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

科研成果: 期刊稿件文章同行评审

18 引用 (Scopus)

摘要

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.

源语言英语
文章编号8769820
页(从-至)114141-114153
页数13
期刊IEEE Access
7
DOI
出版状态已出版 - 2019
已对外发布

指纹

探究 'AVPark: Reservation and cost optimization-based cyber-physical system for long-range autonomous valet parking (L-AVP)' 的科研主题。它们共同构成独一无二的指纹。

引用此