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Noraldin-Dissertation.pdf (10.74 MB)

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Improving Parking Efficiency Using Lidar in Autonomous Vehicles (AV)

Albabah, Noraldin
http://rave.ohiolink.edu/etdc/view?acc_num=akron1613061615734267

Abstract Details

2021, Doctor of Philosophy, University of Akron, Civil Engineering.
A leading cause of traffic congestion in urban cities nowadays is drivers’ search for vacant parking spaces. This research investigates the effectiveness of utilizing autonomous vehicles (AV) in detecting vacant parking spaces at any parking facility and sharing the findings with beneficiaries. A theoretical mathematical model for detection and communication processes using AV technologies is proposed to improve parking management, reduce traffic congestion, advance city trafficking, and develop smart cities. This model identifies the Effective Detection Area (EDA) of AVs as the area that considers several detected spots and can fulfil the constraint requirements of detection factors (DF). It requires a specific number of AVs and consequently, for effective detection purposes, reserves certain parking spots for them. A simulation is conducted to validate its calculations, which thus results in signifying the EDA as three rows, two in front of the AV and one behind, and verifying the AV detection efficiency with about 150 detected parking spots. Communicating the detected information is essential to process it accurately. AVs communicate processed data using vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-everything (V2X) connected through a wireless 5G system, dedicated short-range communication (DSRC), and a cellular network. Accordingly, AV drivers receive parking facility information directly, whereas ordinary vehicle drivers obtain it through a phone application, website or short message service (SMS). This study has several recommendations for future studies, including identifying the relationship between DA and the height of the LiDAR sensor, and investigating the effectiveness of including mobile AVs in the detection process.
Ping Yi (Advisor)
David Roke (Committee Member)
Qindan Huang (Committee Member)
Yilmaz Sozer (Committee Member)
Jun Ye (Committee Member)
177 p.
Civil Engineering
Parking Management, LiDAR, Autonomous Vehicles

Recommended Citations

Citations

  • Albabah, N. (2021). Improving Parking Efficiency Using Lidar in Autonomous Vehicles (AV) [Doctoral dissertation, University of Akron]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=akron1613061615734267

    APA Style (7th edition)

  • Albabah, Noraldin. Improving Parking Efficiency Using Lidar in Autonomous Vehicles (AV). 2021. University of Akron, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=akron1613061615734267.

    MLA Style (8th edition)

  • Albabah, Noraldin. "Improving Parking Efficiency Using Lidar in Autonomous Vehicles (AV)." Doctoral dissertation, University of Akron, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=akron1613061615734267

    Chicago Manual of Style (17th edition)

akron1613061615734267
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© 2021, all rights reserved.
This open access ETD is published by University of Akron and OhioLINK.