Scheduling Heterogeneous Fleets with Skill and Temporal Synchronisation for Automotive Testing

Robert Fina*, Hubert Gattringer, Andreas Müller, Daniel Reischl, Martin Fritz

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

The increased complexity of vehicle testing can be attributed to the rapid development of technical advancements within the automotive industry, thereby prolonging the time to market of a product. The process of allocating and coordinating vehicle tests at proving grounds (PGs) is a complex and time-consuming task. Currently, this process is still performed manually, which is inefficient. This study proposes a methodology for assigning scenarios to designated sites, taking into account travel aspects between locations and fulfilling participant requirements. The allocation procedure is formulated as an Open Job Shop Scheduling problem with temporal synchronisation and skill matching, and is solved by the Constraint Programming tool Google OR-Tools. The efficacy of the approach is demonstrated by its ability to generate a close-to-optimal schedule to fulfil customer requests. Case studies demonstrate that a combination of two distinct objectives are essential to meet the demands of compactness and time efficiency. The findings of this study provide a solid foundation for enhancing automation at a PG, thereby improving efficiency and optimising testing processes.
Original languageEnglish
Title of host publicationIV 2025 - 36th IEEE Intelligent Vehicles Symposium
PublisherIEEE
Pages2054-2060
Number of pages7
ISBN (Electronic)9798331538033
ISBN (Print)979-8-3315-3804-0
DOIs
Publication statusPublished - 25 Jun 2025
Event2025 IEEE Intelligent Vehicles Symposium (IV) - Cluj-Napoca, Romania
Duration: 22 Jun 202525 Jun 2025

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings
ISSN (Print)1931-0587
ISSN (Electronic)2642-7214

Conference

Conference2025 IEEE Intelligent Vehicles Symposium (IV)
Period22.06.202525.06.2025

Fields of science

  • 203013 Mechanical engineering
  • 202 Electrical Engineering, Electronics, Information Engineering
  • 202035 Robotics
  • 203022 Technical mechanics
  • 203015 Mechatronics

JKU Focus areas

  • Digital Transformation

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