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Development of Scheduling, Path Planning and Resource Management Algorithms for Robotic Fully-automated and Multi-story Parking Structure

Debnath, Jayanta Kumar
http://rave.ohiolink.edu/etdc/view?acc_num=toledo1470399189

Abstract Details

2016, Master of Science, University of Toledo, Electrical Engineering.
This thesis demonstrates development of a complete suite of path planning, elevator scheduling and resource allocation algorithms to manage multiple concurrent requests, in real time and in a dynamic context, for storage and retrieval of vehicles loaded onto robotic carts for a robotic, fully-automated, multi-story and driving-free parking structure. The objective is to utilize, for parking, the available spaces across the floors of a parking structure that does not have any driving lanes at a much higher percentage rate which is greater than or equal to 80% in all cases while keeping the customer waiting times at minimum. Path search and planning employs the incremental informed search algorithm D* Lite with domain-specific heuristics, and the uninformed search algorithm Uniform Cost Search in a completely-automated framework. An optimization algorithm based on nested partitions and genetic algorithm is adapted for scheduling of a group of elevators in the multi-story parking structure environment. A small percentage of parking spots are reserved as “blank cells” to facilitate movement of roller beds carrying a vehicle to its storage or retrieval destination. Resource allocation and management is accomplished using statistical models employing queueing theory for structural resources such as blank cells and elevators while minimizing customer waiting time. Lower bounds on the number of elevators needed for a specific floor count and number of parking spaces per floor are derived using statistical modeling. Multiple vehicles are considered to be potentially moving from one parking space to another by roller bed pallets moving along tracks mounted on the surface of each storage cell. A software simulator based on multi-threaded Java code and unified modeling language was developed to perform empirical testing and validation of the performance of the proposed integration framework for the set of path search, elevator scheduling and resource management algorithms. A comprehensive set of test cases where the number of floors in the parking structure, the number of cells on each floor, the number of elevators and the percentage of blank cells are parameters for exploration, are generated applying the constraints that the utilization of the parking structure has to be equal or greater than 80%, and during the “morning/evening rush hours” the capacity of parking lot needs to be fully utilized within a two clock-hour period. A typical business day scenario where morning rush hour that fills the parking lot to its maximum capacity at its conclusion and the evening rush hour that nearly empties the entire parking lot from a fully-occupied state was considered. Multiple concurrent and combination of storage and retrieval requests were generated assuming Poisson distributed customer arrivals. The performance effect of immobilized carts that form fixed obstacles on the parking floor was considered. Performance of the proposed system was assessed and evaluated using a number of performance metrics that included customer waiting time for storage request, customer waiting time for retrieval request, utilization rate for each elevator, average travel distance for storage process, average travel distance for retrieval process and maximum utilization rate for each floor. Simulation results indicate that the robotic, fully-automated and multi-story parking structure system presented in this thesis is feasible and practical for a real time context. The customer waiting time for both storage and retrieval requests is primarily distributed within reasonably acceptable ranges even in the presence of many concurrent storage and retrieval requests and accommodating a variety of customer arrival rates and numerous immobilized vehicles to make it possible for deployment in real-time environments. The simulation study results further indicated that system could handle over 100 concurrent requests in real time. The simulation study indicates that the set of algorithms developed are suitable for robotic, fully-automated and multi-story robotic parking structure to serve concurrent storage-retrieval requests representing a wide range of Poisson distributed customer arrival rates in real time with manageable computing resources under real-life scenarios.
Gursel Serpen (Committee Chair)
Kevin Xu (Committee Member)
Ahmad Javaid (Committee Member)
440 p.
Artificial Intelligence
fully-automated robotic parking; elevator scheduling; real-time; optimal; genetic algorithm; queuing theory; nested partition; UML; simulation software design; multithreaded; path planning; scheduling; optimization

Recommended Citations

Citations

  • Debnath, J. K. (2016). Development of Scheduling, Path Planning and Resource Management Algorithms for Robotic Fully-automated and Multi-story Parking Structure [Master's thesis, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1470399189

    APA Style (7th edition)

  • Debnath, Jayanta. Development of Scheduling, Path Planning and Resource Management Algorithms for Robotic Fully-automated and Multi-story Parking Structure. 2016. University of Toledo, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo1470399189.

    MLA Style (8th edition)

  • Debnath, Jayanta. "Development of Scheduling, Path Planning and Resource Management Algorithms for Robotic Fully-automated and Multi-story Parking Structure." Master's thesis, University of Toledo, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1470399189

    Chicago Manual of Style (17th edition)

toledo1470399189
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© 2016, all rights reserved.
This open access ETD is published by University of Toledo and OhioLINK.