CoCar NextGen: a Multi-Purpose Platform for Connected Autonomous Driving Research
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Abstract (arXiv)
Real world testing is of vital importance to the success of automated driving. While many players in the business design purpose build testing vehicles, we designed and build a modular platform that offers high flexibility for any kind of scenario. CoCar NextGen is equipped with next generation hardware that addresses all future use cases. Its extensive, redundant sensor setup allows to develop cross-domain data driven approaches that manage the transfer to other sensor setups. Together with the possibility of being deployed on public roads, this creates a unique research platform that supports the road to automated driving on SAE Level 5.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Apr 2024.
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Citing papers per year: 2024: 2; 2025: 5; 2026: 1.
8 papers.
- 2024TLD-READY: Traffic Light Detection -- Relevance Estimation and Deployment Analysiscited by 5
- 2025A Data-Driven Novelty Score for Diverse In-Vehicle Data Recordingcited by 3
- 2025The ATLAS of Traffic Lights: A Reliable Perception Framework for Autonomous Drivingcited by 2
- 2025Point Cloud Recombination: Systematic Real Data Augmentation Using Robotic Targets for LiDAR Perception Validationcited by 1
- 2025Fool the Stoplight: Realistic Adversarial Patch Attacks on Traffic Light Detectorscited by 1
- 2025A Feedback-Control Framework for Efficient Dataset Collection from In-Vehicle Data Streamscited by 1
- 2024From One to the Power of Many: Invariance to Multi-LiDAR Perception from Single-Sensor Datasetscited by 0
- 2026Real-World On-Vehicle Evaluation of Embedding-Based Anomaly Detectioncited by 0
- 2026Real-World On-Vehicle Evaluation of Embedding-Based Anomaly Detection19 May 2026
- 2025A Feedback-Control Framework for Efficient Dataset Collection from In-Vehicle Data Streams5 Nov 2025
- 2025A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording6 Jul 2025
- 2025Fool the Stoplight: Realistic Adversarial Patch Attacks on Traffic Light Detectors5 Jun 2025
- 2025Point Cloud Recombination: Systematic Real Data Augmentation Using Robotic Targets for LiDAR Perception Validation5 May 2025
- 2025The ATLAS of Traffic Lights: A Reliable Perception Framework for Autonomous Driving28 Apr 2025
- 2024From One to the Power of Many: Invariance to Multi-LiDAR Perception from Single-Sensor Datasets27 Sep 2024
- 2024TLD-READY: Traffic Light Detection -- Relevance Estimation and Deployment Analysis11 Sep 2024