Reinforcement learning-based vehicle travel path reconstruction from sparse automatic licence plate recognition data
Automatic licence plate recognition (ALPR) data is a vital source for acquiring large-scale vehicle trajectory data in urban transportation research. However, the sparse distribution of ALPR sensors often results in incomplete vehicle trajectories with unobserved travel paths between adjacent ALPR s...
Saved in:
Main Authors: | Qiuping Li, Hui Meng, Li Zhuo |
---|---|
Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2025-01-01
|
Series: | Annals of GIS |
Subjects: | |
Online Access: | https://www.tandfonline.com/doi/10.1080/19475683.2025.2453553 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Q-learning global path planning for UAV navigation with pondered priorities
by: Kevin B. de Carvalho, et al.
Published: (2025-03-01) -
Reinforcement Learning-Based Autonomous Soccer Agents: A Study in Multi-Agent Coordination and Strategy Development
by: Biplov Paneru, et al.
Published: (2025-01-01) -
ReMAV: Reward Modeling of Autonomous Vehicles for Finding Likely Failure Events
by: Aizaz Sharif, et al.
Published: (2024-01-01) -
An Improved HM-SAC-CA Algorithm for Mobile Robot Path Planning in Unknown Complex Environments
by: Ting Jiao, et al.
Published: (2025-01-01) -
Multi-Objective Dynamic Path Planning with Multi-Agent Deep Reinforcement Learning
by: Mengxue Tao, et al.
Published: (2024-12-01)