Planning-oriented Autonomous Driving
InternetLab · Shanghai Artificial Intelligence Laboratory · +1 more institution
Abstract
Modern autonomous driving system is characterized as modular tasks in sequential order, i.e., perception, prediction, and planning. In order to perform a wide diversity of tasks and achieve advanced-level intelligence, contemporary approaches either deploy standalone models for individual tasks, or design a multi-task paradigm with separate heads. However, they might suffer from accumulative errors or deficient task coordination. Instead, we argue that a favorable framework should be devised and optimized in pursuit of the ultimate goal, i.e., planning of the self-driving car. Oriented at this, we revisit the key components within perception and prediction, and prioritize the tasks such that all these tasks…
Citation impact
- FWCI
- 74.34
- Percentile
- 100%
- References
- 83
Authors
16- YHYihan HuCorresponding
InternetLab, Shanghai Artificial Intelligence Laboratory
- JYJiazhi Yang
Shanghai Artificial Intelligence Laboratory, InternetLab
- LCLi Chen
InternetLab, Shanghai Artificial Intelligence Laboratory
- KLKeyu Li
Shanghai Artificial Intelligence Laboratory, InternetLab
- CSChonghao Sima
InternetLab, Shanghai Artificial Intelligence Laboratory
Topics & keywords
- Computer science
- Leverage (statistics)
- Modular design
- Executable
- Artificial intelligence
- Perception
- Task (project management)
- Human–computer interaction