With the rising popularity of the Advanced Driver Assistance System (ADAS), there is an increasing demand for more human-like car-following performance. In this paper, we consider the role of heterogeneity in car-following behavior within car-followi...
This study aims to improve the desired distance adaptability of the cooperative adaptive cruise control (CACC) during car-following. In this study, the characteristics of the desired distance in different traffic flow states were analyzed. The genera...
To explore the potential relationship between the leading vehicle and the following vehicle during car-following, we proposed a novel car-following model combining a convolutional neural network (CNN) with a long short-term memory (LSTM) network. Fir...
21 December 2022
Driver’s behavior characteristics (DBCs) influence car-following safety. Therefore, this paper aimed to analyze the effect of different DBCs on the car-following safety based on the desired safety margin (DSM) car-following model, which include...
The application of vehicle-to-everything (V2X) technology has resulted in the traffic environment being different from how it was in the past. In the V2X environment, the information perception ability of the driver–vehicle unit is greatly enha...
Traffic breakdown refers to the first-order transition from free flow to synchronized flow. It is characterized by a rapid decrease in speed, suddenly increasing density, and abruptly plummeting capacity in most of the relevant observations. To under...
The dramatic progress of Intelligent Transportation Systems (ITS) has made autodriving technology extensively emphasised. Various models have been developed for the aim of modelling the behaviour of autonomous vehicles and their impacts on traffic, a...
Despite the significant impact of network hyperparameters on deep learning car-following models, there has been relatively little research on network hyperparameters of deep learning car-following models. Therefore, this study proposes a car-followin...
In intelligent transportation systems, vehicles can obtain more information, and the interactivity between vehicles can be improved. Therefore, it is necessary to study car-following behavior during the introduction of intelligent traffic information...
Building a human-like car-following model that can accurately simulate drivers’ car-following behaviors is helpful to the development of driving assistance systems and autonomous driving. Recent studies have shown the advantages of applying rei...
Car-following models are used in microscopic simulation tools to calculate the longitudinal acceleration of a vehicle based on the speed and position of a leading vehicle in the same lane. Bicycle traffic is usually included in microscopic traffic si...
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 e...
The lateral control of the vehicle is significant for reducing the rollover risk of high-speed cars and improving the stability of the following vehicle. However, the existing car-following (CF) models rarely consider lateral control. Therefore, a CF...
To systematically study the influence of a propensity for a particular driving style on car-following risk, a safety potential field risk-quantification method that considers driving style is proposed. First, we classify driving behaviors and constru...
For the coupling problem of longitudinal control and lateral control of vehicles, a two-dimensional (2-D) car-following control strategy for an electric vehicle is proposed in this paper. First, a 2-D car-following model for longitudinal following an...
Car-following models are crucial in adaptive cruise control systems, making them essential for developing intelligent transportation systems. This study investigates the characteristics of high-speed traffic flow by analyzing the relationship between...
With the development of the drive of electronic communication technology, the driving assistance system that perceives the external traffic environment has developed rapidly. However, when quantifying the complexity of the road traffic environment wi...
With the rapid development of information and communication technology, future intelligent transportation systems will exhibit a trend of cooperative driving of connected vehicles. Platooning is an important application technique for cooperative driv...
With the development of intelligent connected vehicles (ICVs) and communication technology, collaborative operation among vehicles will become the trend of the future. Thus, traffic flow will be mixed with manual driving vehicles and ICVs. A mixed tr...
In this paper, a car-following model considering the preceding vehicle type is proposed to describe the longitudinal driving behavior closer to reality. Based on the naturalistic driving data sampled in real traffic for more than half a year, the rel...
This paper proposes a novel hybrid car-following model: the physics-informed conditional generative adversarial network (PICGAN), designed to enhance multi-step car-following modeling in mixed traffic flow scenarios. This hybrid model leverages the s...
The application of intelligent and connected technologies, such as vehicle-to-everything (V2X), profoundly influences car-following behavior and traffic flow characteristics. While empirical studies have demonstrated that the car-following behavior i...
Vehicle-to-everything (V2X) technology will significantly enhance the information perception ability of drivers and assist them in optimizing car-following behavior. Utilizing V2X technology, drivers could obtain motion state information of the front...
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...
Although the difference between the velocity of two successive vehicles is considered in the full velocity difference model (FVDM), more status information from preceding vehicles affecting the behavior of car-following has not been effectively utili...
Fine-grained modeling of driving styles is critical for decision making in autonomous driving. However, existing methods are constrained by the high cost of manual labeling and a lack of interpretability. This study proposes an unsupervised disentang...
