Autoware on Board: Enabling Autonomous Vehicles with Embedded Systems

By Shinpei Kato, Shota Tokunaga, Yuya Maruyama, Seiya Maeda, Manato Hirabayashi, Yuki Kitsukawa, Abraham Monrroy, Tomohito Ando, Yusuke Fujii, Takuya Azumi. International Conference on Cyber-Physical Systems, 2018

648 citations recorded by the source corpus.

Subfields: Automotive Engineering, Computer Vision and Pattern Recognition, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/49c0769b9100ed7148648ce11740055f04ca864d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Di Feng
2. Klaus C. J. Dietmayer
3. Steven L. Waslander
4. Baofu Wu
5. Ali Harakeh
6. Sidi Lu
7. Ren Zhong
8. Qingyan Zhang

In Computer Vision and Pattern Recognition

1. Steven L. Waslander
2. Di Feng
3. Ali Harakeh
4. Klaus C. J. Dietmayer
5. Baofu Wu
6. Sidi Lu
7. Ren Zhong
8. Qingyan Zhang

Citations in the corpus

• A Survey on Multimodal Large Language Models for Autonomous Driving (2023, background): “Regulatory and service-wise, autonomous driving technology are receiving increasing government acceptance and public acknowledgment, with numerous companies receiving permits to operate autonomous driving vehicles on public roads in designated regions while more vehicles with autonomous driving…”
• Computing Systems for Autonomous Driving: State of the Art and Challenges (2020, background): “actuation capabilities, the usage of it is still limited to several commercial vehicles with a small set of supportable sensors [235].”
• A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving (2020, background): “It is a difficult task that requires access to an autonomous vehicle platform and a complete software stacks [120], [121] that support the integration of uncertainty estimates from probabilistic detectors in subsequent tasks.”