STOL-AMS / TO-22-Merge-Coordination
Merge coordination aims to minimize the negative impacts of the merging process on the target lane. The shockwave magnitude and duration resulted from a merging maneuver depends on the lane-changing trajectory, traffic conditions in the origin and target lanes, and the response of the vehicles in the target lane to lane-changing vehicle.
☆10Updated 4 years ago
Alternatives and similar repositories for TO-22-Merge-Coordination
Users that are interested in TO-22-Merge-Coordination are comparing it to the libraries listed below
Sorting:
- SUMO Simulation source code of the study - A Study of Applying Eco-Driving Speed Advisory on Transit Signal Priority☆13Updated 2 years ago
- Analysis of various traffic signal control techniques in SUMO☆15Updated 5 years ago
- - Create a queueing model at signalized intersections (e.g. shockwave profile model); - Create a simple SUMO network with traffic lights;…☆10Updated 3 years ago
- This project developed a light-duty CAV lane-changing (LC) model with four components: car following (CF), mandatory and incentive-based …☆13Updated 4 years ago
- Best lane-changing policy with various types of car, on SUMO simulator.☆12Updated last year
- Modeling and control of mixed traffic flow☆45Updated 9 months ago
- Congestion aware cooperative adaptive cruise control algorithm for mitigation of self organized traffic jam☆15Updated 3 years ago
- Autonomous Intersection Management in SUMO traffic simulator achieved with Python and TraCI libraries☆12Updated 4 years ago
- The code used to generate and evaluate SUMO scenarios for measuring the safety and efficiency of low penetration rates of connected auton…☆13Updated 4 years ago
- A study code for HEVs eco-driving control☆22Updated 2 years ago
- SUMO chinese document translation project☆21Updated 3 years ago
- This is a intelligent traffic control environment for Reinforcement Learning and relative researches. This environment is compatible with…☆13Updated 5 years ago
- sumo_learn_project☆40Updated 3 years ago
- Lane-changing decision model based on deep Markov model and Cognitive Hierarchy model☆24Updated 11 months ago
- Multi-vehicle Coordinated Lane Change Strategy☆11Updated 4 years ago
- A SUMO environment for differential varaible speed limits control☆47Updated 4 years ago
- ☆13Updated 3 years ago
- Development of parametric, deep learning, and reinforcement learning agent-based model of car-following behaviour. The models aim to be d…☆23Updated 5 years ago
- A lane changing optimization planning method for autonomous vehicles in mixed traffic flow. For lane changing using three degree curve an…☆17Updated last year
- Distributed Collaboration of Connected Autonomous Vehicles at Unsignalized Intersections using Parallel Monte Carlo Tree Search☆13Updated 3 years ago
- Reinforcement learning based on ramp entrance and exit control of urban trunk roads☆47Updated last year
- Code for the paper @article{ author={Armijos, A. S. C. and Li, A. and Cassandras, C. G.}, title={Maximizing Safety and Efficiency for Coo…☆19Updated last year
- ☆11Updated 2 years ago
- Implementation of Nash Q-Learning for Autonomous Vehicle Decision Making☆14Updated 2 years ago
- Cooperative Control of Traffic Signals and Connected Vehicles: A Multi-agent Deep Reinforcement Learning Approach☆21Updated 3 years ago
- ☆22Updated 3 years ago
- SUMO CAV deployment scenarios for [Gueriau and Dusparic 2020] paper presented at The 23rd IEEE International Conference on Intelligent Tr…☆16Updated 4 years ago
- A cell transmission model based on python☆45Updated last year
- High speed autonomous vehicle navigation and lane change in dense traffic scenario using custom SUMO gym Environment and Reinforcement Le…☆27Updated last year
- Lane Changes in a Highway environment using Reinforcement learning in SUMO☆55Updated 6 years ago