Date of Award

8-2023

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Mechanical Engineering

Committee Chair/Advisor

Dr. Ardalan Vahidi

Committee Member

Dr. Yunyi Jia

Committee Member

Dr. John Wagner

Abstract

A problem facing most public transit systems is low energy efficiency and the continued cycling of large transport vehicles such as buses at low occupancy when low demand for transport exists, wasting energy to no benefit. To remedy this issue, we propose a hybrid system consisting of existing diesel buses and automated electric shuttles to augment the system during off-peak hours. Due to their smaller size, higher occupancy, and more efficient powertrains, these shuttles could reduce the system energy used per passenger-mile-traveled. Automation removes the labor cost of drivers and, thus, eliminates the need to employ more drivers for the shuttles. The automated electric shuttles can reduce the energy use of the public transit system further while still meeting ridership demands during times with low demand for transport using optimized routes. These shuttles are considered on-demand, and we will formulate and solve an optimization algorithm to optimally allocate the shuttles to requests based on predicted fuel use (a proxy for energy use), predicted time cost, and the number of missed requests. The optimization is built upon a network graph that presents combinations of transport requests and the vehicles that can serve them and their associated routes for the optimization to choose from. By using traffic microsimulation software, the shuttles can travel along their optimized routes while being affected by transient traffic conditions, giving a better approximation of their real-world energy use. The proposed hybrid system is implemented in a commercial traffic microsimulation environment representing Clemson University’s Purple Route. To ensure high system fidelity, intersection turn ratios, boarding patterns, car traffic, etc. are implemented as well. When available, the microsimulation uses real data from multiple sources such as historic ridership data and signal timings. The results of the microsimulation demonstrate that a system where buses operate during times of high demand and automated electric shuttles operate during times of low demand has a lower energy use per passenger-mile-traveled and no missed requests. This hybrid system improves the energy used per passenger-mile-traveled by at least 32% ii when compared to the current system of buses. The hybrid system also improves the total energy use by at least 64% when compared to the total energy use of the current bus system. However, minor changes in the capacity of the hybrid system have no significant effect on the performance of the hybrid system.

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