Search Results for author:
Found 9 papers, 3 papers with code
Traffic Control via Connected and Automated Vehicles: An Open-Road Field Experiment with 100 CAVs
The upper layer is called Speed Planner, and is a centralized optimal control algorithm.
Virtual trajectories for I-24 MOTION: data and tools
This article introduces a new virtual trajectory dataset derived from the I-24 MOTION INCEPTION v1. 0. 0 dataset to address challenges in analyzing large but noisy trajectory datasets.
MARVEL: Multi-Agent Reinforcement-Learning for Large-Scale Variable Speed Limits
Variable Speed Limit (VSL) control acts as a promising highway traffic management strategy with worldwide deployment, which can enhance traffic safety by dynamically adjusting speed limits according to real-time traffic conditions.
So you think you can track?
This work introduces a multi-camera tracking dataset consisting of 234 hours of video data recorded concurrently from 234 overlapping HD cameras covering a 4. 2 mile stretch of 8-10 lane interstate highway near Nashville, TN.
The Interstate-24 3D Dataset: a new benchmark for 3D multi-camera vehicle tracking
This work presents a novel video dataset recorded from overlapping highway traffic cameras along an urban interstate, enabling multi-camera 3D object tracking in a traffic monitoring context.
Detecting Socially Abnormal Highway Driving Behaviors via Recurrent Graph Attention Networks
In this work, we consider the problem of detecting a variety of socially abnormal driving behaviors, i. e., behaviors that do not conform to the behavior of other nearby drivers.
I-24 MOTION: An instrument for freeway traffic science
The datasets published with this article contains at least 4 hours of vehicle trajectory data for each of 10 days.
Automatic vehicle trajectory data reconstruction at scale
In this paper we propose an automatic trajectory data reconciliation to correct common errors in vision-based vehicle trajectory data.
Streaming data preprocessing via online tensor recovery for large environmental sensor networks
Measuring the built and natural environment at a fine-grained scale is now possible with low-cost urban environmental sensor networks.
