To address the urban air quality problem, electric vehicles (EV) are often considered as one major contender to reduce emissions from the transportation sector. For a transit-oriented metropolis, in particular, such as Hong Kong, where buses carry over 51% of the daily 11 million passenger trips, emissions from heavy-duty diesel vehicles, mostly buses, constitute up to 80-90% of roadside emissions (EPD, 2013). Electric buses (EB) deployment, hence, is and will remain one key driver for urban air quality management.

Encountering the major obstacles in EB deployment, such as limited range, scarcity of charging facilities, and of course, vehicle cost. How to replace the current bus fleet with EB is one key problem. EB deployment is much more than simply replacing existing buses with E...[ Read more ]

To address the urban air quality problem, electric vehicles (EV) are often considered as one major contender to reduce emissions from the transportation sector. For a transit-oriented metropolis, in particular, such as Hong Kong, where buses carry over 51% of the daily 11 million passenger trips, emissions from heavy-duty diesel vehicles, mostly buses, constitute up to 80-90% of roadside emissions (EPD, 2013). Electric buses (EB) deployment, hence, is and will remain one key driver for urban air quality management.

Encountering the major obstacles in EB deployment, such as limited range, scarcity of charging facilities, and of course, vehicle cost. How to replace the current bus fleet with EB is one key problem. EB deployment is much more than simply replacing existing buses with EB. It is unlikely that the entire bus fleet will be replaced all at once due to financial constraints, nor is it always desirable, as a mixed fleet of existing buses and EB may better complement each other considering the range constraints of EB, vehicle and operation costs, and benefits from emissions reduction. To this end, it is important to design the optimal plan of phasing in EB over time, while ensuring the mixed bus fleet can fully cover the service requirements without negative impacts on the service quality, in terms of travel times and frequencies.

In addition to mixed bus fleet replacement, how to route and schedule the mixed bus fleet, especially EB, under range and recharging constraints is another key problem to be tackled. Moreover, the EB driving range is subject to uncertainty, which may vary with congestion, passenger loading, etc. Their efficient utilization requires an explicit treatment of this range uncertainty in their routing and scheduling plan. Furthermore, it may be beneficial to maintain a mixed fleet of buses, EB and other clean-energy buses, to complement each other for range coverage, vehicle and operating costs, and emissions reduction.

In this thesis, firstly we propose an approach of remaining life additional benefit-cost (RLABC) analysis to solve the frequency-based single bus fleet management (SBFM) problem by gradually replacing and retrofitting the current bus fleet before their nominal retirement. Secondly, we extend the RLABC approach to formulate the frequency-based mixed bus fleet management (MBFM) problem by maximizing the total net benefits resulting from early-retiring, purchasing, and routing the bus fleet within the lifespan of the new replacement buses, referred to as new life additional benefit-cost (NLABC) in this study. Thirdly, by adopting the schedule-based modeling approach, we investigate the routing and scheduling problem of a mixed bus fleet jointly with charging stations. Finally, we extend the third study, and develop a framework to solve the mixed bus fleet location-routing-scheduling problem under range uncertainty