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The SMT-based automatic road network generation in vehicle simulation environment

Published: 01 October 2016 Publication History

Abstract

Vehicle simulators are widely used to test the correctness of vehicle control algorithms. It is important to create a virtual road environment in a way that the vehicle algorithm can be tested under various circumstances that may happen in the real world. However, building such a road environment is typically time consuming and performed in a manual and ad-hoc fashion without having a good notion of coverage criteria. We propose the automatic road network generation for vehicle simulation that is based on Satisfiability Modulo Theories (SMT). We first introduce the curve coverage criteria to characterize the property of horizontal/vertical curves that are required to test advanced safety features such as adaptive cruise control or lane keeping assistance. This criteria includes the number of curves, the distance of adjacent curves and horizontal/vertical curvatures. We propose the road network generation algorithms that utilize the SMT solver to determine a set of 3 dimensional coordinates. This algorithm takes an input of the parametrized constraints formalized from the curve coverage criteria and automatically determines a set of 3D coordinates to generate the road structure. Vehicle simulation engines can then use these coordinates to visualize the road networks, and such road networks are guaranteed to conform to the curve coverage criteria. We developed a plug-in for the Unity3D simulation engine that automates this process and demonstrate the applicability of the generated the road network for the adaptive cruise control testing.

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cover image ACM Other conferences
EMSOFT '16: Proceedings of the 13th International Conference on Embedded Software
October 2016
260 pages
ISBN:9781450344852
DOI:10.1145/2968478
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 01 October 2016

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ESWEEK'16
ESWEEK'16: TWELFTH EMBEDDED SYSTEM WEEK
October 1 - 7, 2016
Pennsylvania, Pittsburgh

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  • (2023)Toward Large-Scale Test for Certifying Autonomous Driving Software in Collaborative Virtual EnvironmentIEEE Access10.1109/ACCESS.2023.329550011(72641-72654)Online publication date: 2023
  • (2022)Feature-Interaction Sampling for Scenario-based Testing of Advanced Driver Assistance Systems✱Proceedings of the 16th International Working Conference on Variability Modelling of Software-Intensive Systems10.1145/3510466.3510474(1-10)Online publication date: 23-Feb-2022
  • (2022)The Inadequacy of Discrete Scenarios in Assessing Deep Neural NetworksIEEE Access10.1109/ACCESS.2022.322090410(118236-118242)Online publication date: 2022
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