applying multi-agent reinforcement learning for highway-merging autonomous vehicles
Containerised SUMO. Use sumo, sumo-gui and TraCI with Docker. 🐳 🚗
A model problem for big data self adaptive systems using SUMO and TraCI
The Decentralized Autonomous Vehicles project connects self-driving vehicles on a blockchain network, enabling secure real-time decision-making. It leverages decentralized nature, incident data sharing, and Vehicular IoT/VANET technology to enhance vehicle autonomy and ensure data security and privacy.
DRIVE: A Digital Network Oracle for Cooperative Intelligent Transportation Systems
Python Package to perform simple Traffic Interventions and run traffic simulations.
NTCIP 1202 traffic-signal attack lab: emulated controller + SUMO intersection. snmpset commands drive a live SUMO-GUI window.
Native macOS GUI for Eclipse SUMO simulations, built with SwiftUI, Metal, and TraCI.
This is a repository for my Masters Thesis called Cognitive technologies in traffic light control.
Design and Control Co-Optimization for Urban Streets Using Reinforcement Learning
Hard real-time traffic light controller in C11 driving a SUMO simulation over TraCI: SCHED_FIFO tasks, measured emergency-vehicle preemption, and the schedulability analysis behind it
Torii: Agent plugin for SUMO with OSM-to-SUMO tools, TLS review, routeability probes, and evidence-aware feedback diagnosis.
An AI-driven Adaptive Traffic Signal Control System (ATSCS) that replaces static timers with dynamic green-light phases. Utilizes YOLOv8 for real-time vehicle density estimation and multi-class classification, achieving 96.4% mAP. Optimized for low-latency inference (>30 FPS) on edge devices to reduce urban congestion and commuter wait times.
A novel modification to existing k-shortest path algorithms which re-routes drivers with regard to reducing average travel time whilst maintaining fairness
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