Modeling the Car-Following Behavior with Consideration of Driver, Vehicle, and Environment Factors: A Historical Review

Abstract

Car-following behavior is the result of the interaction of various elements in the specific driver-vehicle-environment aggregation. Under the intelligent and connected condition, the information perception ability of vehicles has been significantly enhanced, and abundant information about the driver-vehicle-environment factors can be obtained and utilized to study car-following behavior. Therefore, it is necessary to comprehensively take into account the driver-vehicle-environment factors when modeling car-following behavior under intelligent and connected conditions. While there are a considerable number of achievements in research on car-following behavior, a car-following model with comprehensive consideration of driver-vehicle-environment factors is still absent. To address this gap, the literature with a focus on car-following behavior research with consideration of the driver, vehicle, or environment were reviewed, the contributions and limitations of the previous studies were analyzed, and the future exploration needs and prospects were discussed in this paper. The results can help understand car-following behavior and the traffic flow characteristics affected by various factors and provide a reference for the development of traffic flow theory towards smart transportation systems and intelligent and connected driving.

Vehicle Driving Behavior Analysis and Unified Modeling in Urban Road Scenarios

“…Several classical models, such as the optimal velocity (OV) model and the Gipps model, are often extended into microscopic traffic flow models for various driving scenarios [15][16][17][18][19]. Since these models have different assumptions and dynamic characteristics, how to incorporate the influence of external factors on driver behavior into the model by using a reasonable method, in conjunction with the application scenarios, has always been one of the main concerns of micro traffic flow research scholars over the years [20]. Due to the high separation of the existing microscopic traffic flow model system between the following model and the lane-changing model, most models only simulate the behavioral mechanism of a single driver, and the model variables are measured from the driver's perspective, so the calibrated model parameters reflect the behavioral characteristics of a single driver.…”

Intelligent Driver Model-Based Vehicular Ad Hoc Network Communication in Real-Time Using 5G New Radio Wireless Networks

“…Li et al [11] proposed a two-lane highway overtaking the safe distance model. Han et al [12] improved the safe distance car-following model based on the optimal speed model. Aparow et al [13] systematically described an automatic generation method for autonomous driving simulation scenarios.…”

A Hierarchical Framework of Decision Making and Trajectory Tracking Control for Autonomous Vehicles

“…With the increasing development of sensor and communication engineering, the AV has been brought to the forefront, due to its great potential for improving traffic safety, efficiency and energy reduction [1,2]. A significant factor in the development of the AV has been the annual Defense Advanced Research Projects Agency (DARPA) Grand Challenge, from whence AV has received great interest from academia, governments and industry [3].…”

“…The framework considers that the driving environment consists of multi-lane curved roads and multiple surrounding vehicles. (2) The FSM is utilized to determine the reasonable driving maneuver based on the relative safe distance and speed between the EV and surrounding vehicles under the constrained traffic conditions. (3)…”