Neural Network Vehicle Models for High-Performance Automated Driving: Data and Materials
Abstract/Contents
- Abstract
Code and Data needed to replicate results in "Neural Network Vehicle Models for High-Performance Automated Driving".
Model_Learning/ contains experimental data on a high friction surface, code to generate data from a vehicle model, code to train models to fit data, and saved models.
Human_vs_Machine/ contains data comparing the lanekeeping controller to skilled human drivers.
Control/ contains code to simulate the controller described in the paper, code to run this controller in real time on a vehicle, and experimental data.
Description
| Type of resource | software, multimedia |
|---|---|
| Date created | February 26, 2019 |
Creators/Contributors
| Author | Brown, Matthew |
|---|---|
| Author | Kapania, Nitin |
| Author | Kegelman, John |
| Author | Gerdes, J. Christian |
| Author | Spielberg, Nathan |
Subjects
| Subject | mechanical engineering |
|---|---|
| Subject | automated vehicles |
| Subject | vehicle dynamics |
| Subject | controls |
| Subject | modeling |
| Genre | Dataset |
Bibliographic information
| Related Publication | Spielberg, N. A., Brown, M., Kapania, N, R., Kegelman, J. C., and Gerdes, J. C. (2019). Neural network vehicle models for high-performance automated driving. Science Robotics, 4(28), eaaw1975. https://doi.org/10.1126/scirobotics.aaw1975 |
|---|---|
| Location | https://purl.stanford.edu/zb950hd3384 |
Access conditions
- Use and reproduction
- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Preferred citation
- Preferred Citation
- Spielberg, Nathan and Brown, Matthew and Kapania, Nitin and Kegelman, John and Gerdes, J. Christian. (2019). Neural Network Vehicle Models for High-Performance Automated Driving: Data and Materials. Stanford Digital Repository. Available at: https://purl.stanford.edu/zb950hd3384
Collection
Dynamic Design Lab
View other items in this collection in SearchWorksContact information
- Contact
- nspielbe@stanford.edu
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