# WATonoBus: Field-Tested All-Weather Autonomous Shuttle Technology

arXiv: https://arxiv.org/abs/2312.00938 · HTML: https://mlsanity.com/paper/2312.00938/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 33 references that are in the map.
- First posted on arXiv 1 Dec 2023.

## Builds on (most cited first, 6 of 6)

- [YOLOv4: Optimal Speed and Accuracy of Object Detection](https://mlsanity.com/paper/2004.10934/) (2020)
- [Online Extrinsic Calibration based on Per-Sensor Ego-Motion Using Dual Quaternions](https://mlsanity.com/paper/2101.11440/) (2021)
- [Situation-Aware Environment Perception Using a Multi-Layer Attention Map](https://mlsanity.com/paper/2112.01126/) (2021)
- [A Taxonomy to Unify Fault Tolerance Regimes for Automotive Systems: Defining Fail-Operational, Fail-Degraded, and Fail-Safe](https://mlsanity.com/paper/2106.11042/) (2021)
- [Autonomous Shuttle-as-a-Service (ASaaS): Challenges, Opportunities, and Social Implications](https://mlsanity.com/paper/2001.09763/) (2020)
- [Situation-Aware Environment Perception for Decentralized Automation Architectures](https://mlsanity.com/paper/2207.01896/) (2022)

## Built on by (most cited first, 1 of 1)

- [Urban Computing in the Era of Large Language Models](https://mlsanity.com/paper/2504.02009/) (2025)

## Abstract (arXiv)

All-weather autonomous vehicle operation poses significant challenges, encompassing modules from perception and decision-making to path planning and control. The complexity arises from the need to address adverse weather conditions such as rain, snow, and fog across the autonomy stack. Conventional model-based single-module approaches often lack holistic integration with upstream or downstream tasks. We tackle this problem by proposing a multi-module and modular system architecture with considerations for adverse weather across the perception level, through features such as snow covered curb detection, to decision-making and safety monitoring. Through daily weekday service on the WATonoBus platform for almost two years, we demonstrate that our proposed approach is capable of addressing adverse weather conditions and provide valuable insights from edge cases observed during operation.