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
Related projects ⓘ
Alternatives and complementary repositories for TO-22-Merge-Coordination
- SUMO Simulation source code of the study - A Study of Applying Eco-Driving Speed Advisory on Transit Signal Priority☆12Updated last year
- 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
- Multi-vehicle Coordinated Lane Change Strategy☆11Updated 4 years ago
- Modeling and control of mixed traffic flow☆41Updated 4 months ago
- A study code for HEVs eco-driving control☆22Updated last year
- Congestion aware cooperative adaptive cruise control algorithm for mitigation of self organized traffic jam☆13Updated 3 years ago
- A SUMO environment for differential varaible speed limits control☆41Updated 4 years ago
- Autonomous Intersection Management in SUMO traffic simulator achieved with Python and TraCI libraries☆12Updated 4 years ago
- sumo_learn_project☆37Updated 2 years ago
- CACC VISSIM 2.0 Algorithm is designed to simulate close-spaced CACC platoons in VISSIM using the COM interface and VISSIM API. This appli…☆12Updated 4 years ago
- This is a intelligent traffic control environment for Reinforcement Learning and relative researches. This environment is compatible with…☆13Updated 4 years ago
- Distributed Collaboration of Connected Autonomous Vehicles at Unsignalized Intersections using Parallel Monte Carlo Tree Search☆11Updated 2 years ago
- [ITSC 2021] Reinforcement Learning for Mixed Autonomy Intersections☆21Updated last year
- Lane Changes in a Highway environment using Reinforcement learning in SUMO☆47Updated 6 years ago
- High speed autonomous vehicle navigation and lane change in dense traffic scenario using custom SUMO gym Environment and Reinforcement Le…☆15Updated last year
- This project developed a light-duty CAV lane-changing (LC) model with four components: car following (CF), mandatory and incentive-based …☆12Updated 4 years ago
- ☆21Updated 2 years ago
- Reinforcement learning based on ramp entrance and exit control of urban trunk roads☆40Updated 8 months ago
- Aiming at the problem of the traffic efficiency of intelligent networked vehicles passing through unsignalized-intersection in the future…☆43Updated 3 years ago
- Lane-changing decision model based on deep Markov model and Cognitive Hierarchy model☆19Updated 5 months ago
- Master's thesis about Deep Reinforcement Learning for Decision Making in autonomous driving☆24Updated 5 years ago
- A Simulation Environment based on SUMO to analyze Scenarios for autonomous driving vehicles in Cities☆26Updated last year
- Dynamic Traffic Assignment☆12Updated 4 years ago
- We propose a driver modeling process of an intelligent autonomous driving policy, which is obtained through Q-learning.☆23Updated 4 years ago
- This python package contains scripts needed to train IRL Driver models on HighD datasets. This code is accompanying the paper "Validating…☆16Updated 2 years ago
- 基于VISSIM实现在沪宁高速公路低CAV渗透率场景下，设置CAV专用道对高速公路整体行驶安全性和效率的影响，并对该场景进行仿真评估。☆18Updated last year
- Build a very simple intersection assistant driving system simulation based on SUMO and TraCI4Matlab☆10Updated 5 years ago