Online Verification of Automated Road Vehicles Using Reachability Analysis

By Matthias Althoff, John M. Dolan. IEEE Transactions on robotics, 2014

444 citations recorded by the source corpus.

Subfields: Automotive Engineering, Computational Theory and Mathematics, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/be89a07a949df3639f5075d1d6041dd09aefc97c

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In Automotive Engineering

In Computational Theory and Mathematics

In Safety, Risk, Reliability and Quality

Citations in the corpus

Optimization-Based Collision Avoidance (2017, unknown): “The interested reader is referred to [10] and [56] for techniques dealing with those two challenges.”
Planning and Decision-Making for Autonomous Vehicles (2018, methodology): “Online verification can be achieved with reachability analysis (131) when performing conservative linearization, using zonotopes as a set representation and querying from a database of specific emergency maneuvers.”
Computer-aided design for safe autonomous vehicles (2017, background): “Other approaches such as theorem proving [11], [12], [20], verification [2], [8], [21], and synthesis [5], [13], [23] also address the safety of autonomous vehicles.”
APEX: Autonomous Vehicle Plan Verification and Execution (2016, methodology): “Using the approach in [16] and [15] the control inputs for longitudinal acceleration (pressing the accelerator) and steering angle velocity (turning the steering wheel) can be computed as v w and a x respectively.”
Towards Proving the Adversarial Robustness of Deep Neural Networks (2017, methodology): “Specifically, we plan to explore the integration of Reluplex with reachability analysis techniques, for both the offline [11] and online [1] variants.”
Funnel libraries for real-time robust feedback motion planning (2016, unknown): “This idea was used in Althoff and Dolan (2014) for performing online safety verification for ground vehicles.”
Survey on Scenario-Based Safety Assessment of Automated Vehicles (2020, background): “Althoff further develops the approach in [157], [158].”
A Review of Motion Planning for Highway Autonomous Driving (2020, methodology): “processes [131], [170], Monte Carlo simulation [170], evidential theory [52], or interval arithmetic [171].”