Mobile Trajectory Anomaly Detection: Taxonomy, Methodology, Challenges, and Directions

X Kong, J Wang, Z Hu, Y He, X Zhao… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
The growing number of cars on city roads has led to an increase in traffic accidents,
highlighting the need for traffic safety measures. Mobile trajectory anomaly detection is an …

[HTML][HTML] Modeling collision risk for unsafe lane-changing behavior: A lane-changing risk index approach

MS Sheikh, Y Peng - Alexandria Engineering Journal, 2024 - Elsevier
The lane-changing maneuvers are challenging and contributes to traffic accidents and
crashes. They are complicated task that often lead to an increased risk of vehicle collisions …

Sensors-enabled autonomous computational intelligence vehicle model with QoS-driven communication services

K Haseeb, A Rehman, A Ara, A Khan… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
Edge computing is integrated with various physical and computational components in
autonomous networks to develop transportation systems. These systems can gather data …

Experimental Evaluation of a Head-On Collision Warning System Fusing Machine Learning and Decentralized Radio Sensing

JD Cárdenas, MAD Ibarra… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
This paper presents the idea of an automatic head-on-collision warning system based on a
decentralized radio sensing (RS) approach. In this framework, a vehicle in receiving mode …

Systematic Selective Limits Application Using Decision Making Engines to Enhance Safety in Highly Automated Vehicles

D Garikapati, Y Liu, Z Huo - 2024 - preprints.org
Safety limits application has always been a traditional approach to ensure the safe operation
of electro-mechanical systems within many industries including automated vehicles …