Dan Jackson

AI
h-index28
3papers
26citations
Novelty50%
AI Score23

3 Papers

8.9ROMar 29, 2021
Certified Control: An Architecture for Verifiable Safety of Autonomous Vehicles

Daniel Jackson, Valerie Richmond, Mike Wang et al.

Widespread adoption of autonomous cars will require greater confidence in their safety than is currently possible. Certified control is a new safety architecture whose goal is two-fold: to achieve a very high level of safety, and to provide a framework for justifiable confidence in that safety. The key idea is a runtime monitor that acts, along with sensor hardware and low-level control and actuators, as a small trusted base, ensuring the safety of the system as a whole. Unfortunately, in current systems complex perception makes the verification even of a runtime monitor challenging. Unlike traditional runtime monitoring, therefore, a certified control monitor does not perform perception and analysis itself. Instead, the main controller assembles evidence that the proposed action is safe into a certificate that is then checked independently by the monitor. This exploits the classic gap between the costs of finding and checking. The controller is assigned the task of finding the certificate, and can thus use the most sophisticated algorithms available (including learning-enabled software); the monitor is assigned only the task of checking, and can thus run quickly and be smaller and formally verifiable. This paper explains the key ideas of certified control and illustrates them with a certificate for LiDAR data and its formal verification. It shows how the architecture dramatically reduces the amount of code to be verified, providing an end-to-end safety analysis that would likely not be achievable in a traditional architecture.

2.9CRApr 18, 2020
CryptoCam: Privacy Conscious Open Circuit Television

Gerard Wilkinson, Dan Jackson, Andrew Garbett et al.

The prevalence of Closed Circuit Television (CCTV) in today's society has given rise to an inherent asymmetry of control between the watchers and the watched. A sense of unease relating to the unobservable observer (operator) often leads to a lack of trust in the camera and its purpose, despite security cameras generally being present as a protective device. In this paper, we detail our concept of Open Circuit Television and prototype CryptoCam, a novel system for secure sharing of video footage to individuals and potential subjects nearby. Utilizing point-of-capture encryption and wireless transfer of time-based access keys for footage, we have developed a system to encourage a more open approach to information sharing and consumption. Detailing concerns highlighted in existing literature we formalize our over-arching concept into a framework called Open Circuit Television (OCTV). Through CryptoCam we hope to address this asymmetry of control by providing subjects with data equity, discoverability and oversight.

4.4AIJun 25, 2012
Relational Approach to Knowledge Engineering for POMDP-based Assistance Systems as a Translation of a Psychological Model

Marek Grzes, Jesse Hoey, Shehroz Khan et al.

Assistive systems for persons with cognitive disabilities (e.g. dementia) are difficult to build due to the wide range of different approaches people can take to accomplishing the same task, and the significant uncertainties that arise from both the unpredictability of client's behaviours and from noise in sensor readings. Partially observable Markov decision process (POMDP) models have been used successfully as the reasoning engine behind such assistive systems for small multi-step tasks such as hand washing. POMDP models are a powerful, yet flexible framework for modelling assistance that can deal with uncertainty and utility. Unfortunately, POMDPs usually require a very labour intensive, manual procedure for their definition and construction. Our previous work has described a knowledge driven method for automatically generating POMDP activity recognition and context sensitive prompting systems for complex tasks. We call the resulting POMDP a SNAP (SyNdetic Assistance Process). The spreadsheet-like result of the analysis does not correspond to the POMDP model directly and the translation to a formal POMDP representation is required. To date, this translation had to be performed manually by a trained POMDP expert. In this paper, we formalise and automate this translation process using a probabilistic relational model (PRM) encoded in a relational database. We demonstrate the method by eliciting three assistance tasks from non-experts. We validate the resulting POMDP models using case-based simulations to show that they are reasonable for the domains. We also show a complete case study of a designer specifying one database, including an evaluation in a real-life experiment with a human actor.