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Found 6 papers, 1 papers with code
Enhancing Autonomous Vehicle Training with Language Model Integration and Critical Scenario Generation
This paper introduces CRITICAL, a novel closed-loop framework for autonomous vehicle (AV) training and testing.
Adaptive Road Configurations for Improved Autonomous Vehicle-Pedestrian Interactions using Reinforcement Learning
The deployment of Autonomous Vehicles (AVs) poses considerable challenges and unique opportunities for the design and management of future urban road infrastructure.
Route Planning for Last-Mile Deliveries Using Mobile Parcel Lockers: A Hybrid Q-Learning Network Approach
Our results indicate that HQM achieves better optimisation performance with shorter computation time than the exact approach solved by the Gurobi solver in large problem instances.
Multi-core fiber enabled fading noise suppression in φ-OFDR based quantitative distributed vibration sensing
Coherent fading has been regarded as a critical issue in phase-sensitive optical frequency domain reflectometry ({\phi}-OFDR) based distributed fiber-optic sensing.
A Reinforcement Learning-based Adaptive Control Model for Future Street Planning, An Algorithm and A Case Study
An intelligent street can learn and improve its decision-making on the right-of-way (ROW) for road users, liberating more active pedestrian space while maintaining traffic safety and efficiency.
Location-routing Optimisation for Urban Logistics Using Mobile Parcel Locker Based on Hybrid Q-Learning Algorithm
Mobile parcel lockers (MPLs) have been recently introduced by urban logistics operators as a means to reduce traffic congestion and operational cost.
