◽  
Author(s):  
Xiulan Song ◽  
Xiaoxin Lou ◽  
Limin Meng
Keyword(s):  
Time Delay ◽  
Autonomous Vehicles ◽  
Adaptive Cruise Control ◽  
Sufficient Conditions ◽  
Wireless Channel ◽  
Linear Matrix ◽  
Connected Vehicle ◽  
Cruise Control ◽  
Cooperative Adaptive Cruise Control ◽  
Vehicle Platoon

In this paper, we consider the cooperative adaptive cruise control problem of connected autonomous vehicles networked by heterogeneous wireless channel transmission. The cooperative adaptive cruise control model with variable input delays is established to describe the varying time-delays induced from vehicular actuators and heterogeneous channel transmission. Then a set of decentralized time-delay feedback cooperative adaptive cruise control controllers is computed in such way that each vehicle evaluates its own adaptive cruise control strategy using only neighborhood information. In order to establish string stability of the connected vehicle platoon with the decentralized controllers, the sufficient conditions are obtained in the form of linear matrix inequalities. The scenarios, consisting of four different cars with three heterogeneous wireless channels, are used to demonstrate the effectiveness of the presented method.

Improved Adaptive Cruise Control for Autonomous Vehicles with Consideration of Crash Avoidance

2021 ◽  
Author(s):  
Yu Zhang ◽  
Yunfeng Chu ◽  
Mingming Dong ◽  
Li Gao ◽  
Yechen Qin ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Adaptive Cruise Control ◽  
Cruise Control ◽  
Crash Avoidance

scholarly journals Safety problems in vehicles with adaptive cruise control system

2017 ◽  
Vol 42 (1) ◽  
pp. 389-398 ◽  
Author(s):  
Arun K. Yadav ◽  
Janusz Szpytko
Keyword(s):  
Control System ◽  
Autonomous Vehicles ◽  
Adaptive Cruise Control ◽  
Main Concern ◽  
Cruise Control ◽  
Adaptive Cruise Control System ◽  
Cruise Control System ◽  
Preceding Vehicle ◽  
Driving Stability ◽  
Autonomous Technology

Abstract In today’s world automotive industries are still putting efforts towards more autonomous vehicles (AVs). The main concern of introducing the autonomous technology is safety of driver. According to a survey 90% of accidents happen due to mistake of driver. The adaptive cruise control system (ACC) is a system which combines cruise control with a collision avoidance system. The ACC system is based on laser and radar technologies. This system is capable of controlling the velocity of vehicle automatically to match the velocity of car, bus or truck in front of vehicle. If the lead vehicle gets slow down or accelerate, than ACC system automatically matches that velocity. The proposed paper is focusing on more accurate methods of detecting the preceding vehicle by using a radar and lidar sensors by considering the vehicle side slip and by controlling the distance between two vehicles. By using this approach i.e. logic for calculation of former vehicle distance and controlling the throttle valve of ACC equipped vehicle, an improvement in driving stability was achieved. The own contribution results with fuel efficient driving and with more safer and reliable driving system, but still some improvements are going on to make it more safe and reliable.

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