Thesis (M.P.A.)--University of Hong Kong, 1998. / Includes bibliographical references (leaf 113-115).

Thesis (M.P.A.)--University of Hong Kong, 1998. / Includes bibliographical references (leaves 113-115). Also available in print.

There are currently very few models that estimate diesel and hybrid bus fuel consumption levels. Those that are available either require significant dynamometer data gathering to calibrate the model parameters and also produce a bang-bang control system (optimum control entails maximum throttle and braking input). This thesis extends the Virginia Tech Comprehensive Power-Based Fuel Consumption Model (VT-CPFM) to model diesel buses and develops an application for it. A procedure is developed to calibrate the bus parameters using publicly available data from the Altoona Bus Research and Testing Center. In addition, calibration is also made using in-field bus fuel consumption data. The research presented in this thesis calibrates model parameters for a total of 10 standard diesel buses and 3 hybrid buses from Altoona and 10 buses from Blacksburg Transit. In the case of the Altoona data, the VT-CPFM estimated fuel consumption levels on the Orange County bus cycle dynamometer test produce an average error of 4.7%. The estimation error is less than 6% for all but two buses with a maximum error of 10.66% for one hybrid bus. The VT-CPFM is also validated using on-road fuel consumption measurements that are derived by creating drive cycles from acceleration information producing an average estimation error of 22%. These higher errors are attributed to the errors associated with constructing the in-field drive cycles given that they are not available. In the case of the Blacksburg Transit buses, the calibrated parameters produce a low sum of mean squared error, less than 0.002, and a coefficient of determination greater than 0.93. Finally an application of the VT-CPFM is presented in the form of a dynamic bus scheduling algorithm. / Master of Science

Although public transit bus accounts for only a small percentage of the mode share for transportation in Florida, the annual passenger miles were over 1 billion with over 200 million passenger trips in 2005. These numbers warrant close attention to be paid to the safety of public transit vehicles. Despite the relatively low occurrence of fatalities and bus crashes, each crash of a high occupancy vehicle such as a public transit bus could expose more people to injury than a private automobile crash. Bus crashes also have a significant impact on the automobiles that are involved. Since a high percentage of bus crashes in Florida are caused by rear-end collisions with private automobiles, improving the signage and lighting that will allow buses to move back into traffic safely is very important for bus safety and operations. This paper uses bus operator surveys, crash data, and field studies to develop recommendations for lighting and signage on the back of the bus, roadway signs and revised Florida legislations. Improved signage and lighting will help the bus move back into traffic safely, decrease bus delay and improve bus operations however it must be accompanied by laws and law enforcement.

published_or_final_version / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

published_or_final_version / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

published_or_final_version / abstract / Economics and Finance / Master / Master of Economics

Thesis (M. Econ.)--University of Hong Kong, 1995. / Xeror copy of typescript. Includes bibliographical references (leaf 83-87).

Thesis (M.Econ.)--University of Hong Kong, 1995. / Includes bibliographical references (leaf 83-87). Also available in print.

Overwhelming evidence throughout the literature has shown that bus overhead and maintenance (O&M) costs increase as buses age. This has implications toward a fleet manager's decision of when one should buy, use, or sell buses to minimize total fleet costs. Unfortunately, there are uncertain market conditions associated with bus fleets that cloud the manager's ability to make appropriate decisions. Using integer programming (IP), O&M trends and changing market conditions are integrated into a model to better analyze bus fleets. Due to recent budget constraints of transit agencies, needs for a bus fleet replacement model have arisen. King County in Washington State has supplied cost aggregated data of their New Flyer (NF) and NF hybrid buses. These data have been analyzed to create statistical relationships based on rising O&M costs per mile with age, which are then integrated with the IP model to determine the impact of changing diesel prices, potential carbon dioxide (CO2) emissions costs, uncertain maintenance costs, and bus purchase cost subsidies. The goal is to aid fleet managers to determine the costs of early or delayed suboptimal bus replacement timing and the impacts of market variability on fleet costs and optimal replacement timing. The optimal replacement age for NF and NF hybrid buses based on King County data and current fuel prices of $3.99/gal are 16.7 and 18.3 years, respectively. It has been consistently observed that greater expense is incurred when buses are replaced earlier rather than later from optimal. To minimize total CO2 emissions (including operation and construction emissions), buses should be replaced slightly before the optimal replacement time without considering CO2 emissions. High diesel prices and CO2 emissions had little or no effect, on when buses should be replaced. However, higher maintenance costs reduced the optimal replacement time by almost two years. Although NF hybrid buses have been found to have no economic advantage over conventional buses, this finding may be a consequence of the different costs associated to the different routes operated by hybrid and conventional buses. Due to the lack of detailed King County's route level historical data, a study of the economic competitiveness of NF hybrids against conventional buses is outside the scope of this thesis. If buses are used less with age, the optimal replacement age is reduced. The optimal replacement age also dropped significantly when the Federal Transit Agency's procurement assistance is applied into the model. The procurement assistance can be up to 80% of the capital costs and can be considered a purchase subsidy from the transit agency viewpoint. If purchase subsidies decrease bus purchase prices by 1%, the optimal replacement age drops approximately 1.5%. When the bus purchase price is reduced by 80%, the optimal bus replacement age is less than 12 years, the FTA's minimum replacement age.