相关论文: Supporting Car-Following Behavior through V2V-Base…

Driving information and data under potential vehicle crashes create opportunities for extensive real-world observations of driver behaviors and relevant factors that significantly influence the driving safety in emergency scenarios.…

As autonomous vehicles are gradually being deployed in the real world, external Human-Machine Interfaces (eHMIs) are expected to serve as a critical solution for enhancing vehicle-pedestrian communication. However, existing eHMI designs…

Highway merging scenarios featuring mixed traffic conditions pose significant modeling and control challenges for connected and automated vehicles (CAVs) interacting with incoming on-ramp human-driven vehicles (HDVs). In this paper, we…

The recent advancements in wireless technology enable connected autonomous vehicles (CAVs) to gather data via vehicle-to-vehicle (V2V) communication, such as processed LIDAR and camera data from other vehicles. In this work, we design an…

Autonomous driving systems often infer pedestrian yielding behavior from geometric and kinematic cues alone, limiting their ability to reason about visual scene context and age-dependent behavioral variability. This limitation can produce…

The rapid adoption of autonomous vehicle has established mixed traffic environments, comprising both autonomous and human-driven vehicles (HDVs), as essential components of next-generation mobility systems. Along these lines, connectivity…

The emerging technology of Vehicle-to-Vehicle (V2V) communication over vehicular ad hoc networks promises to improve road safety by allowing vehicles to autonomously warn each other of road hazards. However, research on other transportation…

Given the rapid advance in ITS technologies, future mobility is pointing to vehicular autonomy. However, there is still a long way before full automation, and human intervention is required. This work sheds light on understanding human…

Automated vehicles (AVs) must communicate their yielding intentions to pedestrians at crossings. External Human-Machine Interfaces (eHMIs, on-vehicle displays) are promising solutions, but were primarily tested with walking pedestrians.…

Drivers' perception of risky situations has always been a challenge in driving. Existing risk-detection methods excel at identifying collisions but face challenges in assessing the behavior of road users in non-collision situations. This…

This study evaluates the performance of Vehicle-to-Vehicle Visible Light Communication in dynamic environments, focusing on the effects of speed, horizontal offset, and other factors on communication reliability. Using On-Off Keying…

Among all types of crashes, rear-end crashes dominate, which are closely related to the car-following (CF) behaviors. Traditional CF behavior models focused on the influence of the vehicle in front, but usually ignored the peer pressure…

Many car accidents are caused by human distractions, including cognitive distractions. In-vehicle human-machine interfaces (HMIs) have evolved throughout the years, providing more and more functions. Interaction with the HMIs can, however,…

Vehicle-to-vehicle (V2V) communications have a great potential to improve traffic system performance. Most existing work of connected and autonomous vehicles (CAVs) focused on adaptation to downstream traffic conditions, neglecting the…

Infrastructure-to-Vehicle (I2V) and Vehicle-to-Infrastructure (V2I) communication is likely to be a key-enabling technology for automated driving in the future. Using externally placed sensors, the digital infrastructure can support the…

Pedestrian occlusion is challenging for autonomous vehicles (AVs) at midblock locations on multilane roadways because an AV cannot detect crossing pedestrians that are fully occluded by downstream vehicles in adjacent lanes. This paper…

Connected and automated vehicles (CAVs) have recently gained prominence in traffic research due to advances in communication technology and autonomous driving. Various longitudinal control strategies for CAVs have been developed to enhance…

This paper presents a LiDAR-based end-to-end autonomous driving method with Vehicle-to-Everything (V2X) communication integration, termed V2X-Lead, to address the challenges of navigating unregulated urban scenarios under mixed-autonomy…

Connected automated vehicles (CAVs) have brought new opportunities to improve traffic throughput and reduce energy consumption. However, the uncertain lane-change behaviors (LCBs) of surrounding vehicles (SVs) as an uncontrollable factor…

Given pedestrians' vulnerability in road traffic, it remains unclear how novel AV appearances will impact pedestrians crossing behaviour. To address this gap, this study pioneers an investigation into the influence of AVs' exterior design,…