Decision-making of autonomous vehicles in interactions with jaywalkers: A risk-aware deep reinforcement learning approach
Jaywalking, as a hazardous crossing behavior, leaves little time for drivers to anticipate and
respond promptly, resulting in high crossing risks. The prevalence of Autonomous Vehicle …
respond promptly, resulting in high crossing risks. The prevalence of Autonomous Vehicle …
Advancing Vulnerable Road Users Safety: Interdisciplinary Review on V2X Communication and Trajectory Prediction
The advancements in Intelligent Transportation Systems have brought a heightened focus
on safety, driven by innovative solutions like Vehicle-to-Everything (V2X) communication …
on safety, driven by innovative solutions like Vehicle-to-Everything (V2X) communication …
Identifying dynamic interaction patterns in mandatory and discretionary lane changes using graph structure
A quantitative understanding of dynamic lane‐changing interaction patterns is
indispensable for improving the decision‐making of autonomous vehicles (AVs), especially …
indispensable for improving the decision‐making of autonomous vehicles (AVs), especially …
[HTML][HTML] Real-time traffic conflict prediction at signalized intersections using vehicle trajectory data and deep learning
Real-time conflict prediction at signalized intersections is crucial for urban road safety
management. This study developed a real-time conflict prediction framework for signalized …
management. This study developed a real-time conflict prediction framework for signalized …
Deep learning-based pedestrian trajectory prediction and risk assessment at signalized intersections using trajectory data captured through roadside LiDAR
In recent years, rapid advancements in the Autonomous Vehicles (AVs) industry have
greatly motivated the research and development in pedestrian trajectory prediction and risk …
greatly motivated the research and development in pedestrian trajectory prediction and risk …
Incremental learning-based real-time trajectory prediction for autonomous driving via sparse gaussian process regression
In the context of spatial-temporal autonomous driving, the accurate and real-time trajectory
prediction of the surrounding vehicle (SV) is crucial. This paper aims to design an efficient …
prediction of the surrounding vehicle (SV) is crucial. This paper aims to design an efficient …
Adaptive risk tendency in uncertainty-aware motion planning using risk-sensitive Reinforcement Learning
As the most vulnerable road users, pedestrians demand particular safety guarantees in
driving tasks. This work designs a hierarchical motion planning framework for active …
driving tasks. This work designs a hierarchical motion planning framework for active …
Pedestrian warning: Intelligent vision sensor vs. edge ai with LTE C-V2X in a smart city
Unlocking the Potential of Smart Cities: Our paper details a groundbreaking field test
validating the direct camera-to-RSU connection in a C-V2X pedestrian warning scenario. By …
validating the direct camera-to-RSU connection in a C-V2X pedestrian warning scenario. By …
Enhancing Vehicle Sensing for Traffic Safety and Mobility Performance Improvements Using Roadside LiDAR Sensor Data
Recent technological advancements in computer vision algorithms and data acquisition
devices have greatly facilitated research activities towards enhancing traffic sensing for …
devices have greatly facilitated research activities towards enhancing traffic sensing for …