There are 5 repositories under automated-driving topic.
Sample scripts for the Bosch Small Traffic Lights Dataset
Visual generation of traffic scenarios based on the OpenSCENARIO standard
SimViz contains tools and resources for authoring and executing autonomous vehicle simulations on roadways and city scapes by using map import, scene creation, formatting of ground truth data, and creating spline based roads.
Eclipse ADORe is a ROS based modular software library and toolkit for decision making, planning, control and simulation of automated vehicles supporting CARLA and SUMO.
Semantic Understanding of Foggy Scenes with Purely Synthetic Data
TensorFlow training pipeline and dataset for prediction of evidential occupancy grid maps from lidar point clouds.
3D model exchange format with physical material properties for virtual development, test and validation of automated driving.
Python codes for automated driving algorithms.自动驾驶算法。
Coupled simulator for research on driver-pedestrian interactions made in Unity3D.
Resources that help engineers thrive in automated driving R&D
A Python library for reading, writing and visualizing the OMEGA Format, targeted towards storing reference and perception data in the automotive context on an object list basis with a focus on an urban use case.
Semantic segmentation and transfer learning using pretrained SalsaNext model in MATLAB
基于Delaunay三角剖分的大学生方程式无人赛车路径规划算法
L3Pilot Common Data Format
Supplementary material for "Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges" IEEE transactions on intelligent transportation systems: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9000872 -- arxiv: https://arxiv.org/pdf/1902.07830.pdf
Source code and other required files to provide a base automated driving software on an AmigoBot using ROS.
All issues, discussions etc. on mirror: https://gitlab.com/tuda-fzd/perception-sensor-modeling/object-based-generic-perception-object-model
A converter from OpenDRIVE to NetworkX and GeoPandas
MATLAB class intended to serve as the interface between path planning and path tracking.
Building trust towards self driving, one step at a time.
A framework for the analysis of perceived risk in the interaction between pedestrian and vehicle, from the perspective of the driver using a crowdsourcing approach.
Framework for the analysis of crossing behaviour in the interaction between multiple pedestrians and an automated vehicle, from the perspective of one of the pedestrians using a crowdsourcing approach.
This is the final project in the Course 1 - Introduction to Self Driving Cars of the Self-Driving Car Specialization offered by Coursera
Crowdsourced experiment on bio-inpired interfaces for automated vehicles.
A framework for the analysis of trust in the interaction between pedestrians and vehicle (manual and automated), from the perspective of the driver of a manual or an automated vehicle, using a crowdsourcing approach.
A framework for the analysis of un(certainty) in traffic, using a crowdsourcing approach.
An REU (Research Experiences for Undergraduates) project on human behavior and automated driving features
It explores topics such as automotive mechanics, CAN, C++, and emerging trends in mobility software.
Examining eHMIs in critical driver-pedestrian encounters in a coupled simulator
Crowdsourced experiment on eye contract between automated vehicles and pedestrians.
Frontend of crowdsourced experiment on acceptance the AI-based lane changes of an automated car.
Detection of saliency in crowdsourced gazes data.
This project defines a framework for the analysis of crossing behaviour in the interaction between a pedestrian and an automated vehicle with a textual eHMI using a crowdsourcing approach.
Additional results for "Using Drones as Reference Sensors for Neural-Networks-Based Modeling of Automotive Perception Errors"