This study aims to examine the differences in drivers’ reaction time (RTs) while driving on horizontal curves and straight roadway segments, among different driver classes, and in different driving environments to better understand human driver...
This paper investigates a car-following model that incorporates both classical and fractional discrete operators. While classical models have been extensively studied, the influence of discrete fractional operators on the stability of such systems ha...
Although a lot of work has been conducted on car-following modeling, model calibration and validation are still a great challenge, especially in the era of autonomous driving. Most challengingly, besides the immediate benefit incurred with a car-foll...
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 (...
The contribution of autonomous vehicles to traffic is one of the key aspects of future ground transportation in smart cities. Autonomous vehicles are able to provide many benefits, but some benefits can only provide advantages if these vehicles compr...
In this paper, an economy-oriented car-following control (EOCFC) strategy is proposed for electric vehicles in car-following scenarios. Specifically, a controller based on model predictive control (MPC) is developed to optimize the host vehicle&rsquo...
To address traffic congestion in urban expressways during the transition from wide to narrow sections, this study proposed a car-following strategy based on deep reinforcement learning. Firstly, a car-following strategy was developed based on a twin-...
Connected and Automated Vehicles (CAV) have been rapidly developed, which, inevitably, renders that human-driven and autonomous vehicles share the road. Thus, trajectory prediction is an important research topic, which helps each CAV to efficiently f...
The type of vehicles in realistic traffic systems are not homogeneous. Impacts of the preceding vehicle’s type on the car-following behavior, fuel consumption and exhaust emissions are still unclear. This paper presents a study on the impacts o...
In normal car-following (CF) states, the minimum safe braking distance (MSBD) is virtually an unmeasurable variable, mainly due to the diversity of drivers’ reaction times and vehicles’ braking performance. The average MSBD regarding the...
This study proposes a new method to improve the accuracy of car-following models in predicting the mobility of mixed traffic flow involving trucks and automated vehicles (AVs). A classification is developed to categorize car-following behaviors into...
Under the development of intelligent network technology, drivers can obtain the surrounding traffic situation in real time, which is conducive to improving the stability of traffic flow. Therefore, this paper proposes a new curve-car-following model...
The transition to intelligent transportation systems (ITSs) is necessary to improve traffic flow in urban areas and reduce traffic congestion. Traffic modeling simplifies the understanding of the traffic paradigm and helps researchers to estimate tra...
This study proposes an adaptive car-following model based on the unscented Kalman filter algorithm to enable coordinated speed control in vehicle platoons and to address key limitations present in conventional car-following models. Traditional models...
With the continuous advancement of electronic technology, auto parts manufacturing institutions are gradually applying electronic throttles to automobiles for precise control. Based on the visual angle model (VAM), a car-following model considering t...
On highways, it is commonplace to observe car-following behavior among vehicles. Unfortunately, this behavior results in significant particulate matter (PM) emissions, which greatly contribute to environmental pollution. Additionally, adverse weather...
This paper addresses the modeling challenge of significant asymmetry between acceleration and deceleration processes in car-following behavior by proposing an Asymmetric Acceleration and Deceleration Car Following (AAD-CF) model. The model characteri...
The car-following model (CFM) utilizes intelligent transportation systems to gather comprehensive vehicle travel information, enabling an accurate description of vehicle driving behavior. This offers valuable insights for designing autonomous vehicle...
One of the current topics of interest in transportation science is the use of intelligent computation and IoT (Internet of Things) technologies. Researchers have proposed many approaches using these concepts, but the most widely used concept in road...
Concerning roadside traffic detection applications, and to address the millimeter-wave radar’s missing data problem caused by target occlusion or the absence of features in low-speed conditions, this paper proposes a trajectory compensation met...
Accurate modeling of car-following behavior is essential for understanding traffic dynamics and enabling predictive control in intelligent transportation systems. This study presents a novel data-driven framework that combines information-theoretic i...
Reinforcement learning (RL)–based car-following (CF) control strategies have attracted significant attention in academia, emerging as a prominent research topic in recent years. Most of these control strategies focus solely on the motion status...
To characterize the dynamic interaction properties of heterogeneous traffic flow in the complex human–vehicle–road environment and to enhance the safety and efficiency of connected autonomous vehicles (CAVs), this study analyzes the self-...
The development of the Connected and Autonomous Vehicle (CAV) and Hybrid Electric Vehicle (HEV) provides a new effective means for the optimization of eco-driving strategies. However, the existing research has not effectively considered the cooperati...
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