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

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AVPark: Reservation & Cost Optimization Based Cyber-Physical System for Long-range Autonomous Valet Parking (L-AVP). / Khalid, Muhammad; Cao, Yue; Aslam, Nauman; Raza, Mohsin; Moon, Alun; Zhou, Huan.

In: IEEE Access, Vol. 7, 29.08.2019, p. 114141-114153.

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@article{41e38b81d93c4bfb89d3a1135ea62b1d,
title = "AVPark: Reservation & Cost Optimization Based Cyber-Physical System for Long-range Autonomous Valet Parking (L-AVP)",
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 tofetch 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 durationfor 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.",
keywords = "Autonomous Parking, Optimization, Autonomous Driving, Reservation",
author = "Muhammad Khalid and Yue Cao and Nauman Aslam and Mohsin Raza and Alun Moon and Huan Zhou",
year = "2019",
month = aug,
day = "29",
doi = "10.1109/access.2019.2930564",
language = "English",
volume = "7",
pages = "114141--114153",
journal = "IEEE Access",
issn = "2169-3536",
publisher = "IEEE",

}

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TY - JOUR

T1 - AVPark: Reservation & Cost Optimization Based Cyber-Physical System for Long-range Autonomous Valet Parking (L-AVP)

AU - Khalid, Muhammad

AU - Cao, Yue

AU - Aslam, Nauman

AU - Raza, Mohsin

AU - Moon, Alun

AU - Zhou, Huan

PY - 2019/8/29

Y1 - 2019/8/29

N2 - 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 tofetch 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 durationfor 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.

AB - 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 tofetch 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 durationfor 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.

KW - Autonomous Parking

KW - Optimization

KW - Autonomous Driving

KW - Reservation

U2 - 10.1109/access.2019.2930564

DO - 10.1109/access.2019.2930564

M3 - Article

VL - 7

SP - 114141

EP - 114153

JO - IEEE Access

JF - IEEE Access

SN - 2169-3536

ER -