abstract: Informal public transport is commonplace in the developing world, but the service exists in the United States as well, and is understudied. Often called "dollar vans", New York's commuter vans serve approximately 120,000 people every day (King and Goldwyn, 2014). While this is a tiny fraction of the New York transit rider population, it is comparable to the total number of commuters who ride transit in smaller cities such as Minneapolis/St Paul and Phoenix. The first part of this study reports on the use of commuter vans in Eastern Queens based on a combination of surveys and a ridership tally, all conducted in summer 2016. It answers four research questions: How many people ride the vans? Who rides the commuter vans? Why do they ride commuter vans? Do commuter vans complement or compete against formal transit? Commuter van ridership in Eastern Queens was approximately 55,000 with a high percentage of female ridership. Time and cost savings were the main factors influencing commuter van ridership. Possession of a MetroCard was shown to negatively affect the frequency of commuter van ridership. The results show evidence of commuter vans playing both a competing and complementary role to MTA bus and subway transit. The second part of this study presents a SWOT analysis results of commuter vans, and the policy implications. It answers 2 research questions: What are the main strengths, weaknesses, opportunities and threats of commuter vans in Eastern Queens? and How do the current policies, rules and regulations affect commuter van operation? The SWOT analysis results show that the commuter van industry is resilient, performs a necessary service, and, with small adjustments that will help reduce operating costs and loss of profits have a chance of thriving in Eastern Queens and the rest of New York City. The study also discusses the mismatch between policy and practice offering recommendations for improvement to ensure that commuter vans continue to serve residents of New York City. / Dissertation/Thesis / Masters Thesis Urban and Environmental Planning 2017

There has been an increased push away from the traditional combustion-engine powered vehicle due to environmental, health, and political concerns. As a result, alternative methods of transportation such as electric vehicles (EVs) have gaining popularity in the market. However, the EVs are not penetrating the market as quickly as expected, due in part to a combination of range, charge anxiety, and their financial costs. EVs cannot travel far due to limited driving range and require longer charge times than combustion-engine powered vehicles to recharge. Coupled with a lacking infrastructure for charging, the feasibility of an all-electric transportation market is still not possible. We propose a novel system in which we study and characterize the feasibility of increasing the effective driving range of a battery electric vehicle by utilizing inductive charge transfer to create an ad-hoc charging network where vehicles can “share” charge with one another. The application of wireless charge transfer from vehicle-to-vehicle (V2V) is the first of its kind and does not require any changes to current metropolitan infrastructures. Through the use of computer networking and communications algorithms, we analyze real-world commuter and taxi data to determine the potential effectiveness of such a system. We propose a participation and incentive mechanism to encourage participation in this network that enables the system to be functional.To illustrate proof of principle for V2V charging at traffic lights, we simulate a simplified model in which vehicles only exchange charge at traffic lights without coordination with other vehicles. Using a greedy heuristic, vehicles only exchange charge if they happen to meet another vehicle that has charge to share. The heuristic is greedy since decisions are made at each iteration with longer optimality not being considered. We are able to demonstrate an increase in effective driving range of EVs using these simplistic assumptions. In this thesis, we develop and quantify a complete simulation framework, which allows EVs to operate using charge sharing. We analyze data from the United States Department of Transportation, New York City Taxi and Limousine Commission, and Regional New York City data sources to understand the cumulative driving distance distributions for passenger/commuter vehicles and taxicabs in large metropolitan areas such as New York City. We show that the driving distributions can best be represented as heavy-tail distribution functions with most commuter vehicles not requiring additional charge during a typical day’s usage of their vehicle as compared to taxicabs, which regularly travel more than 100 miles during a 12-hour shift. We develop and parameterize several variables for input into our simulation framework including driving distance, charge exchange heuristics, models for determining pricing of charge units, traffic density, and geographic location. The inclusion of these parameters helps to build a framework that can be utilized for any metropolitan area to determine the feasibility of EVs. We have performed extensive evaluation of our model using real data. Our current simulations indicate that we can increase the effective distance that an electric vehicle travels by a factor of at least 2.5. This increased driving range makes EVs a more feasible mode of transportation for fleet vehicles such as taxicabs that rely heavily on commuting long cumulative distances. We have identified areas for future improvement to add further parameters to make the model even more sensitive. Finally, we focus on the application of our charge sharing framework in a real-world application for utilizing this methodology for the New York City bus system. In partnership with the New York City MTA, we launched a feasibility study of converting the currently majority hybrid bus fleet into a complete electric bus fleet with charging available at bus stops during scheduled bus stops. Unlike the earlier charge sharing framework, this simulation focuses on discrete distances that are traveled by the bus before having an opportunity to charge at the next bus stop. In this scenario, a large source of variability is the amount of time that the bus is able to stop at a bus stop for charging since this is determined by the amount of time needed to successfully embark and disembark the passengers at the given bus stop. This particular variability impacts how much charge the bus is able to gain during any given stop. We conclude with a list of opportunities for future work in expanding the model with additional parameters and conclusions of our work. Further, we identify areas of further research that outline the potential positive and negative outcomes from a charge sharing system that can be extended to various other applications including micro-mobility applications such as electric scooters and bicycles.