Autonomous Vehicle modelling using MATLAB and Simulink

Source code for paper "Safe, Efficient, and Comfortable Velocity Control based on Reinforcement Learning for Autonomous Driving"

An embedded CAN bus sniffer which is able to monitor any of the vehicle internal CAN bus and perform some action by triggering new CAN messages. In this way certain vehicle functionality can be triggered by responding to custom steering wheel button events, or use the vehicle virtual cockpit to display OBD-PIDs values instead of relying on an ex…

An implementation of an Autonomous Vehicle Agent in CARLA simulator, using TF-Agents

YOLO-v5 기반 "단안 카메라"의 영상을 활용해 차간 거리를 일정하게 유지하며 주행하는 Adaptive Cruise Control 기능 구현

Enhance openpilot longitudinal control with an external radar add-on.

Animation of a string stable four-truck platooning at 72 km/h with 1 second time gap.

This collection of MATLAB scripts intends to study the performance of state-constrained controllers utilizing control barrier functions in the context of adaptive cruise control.

Codebase of paper "Self-Improving Safety Performance of Reinforcement Learning Based Driving with Black-Box Verification Algorithms" published at ICRA 2023 📝

Simulation and animation of a cut-in scenario between trucks one and two in a four-truck platoon with 1 second time gap.

This is an implementation of an adaptive cruise control system based on a computer vision pipeline. This work is based on YOLACT, a State-Of-The-Art real-time instance segmentation network. You're welcome to test and try our code, we hope you'll enjoy this work!

Codebase of paper "Self-Improving Safety Performance of Reinforcement Learning Based Driving with Black-Box Verification Algorithms" published at ICRA 2023

Projects done during T4AV: Lane Detection, Adaptive Cruise Control and Platooning

This is a comprehensive project focused on developing advanced algorithms for autonomous driving, including adaptive cruise control, model predictive control (MPC), and robust scene understanding in various weather conditions.

Noise-Adaptive Driving Assistance System (NADAS) using Deep Reinforcement Learning, State-Estimation & State Representation

Adaptive Cruise Control in MATLAB

Tests the behavior of algorithms for Advanced Driver Assistance Systems (ADAS).

A Python-based traffic simulation project that models car-following behavior using ACC, BCC, and an integrated model. It includes realistic physics, energy consumption calculations, a GUI for visualization, and a headless mode for data analysis.

Implement Adaptive Cruise Control Using Arduino Kit - Windsor university project