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AVPark: Reservation & Cost Optimization Based Cyber-Physical System for Long-range Autonomous Valet Parking (L-AVP)

Research output: Contribution to journalJournal articlepeer-review

  • Muhammad Khalid
  • Yue Cao
  • Nauman Aslam
  • Mohsin Raza
  • Alun Moon
  • Huan Zhou
<mark>Journal publication date</mark>29/08/2019
<mark>Journal</mark>IEEE Access
Number of pages13
Pages (from-to)114141-114153
Publication StatusPublished
Early online date23/07/19
<mark>Original language</mark>English


The autonomous vehicle (AV) is an emerging product of intelligent transportation system. This paper proposes a new parking cost optimization scheme for long-range autonomous valet parking (L-AVP), namely AVPark. The L-AVP selects a drop-off point (as the temporary reference point for people to fetch the AV for traveling purpose) for AV. The user leaves AV at drop-off spot and the AV finds out the most optimal car parks (CPs) itself. The AVPark provides an AV with the most optimal car park considering the parking price, fuel consumption, and distance to a vacant parking space. AVPark aims to minimize the walking distance for drivers, and also the round-trip duration for AV from the drop-off point to car park through a combination of weighted values and heuristic approach. By facilitating the drop-off point that is newly brought into the emerging scenario, an optimization scheme is proposed to minimize the total cost for fuel consumption and traveling time using the weighted value analysis. The results show that AVPark optimized the total trip duration, walking distance, and cost.

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