Dryve: Autonomous cleaning of ADAS vision-based sensors in the rain
Abstract/Contents
- Abstract
- Investments in autonomous driving technology have already exceeded $200 billion, yet despite this staggering figure, driving in the rain is still an unmet need. Current self-driving vehicles are unable to drive during unexpected showers and will simply park on the side of the road. Navigating in the rain without proper cleaning technology is very challenging, water droplets will accumulate on lenses and cause distorted visibility. The solution presented in this report, named Dryve, consists of a redesigned camera case that uses a combination of high-speed rotation, hydrophobic coating, and air blowers to keep the camera lens free of droplets. By preventing rain droplets from accumulating on the camera lens, Dryve can strongly improve visibility and sensing accuracy. Dryve strives to enable safe and autonomous driving during rainy conditions, hence further encouraging the mass adoption of self-driving technology.
Description
| Type of resource | text |
|---|---|
| Publication date | April 3, 2023; 2023 |
Creators/Contributors
| Author | Adebayo, Oluwakanyinsola | |
|---|---|---|
| Author | Litong, Trisha |
https://orcid.org/0000-0001-6782-2365
(unverified)
|
| Author | Marchioni, Francesco | |
| Author | Pang, Michael | |
| Author | Verma, Shrey | |
| Author | Wadhokar, Atharva | |
| Author | Claesson, Oscar | |
| Author | Johansson, Louise | |
| Author | Jönsson, André | |
| Author | Svensson, Per-Emil |
Subjects
| Subject | Autonomous vehicles, sensors, sensor cleaning, cameras, ADAS |
|---|---|
| Genre | Text |
| Genre | Capstone |
| Genre | Report |
| Genre | Student project report |
Bibliographic information
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- 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 4.0 International license (CC BY-NC).
Preferred citation
- Preferred citation
- Adebayo, O., Litong, T., Marchioni, F., Pang, M., Verma, S., and Wadhokar, A. (2023). Dryve: Autonomous cleaning of ADAS vision-based sensors in the rain. Stanford Digital Repository. Available at https://purl.stanford.edu/nh804jy2651. https://doi.org/10.25740/nh804jy2651.
Collection
ME310 Project Based Engineering Design
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- engreference@stanford.edu
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