Optimized Pricing & Scheduling Model for Long Range Autonomous Valet Parking

Khalid, Muhammad, Cao, Yue, Aslam, Nauman, Suthaputchakun, Chakkaphong, Arshad, Muhammad and Khalid, Waqar (2019) Optimized Pricing & Scheduling Model for Long Range Autonomous Valet Parking. In: FIT 2018 - 16th International Conference on Frontiers of Information Technology, 17th - 19th December 2018, Islamabad, Pakistan.

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/FIT.2018.00019


Intelligent transportation system has moved one step forward to autonomy. Effective development of autonomous vehicles is happening rapidly. Industries nowadays are interested in developing less costly and highly controllable autonomous vehicles. As a result, these autonomous vehicles will be rapidly increasing on roads in near future. Due to an upward trend in a number of vehicles, need of car Park has also shown a higher demand in past few years. Remote car parks are used to accommodate increasing numbers of vehicles and are away from the urban area and do not disturb normal traffic routines. It helps to ensure road safety for humans and get rid of traffic congestion in busy areas. In long-range autonomous valet parking, usually user leaves their vehicle at drop-off spot and it autonomously moves towards Car Park. Traffic congestion should be alleviated by lowering down the parking prices for car parks. This paper has proposed an optimized pricing & scheduling model for long range autonomous valet parking. The proposed model minimizes parking fee by comparing benchmark with optimized parking fee and selecting minimum parking fee based on user preferences. The aim to minimize fuel consumption as well as walking distance. The proposed model has been analyzed through simulation and mathematical equations.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Autonomous Valet Parking, Reservation, Smart Parking
Subjects: G400 Computer Science
L900 Others in Social studies
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 20 May 2019 11:58
Last Modified: 10 Oct 2019 18:48
URI: http://nrl.northumbria.ac.uk/id/eprint/39353

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