Related papers: Supporting Car-Following Behavior through V2V-Base…
Vehicle pedestrian communication is extremely important when developing autonomy for an autonomous vehicle. Enabling bidirectional nonverbal communication between pedestrians and autonomous vehicles will lead to an improvement of…
Decentralized strategies are of interest for local decision-making over multi-vehicle networks. This paper studies mixed traffic networks of human-driven and autonomous vehicles with partial sensor measurements. The idea is to enable the…
As autonomous vehicles become more integrated into shared human environments, effective communication with road users is essential for ensuring safety. While previous research has focused on developing external Human-Machine Interfaces…
Vehicle-to-Vehicle (V2V) communication technology has dramatically promoted many promising applications to enhance traffic safety, mobility, and sustainability. However, However, we still lack the understanding of some fundamental…
This paper addresses the problem of human-based driver support. Nowadays, driver support systems help users to operate safely in many driving situations. Nevertheless, these systems do not fully use the rich information that is available…
Simulation is a crucial step in ensuring accurate, efficient, and realistic Connected and Autonomous Vehicles (CAVs) testing and validation. As the adoption of CAV accelerates, the integration of real-world data into simulation environments…
Traditionally, evaluation of intersection safety has been largely reactive, based on historical crash frequency data. However, the emerging data from Connected and Automated Vehicles (CAVs) can complement historical data and help in…
Idling vehicle detection (IVD) uses surveillance video and multichannel audio to localize and classify vehicles in the last frame as moving, idling, or engine-off in pick-up zones. IVD faces three challenges: (i) modality heterogeneity…
Increasing autonomous vehicles (AVs) in transportation systems makes effective interactions between AVs and pedestrians indispensable. External human--machine interface (eHMI), which employs visual or auditory cues to explicitly convey…
Vehicle-to-Infrastructure (V2I) collaborative perception leverages data collected by infrastructure's sensors to enhance vehicle perceptual capabilities. LiDAR, as a commonly used sensor in cooperative perception, is widely equipped in…
Human-centered dynamic scene understanding plays a pivotal role in enhancing the capability of robotic and autonomous systems, in which Video-based Human-Object Interaction (V-HOI) detection is a crucial task in semantic scene…
High data rate and low-latency vehicle-to-vehicle (V2V) communication are essential for future intelligent transport systems to enable coordination, enhance safety, and support distributed computing and intelligence requirements. Developing…
Recently, we developed a dynamic distributed end-to-end vehicle routing system (E2ECAV) using a network of intelligent intersections and level 5 CAVs (Djavadian & Farooq, 2018). The case study of the downtown Toronto Network showed that…
Humans can efficiently extract knowledge and learn skills from the videos within only a few trials and errors. However, it poses a big challenge to replicate this learning process for autonomous agents, due to the complexity of visual…
With the advent of Advanced Driver Assistance Systems (ADAS), there is an increasing need to evaluate driver behavior while using such technology. In this unique study, a forward collision warning (FCW) system using connected vehicle…
Connected and Autonomous Vehicles (CAVs) require continuous access to sensory data to perform complex high-speed maneuvers and advanced trajectory planning. High priority CAVs are particularly reliant on extended perception horizon…
Modern perception systems of autonomous vehicles are known to be sensitive to occlusions and lack the capability of long perceiving range. It has been one of the key bottlenecks that prevents Level 5 autonomy. Recent research has…
Recent advancements in connected autonomous vehicle (CAV) technology have sparked growing research interest in lane-free traffic (LFT). LFT envisions a scenario where all vehicles are CAVs, coordinating their movements without lanes to…
In transportation networks, intersections pose significant risks of collisions due to conflicting movements of vehicles approaching from different directions. To address this issue, various tools can exert influence on traffic safety both…
Assessing collision risk is a critical challenge to effective traffic safety management. The deployment of unmanned aerial vehicles (UAVs) to address this issue has shown much promise, given their wide visual field and movement flexibility.…