Related papers: Exploratory Driving Performance and Car-Following …
Adaptive cruise control (ACC) vehicles are the first step toward comprehensive vehicle automation. However, the impacts of such vehicles on the underlying traffic flow are not yet clear. Therefore, it is of interest to accurately model…
Connectivity in ground vehicles allows vehicles to share crucial vehicle data, such as vehicle acceleration, with each other. Using sensors such as cameras, radars and lidars, on the other hand, the intravehicular distance between a leader…
This paper investigates the accuracy and robustness of car-following (CF) and adaptive cruise control (ACC) models used to simulate measured driving behaviour of commercial ACCs. To this aim, a general modelling framework is proposed, in…
This paper presents a comprehensive review of trajectory data of Advanced Driver Assistance System equipped-vehicle, with the aim of precisely model of Autonomous Vehicles (AVs) behavior. This study emphasizes the importance of trajectory…
In this simulator study, we adopt a human-centered approach to explore whether and how drivers' cognitive state and driving environment complexity influence reliance on driving automation features. Besides, we examine whether such reliance…
Autonomous driving services rely heavily on sensors such as cameras, LiDAR, radar, and communication modules. A common practice of processing the sensed data is using a high-performance computing unit placed inside the vehicle, which…
Learning-based controllers have achieved impressive performance in agile quadrotor flight but typically rely on massive training in simulation, necessitating accurate system identification for effective Sim2Real transfer. However, even with…
Automated driving systems (ADSs) promise a safe, comfortable and efficient driving experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The full potential of ADSs cannot be realized unless the robustness of…
Vehicle control algorithms exploiting connectivity and automation, such as Connected and Automated Vehicles (CAVs) or Advanced Driver Assistance Systems (ADAS), have the opportunity to improve energy savings. However, lower levels of…
Two new methods are presented for estimating car-following model parameters using data collected from the Adaptive Cruise Control (ACC) enabled vehicles. The vehicle is assumed to follow a constant time headway relative velocity model in…
Automated vehicles are gradually entering people's daily life to provide a comfortable driving experience for the users. The generic and user-agnostic automated vehicles have limited ability to accommodate the different driving styles of…
Deployed SAE level 4+ Automated Driving Systems (ADS) without a human driver are currently operational ride-hailing fleets on surface streets in the United States. This current use case and future applications of this technology will…
This work describes the use of on-board vehicle data from cars with advanced driver assistance features as a trip summary, with the goal of helping drivers contextualize their driving habits in terms of sustainability. The approach is…
Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS) are expected to improve comfort, productivity and, most importantly, safety for all road users. To ensure that the systems are safe, rules and regulations…
Accurate lane change prediction can reduce potential accidents and contribute to higher road safety. Adaptive cruise control (ACC), lane departure avoidance (LDA), and lane keeping assistance (LKA) are some conventional modules in advanced…
Automated Driving Systems (ADSs) have seen rapid progress in recent years. To ensure the safety and reliability of these systems, extensive testings are being conducted before their future mass deployment. Testing the system on the road is…
A rather simple car driving simulator was created based on the available open source engine TORCS and used to analyze the basic features of human behavior in car driving within the car-following setups. Eight subjects with different skill…
The development of Autonomous Vehicles (AVs) has redefined the way of transportation by eliminating the need for human intervention in driving. This revolution is fueled by rapid advancements in adaptive cruise control (ACC), which make AVs…
Insight into individual driving behavior and habits is essential in traffic operation, safety, and energy management. With Connected Vehicle (CV) technology aiming to address all three of these, the identification of driving patterns is a…
Autonomated vehicles (AVs) are expected to have a profound impact on society, with high expectations for their potential benefits. One key anticipated benefit is the reduction of traffic congestion and stop-and-go waves, which negatively…