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Found 11 papers, 3 papers with code
Lane-Wise Highway Anomaly Detection
This paper proposes a scalable and interpretable framework for lane-wise highway traffic anomaly detection, leveraging multi-modal time series data extracted from surveillance cameras.
On-Board Vision-Language Models for Personalized Autonomous Vehicle Motion Control: System Design and Real-World Validation
Personalized driving refers to an autonomous vehicle's ability to adapt its driving behavior or control strategies to match individual users' preferences and driving styles while maintaining safety and comfort standards.
Large Language Models for Autonomous Driving (LLM4AD): Concept, Benchmark, Experiments, and Challenges
Our research highlights the significant potential of LLMs to enhance various aspects of autonomous vehicle technology, from perception and scene understanding to language interaction and decision-making.
Optimizing ROI Benefits Vehicle ReID in ITS
Tracked vehicle images were cropped from inside and outside the ROIs at five-frame intervals.
Enhancing Vehicle Re-identification and Matching for Weaving Analysis
Vehicle weaving on highways contributes to traffic congestion, raises safety issues, and underscores the need for sophisticated traffic management systems.
Personalized Autonomous Driving with Large Language Models: Field Experiments
We also validate that the proposed memory module considers personalized preferences and further reduces the takeover rate by up to 65. 2% compared with those without a memory module.
A New Scoring Method for the Evaluation of Vehicle Road Departure Detection Systems
Road departure detection systems (RDDSs) for eliminating unintentional road departure collisions have been developed and equipped on some commercial vehicles in recent years.
Risk assessment and mitigation of e-scooter crashes with naturalistic driving data
The goal is to quantitatively measure the behaviors of e-scooter riders in different encounters to help facilitate crash scenario modeling, baseline behavior modeling, and the potential future development of in-vehicle mitigation algorithms.
A Method for Crash Prediction and Avoidance Using Hidden Markov Models
In particular, hidden Markov models are developed for the traffic lanes and speed change of vehicles on highway.
A Wearable Data Collection System for Studying Micro-Level E-Scooter Behavior in Naturalistic Road Environment
As one of the most popular micro-mobility options, e-scooters are spreading in hundreds of big cities and college towns in the US and worldwide.
PSI: A Pedestrian Behavior Dataset for Socially Intelligent Autonomous Car
These innovative labels can enable several computer vision tasks, including pedestrian intent/behavior prediction, vehicle-pedestrian interaction segmentation, and video-to-language mapping for explainable algorithms.
