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

Muhammad Khalid, Yue Cao, Nauman Aslam, Mohsin Raza, Alun Moon, Huan Zhou

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)
76 Downloads (Pure)

Abstract

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 travelling 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 drop-off point to car park through 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 travelling time using the weighted value analysis. Results show that AVPark optimized the total trip duration, walking distance and cost.
Original languageEnglish
Pages (from-to)114141-114153
JournalIEEE Access
Volume7
Early online date23 Jul 2019
DOIs
Publication statusPublished - 29 Aug 2019

Keywords

  • Autonomous Parking
  • Optimization
  • Autonomous Driving
  • Reservation

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