From 015922c515efdd6a37e6ddf7d8dd9594bcdd9974 Mon Sep 17 00:00:00 2001 From: XHwind <310381979@qq.com> Date: Sat, 31 Jul 2021 23:30:09 -0700 Subject: [PATCH 1/2] Update the doc description --- README.md | 12 +++++------- docs/index.rst | 2 ++ 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index c0f7ebb7..a5f24a79 100644 --- a/README.md +++ b/README.md @@ -9,8 +9,7 @@ well as regular automated driving components (e.g., perception, localization, pl OpenCDA is all in Python. The purpose is to enable researchers to fast-prototype, simulate, and test CDA algorithms and functions. By applying our simulation tool, users can conveniently conduct both task-specific evaluation (e.g. object detection accuracy) and pipeline-level assessment (e.g. traffic safety) on their customized algorithms. -Inspired by the [USDOT CDA CARMA program](https://its.dot.gov/cda/), OpenCDA, as an open-source project, makes a unique contribution from the perspective of initial-stage development and testing using simulation. -Users can consider using OpenCDA for initial algorithmic testing, and should use the [CARMA everything-in-the-loop](https://github.com/usdot-fhwa-stol/carma-simulation) evaluation tool and [CARMA platform](https://github.com/usdot-fhwa-stol/carma-platform) for software platform development and field testing. +In collaboration with [U.S.DOT CDA Research](https://its.dot.gov/cda/) and the [FHWA CARMA Program](https://highways.dot.gov/research/operations/CARMA), OpenCDA, as an open-source project, makes a unique contribution from the perspective of initial-stage development and testing using simulation. OpenCDA is designed and built to support initial algorithmic testing for CDA Features. Through collaboration with CARMA Collaborative, this tool provides a unique capability to the CDA research community and will interface with the [CARMA XiL tools](https://github.com/usdot-fhwa-stol/carma-simulation) being developed by U.S.DOT to support more advanced simulation testing of CDA Features. The key features of OpenCDA are: * Integration: OpenCDA utilizes CARLA and SUMO separately, as well as integrates them together for realistic scene rendering, vehicle modeling, and traffic simulation. @@ -19,7 +18,7 @@ The key features of OpenCDA are: * Benchmark: OpenCDA offers benchmark testing scenarios, benchmark baseline maps, state-of-the-art benchmark algorithms for ADS and Cooperative ADS functions, and benchmark evaluation metrics. * Connectivity and Cooperation: OpenCDA supports various levels and categories of cooperation between CAVs in simulation. This differentiates OpenCDA from other single vehicle simulation tools. - + Users could refer to [OpenCDA documentation](https://opencda-documentation.readthedocs.io/en/latest/) for more details. ## Major Components @@ -41,7 +40,7 @@ author={Runsheng Xu, Yi Guo, Xu Han, Xin Xia, Hao Xiang, Jiaqi Ma}, booktitle={2021 IEEE Intelligent Transportation Systems Conference (ITSC)}, year={2021} } -``` + ``` The arxiv link to the paper: https://arxiv.org/abs/2107.06260 Also, under this LICENSE, OpenCDA is for non-commercial research only. Researchers can modify the source code for their own research only. Contracted work that generates corporate revenues and other general commercial use are prohibited under this LICENSE. See the LICENSE file for details and possible opportunities for commercial use. @@ -73,7 +72,7 @@ We welcome your contributions. - Please report bugs and improvements by submitting issues. - Submit your contributions using [pull requests](https://github.com/ucla-mobility/OpenCDA/pulls). Please use [this template](.github/PR_TEMPLATE.md) for your pull requests. - + ## In OpenCDA v0.1.0 Release The current version features the following: * OpenCDA v0.1.0 software stack (basic ADS and cooperative ADS platform, benchmark algorithms for platooning, cooperative lane change, merge, and other freeway maneuvers) @@ -102,11 +101,10 @@ OpenCDA is supported by the [UCLA Mobility Lab](https://mobility-lab.seas.ucla.e ### Project Lead:
- Runsheng Xu ([linkedin](https://www.linkedin.com/in/runsheng-xu/), [github](https://github.com/DerrickXuNu))
- + ### Team Members: - Xu Han ([linkedin](https://linkedin.com/in/xu-han-12851a64), [github](https://github.com/xuhan417)) - Hao Xiang ([linkedin](https://www.linkedin.com/in/hao-xiang-42bb5a1b2/), [github](https://github.com/XHwind)) - Dr. Yi Guo ([linkedin](https://www.linkedin.com/in/yi-guo-4008baaa/)) - Dr. Xin Xia ([linkedin](https://www.linkedin.com/in/yi-guo-4008baaa/)) - diff --git a/docs/index.rst b/docs/index.rst index 320eaa61..a756116c 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -11,6 +11,8 @@ OpenCDA builds upon standard automated driving system (ADS) platforms and focuse OpenCDA is **all in Python**. The purpose is to enable researchers to fast-prototype, simulate, and test CDA algorithms and functions. By applying our simulation tool, users can conveniently conduct both task-specific evaluation (e.g. object detection accuracy) and pipeline-level assessment (e.g. traffic safety) on their customized algorithms. +In collaboration with `U.S.DOT CDA Research `_ and the `FHWA CARMA Program `_, OpenCDA, as an open-source project, makes a unique contribution from the perspective of initial-stage development and testing using simulation. OpenCDA is designed and built to support **initial algorithmic testing** for CDA Features. Through collaboration with CARMA Collaborative, this tool provides a unique capability to the CDA research community and will interface with the `CARMA XiL tools `_ being developed by U.S.DOT to support more advanced simulation testing of CDA Features. + OpenCDA is a work in progress. Many features on the roadmap are being continuously developed. We welcome your contribution and please visit our Github repo for the latest release. From 3e54d5e324272e75afe133ed41cc011baa95fc9a Mon Sep 17 00:00:00 2001 From: XHwind <310381979@qq.com> Date: Sat, 31 Jul 2021 23:32:42 -0700 Subject: [PATCH 2/2] fix space --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index a5f24a79..c55b8179 100644 --- a/README.md +++ b/README.md @@ -40,7 +40,7 @@ author={Runsheng Xu, Yi Guo, Xu Han, Xin Xia, Hao Xiang, Jiaqi Ma}, booktitle={2021 IEEE Intelligent Transportation Systems Conference (ITSC)}, year={2021} } - ``` +``` The arxiv link to the paper: https://arxiv.org/abs/2107.06260 Also, under this LICENSE, OpenCDA is for non-commercial research only. Researchers can modify the source code for their own research only. Contracted work that generates corporate revenues and other general commercial use are prohibited under this LICENSE. See the LICENSE file for details and possible opportunities for commercial use.