Advances and applications of computer vision techniques in vehicle trajectory generation and surrogate traffic safety indicators
Abstract The application of Computer Vision (CV) techniques massively stimulates
microscopic traffic safety analysis from the perspective of traffic conflicts and near misses …
microscopic traffic safety analysis from the perspective of traffic conflicts and near misses …
CitySim: a drone-based vehicle trajectory dataset for safety-oriented research and digital twins
O Zheng, M Abdel-Aty, L Yue… - Transportation …, 2024 - journals.sagepub.com
The development of safety-oriented research and applications requires fine-grain vehicle
trajectories that not only have high accuracy, but also capture substantial safety-critical …
trajectories that not only have high accuracy, but also capture substantial safety-critical …
A temporal multi-gate mixture-of-experts approach for vehicle trajectory and driving intention prediction
R Yuan, M Abdel-Aty, Q Xiang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Accurate vehicle trajectory prediction is critical for autonomous vehicles and advanced
driver assistance systems to make driving decisions and improve traffic safety. This paper …
driver assistance systems to make driving decisions and improve traffic safety. This paper …
A physical law constrained deep learning model for vehicle trajectory prediction
Vehicle trajectory prediction is crucial and indispensable for ensuring the safe and efficient
operation of autonomous vehicles in complex traffic environments. The application of …
operation of autonomous vehicles in complex traffic environments. The application of …
Interaction-aware personalized vehicle trajectory prediction using temporal graph neural networks
A Abdelraouf, R Gupta, K Han - 2023 IEEE 26th International …, 2023 - ieeexplore.ieee.org
Accurate prediction of vehicle trajectories is vital for advanced driver assistance systems and
autonomous vehicles. Existing methods mainly rely on generic trajectory predictions derived …
autonomous vehicles. Existing methods mainly rely on generic trajectory predictions derived …
KI-GAN: Knowledge-Informed Generative Adversarial Networks for Enhanced Multi-Vehicle Trajectory Forecasting at Signalized Intersections
Reliable prediction of vehicle trajectories at signalized intersections is crucial to urban traffic
management and autonomous driving systems. However it presents unique challenges due …
management and autonomous driving systems. However it presents unique challenges due …
Personalized trajectory prediction for driving behavior modeling in ramp-merging scenarios
Despite numerous studies on trajectory prediction, existing approaches often fail to
adequately capture the multifaceted and individual nature of driving behavior. In recognition …
adequately capture the multifaceted and individual nature of driving behavior. In recognition …
VIF-GNN: A Novel Agent Trajectory Prediction Model based on Virtual Interaction Force and GNN
Agent trajectory prediction of traffic scenarios is a significant module of environment
reasoning and autonomous vehicle decision, and the core challenge is the ability to …
reasoning and autonomous vehicle decision, and the core challenge is the ability to …
Proactive safety analysis using roadside LiDAR based vehicle trajectory data
N Bhattarai - 2023 - ttu-ir.tdl.org
The underlying weaknesses of crash data have led to the shift of traffic safety analysis from
reactive to proactive approaches. Using conflicts/near-crashes as crash surrogates is the …
reactive to proactive approaches. Using conflicts/near-crashes as crash surrogates is the …