# The Controllability of Planning, Responsibility, and Security in Automatic Driving Technology

arXiv: https://arxiv.org/abs/2102.00617 · HTML: https://mlsanity.com/paper/2102.00617/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 16 references that are in the map.
- First posted on arXiv 1 Feb 2021.

## Builds on (most cited first, 3 of 3)

- [Mitigating Adversarial Effects Through Randomization](https://mlsanity.com/paper/1711.01991/) (2017)
- [The social dilemma of autonomous vehicles](https://mlsanity.com/paper/1510.03346/) (2015)
- [Deep Learning for Signal Authentication and Security in Massive Internet of Things Systems](https://mlsanity.com/paper/1803.00916/) (2018)

## Abstract (arXiv)

People hope automated driving technology is always in a stable and controllable state; specifically, it can be divided into controllable planning, controllable responsibility, and controllable information. When this controllability is undermined, it brings about the problems, e.g., trolley dilemma, responsibility attribution, information leakage, and security. This article discusses these three types of issues separately and clarifies the misunderstandings.