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A testbed simulator for autonomous vehicle testing methods

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

Research areas: Autonomous and self-adaptive systems; Cyber Physical Systems; Safety analysis, system safety; Safety of autonomous and self-adaptive systems; Software testing

Prior work at York has developed an autonomous car simulator as part of a project to explore the value of a situation-coverage metric for robot testing (see [1] for an outline of the approach). The currently version of the simulator has a simulated robot with a number of seeded faults that can be switched on and off. This allows us to evaluate robot test generation approaches by applying them to the simulated robot and measuring how many of the seeded faults they find. This past work has weaknesses, however:

• The results from the above work are somewhat noisy as the current robot is rather buggy. Even when all seeded faults are disabled, it does some rather odd things. When the seeded faults are switched on, it is relatively easy for a test method to discover them. Ideally, the no-fault robot would be behave impeccably in a wide variety of driving situations, and the seeded faults would be reasonably difficult to discover.
• The current implementation also lacks a clear rationale for the faults seeded - it is not clear that the set of faults seeded is optimally diverse (in terms of the types of faults possible in robot control software) or optimally representative (in terms of the types of faults likely in robot control software).

There is therefore potential for a PhD project thus:

• Define a clear standard for acceptable behaviour of an autonomous vehicle in a UK-style road environment.
• Define a taxonomy of faults, taking into account prior taxonomies of robot software faults (e.g. those presented in [2,3], and accounts of real-world autonomous vehicle failures (e.g. those described in [4]).
• Revise and improve the vehicle controller so as to achieve behaviour in the simulation consistent with the above items - compliance with the behaviour standard n the baseline case, and appropriately different when each seeded fault is enabled.
• Evaluate the work by comparing the number and type of failures detected by existing test methods against the current vehicle controller and your improved vehicle controller. (The current simulator has tooling that can generate random maps and detect many failure behaviours)
• Apply the taxonomy, simulator and experimental protocols to evaluate a range of plausible testing techniques

After the project, the resulting taxonomy, simulator and experimental protocols will be of significant value to the autonomous vehicle development and test communities.


[1] Situation coverage - a coverage criterion for testing autonomous robots Rob Alexander, Heather Hawkins, Drew Rae Technical Report YCS-2015-496, Department of Computer Science, University of York, Jan 2015

[2] Lussier B, Chatila R, Guiochet J, Ingrand F, Lampe A, Killijian M-O, et al. Fault Tolerance in Autonomous Systems: How and How Much. Proceedings of the 4th IARP/IEEE-RAS/EURON Joint Workshop on Technical Challenges for Dependable Robots in Human Environments, 2005.

[3] Dependability and its Threats - a Taxonomy Algirdas Avizienis, Jean-Claude Laprie, Brian Randell

[4] Fletcher L, Teller S, Olson E, Moore D, Kuwata Y, How J, et al. The MIT-Cornell Collision and Why it Happened. Journal of Field Robotics. 2008;25:775-807.

Related Subjects

How good is research at University of York in Computer Science and Informatics?

FTE Category A staff submitted: 34.80

Research output data provided by the Research Excellence Framework (REF)

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