Sample scripts for the Bosch Small Traffic Lights Dataset
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Updated
Aug 8, 2020 - Python
Sample scripts for the Bosch Small Traffic Lights Dataset
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.
Coupled simulator for research on driver-pedestrian interactions made in Unity3D.
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.
Visual generation of traffic scenarios based on the OpenSCENARIO standard
r:trån is a road space model transformer library for OpenDRIVE, CityGML and beyond
Semantic Understanding of Foggy Scenes with Purely Synthetic Data
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.
Python codes for automated driving algorithms.自动驾驶算法。
3D model exchange format with physical material properties for virtual development, test and validation of automated driving.
Source code and other required files to provide a base automated driving software on an AmigoBot using ROS.
TensorFlow training pipeline and dataset for prediction of evidential occupancy grid maps from lidar point clouds.
Semantic segmentation and transfer learning using pretrained SalsaNext model in MATLAB
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
基于Delaunay三角剖分的大学生方程式无人赛车路径规划算法
Resources that help engineers thrive in automated driving R&D
L3Pilot Common Data Format
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 perceived risk in the interaction between pedestrian and vehicle, from the perspective of the driver using a crowdsourcing approach.
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