Recent developments in the shipping industry have opened some unprecedented trade opportunities on various levels. Be it individual consumption or business needs, the thought of receiving a package on the same day or within 4-hour from some other business or industry in the urban area is worth appreciating. The congestion on ground transportation modes is higher than ever. Since currently the same-day delivery in urban areas is carried mainly by ground modes, the catchment area of this delivery service is limited. The On-Demand Mobility for cargo can elevate the concept of express shipping in revolutionary ways. It will not only increase the catchment area thereby encompassing more business and consumers but will also expedite the delivery as these vehicles will fly over the ground traffic. The objective of this study was to estimate the total demand for ODM Cargo operations and study its effect on ODM passenger operations. The area of interest for this study was Northern California (17 counties). Annual cargo flows in the study area were rigorously analyzed through databases like Transearch, Freight Analysis Framework-4, and T-100 International for freight. The results of this study are presented through a parametric analysis of market share. The end product also includes the flight trajectories (with flight plan) of daily ODM cargo flights in the study region. The On-Demand Mobility cargo operations are expected to complement passenger On-Demand Mobility operations. Therefore, the effect of ODM cargo operations on the passenger ODM operations was also analyzed in this study. The major challenge faced in this study was the unavailability of datasets with the desired level of details and refinements. Since the movement of cargo is mostly done by private companies, the detailed records of shipments are often not public knowledge. / Master of Science / The recent advancements in shipping industry has made transfer of goods both domestic and international, swifter and more reliable. Nowadays, some business and consumers in urban areas have the options of few-hours or same day delivery. Currently the same-day delivery in urban areas is carried mainly by ground modes (trucks) and hence the catchment area of this delivery service is limited. Adding to it, the traffic congestion on the urban roads is a major hinderance in growth of such services. The On-Demand Mobility for cargo can reform express shipping in revolutionary ways. The concept vehicle can fly over the ground traffic. Therefore, it will increase the catchment area thereby encompassing more business and consumers, along with faster delivery options in currently serviced areas. For the study, we analyzed different databases for annual cargo flows in the region. Seventeen counties in the Northern California were chosen as the study area (or region). The study was focused on estimating the potential market (demand) for the On-Demand Mobility Cargo operations. Multiple set of results were calculated for different market shares that On-Demand Mobility can potentially capture in cargo operations. Flight trajectories (with flight plan) for daily ODM cargo flights were the final product. The On-Demand Mobility cargo operations are expected to complement passenger ODM operations. Therefore, the effect of ODM cargo operations on the passenger ODM operations was also analyzed in this study. The major challenge faced in this study was the unavailability of datasets with the desired level of details and refinements.

On-Demand Mobility (ODM) is a concept to address congestion problems. Using electric aircraft and vertical take-off with limited landing (VTOL) capabilities, the ODM concept offers on demand transportation service between designated landing sites at a fraction of driving time. The purpose of this research is to estimate the potential ODM demand and understand the challenges of introducing ODM using the Northern California region (including major cities like San Francisco, Sacramento, and San Jose) as an area of study and a second, less rigorous analysis for the Washington-Baltimore region. A conditional logit model was developed to estimate mode choice behavior and to estimate ODM demand; presenting automobile and public transportation as the two competing modes to ODM. There are significant challenges associated with the service including ability to operate in bad weather, vehicle operating cost, siting and cost of landing sites, and overall public acceptance of small, remotely operated aircraft. Nine scenarios were run varying the input for a base fare, landing fare, cost per-passenger-mile, auto operational costs, and ingress (waiting) times. The results yielded sensitivity of demand to all these parameters and especially showed a great difference in demand when auto costs were decreased from the standard American Automobile Association (AAA) cost per mile to a likely, future auto operating cost. The challenge that aerospace engineers face is designing an aircraft capable of achieving lower operational costs. The results showed that in order for the ODM to be a competitive mode, the cost per passenger-mile should be kept at $1. / Master of Science / On-Demand Mobility (ODM) is a concept to address congestion problems. Using an electric propulsion aircraft, the ODM concept offers on demand transportation service between designated landing sites at a fraction of driving time; an “air taxi” or “air Uber” as coined by media outlets. The purpose of this research is to estimate the potential ODM demand and understand the challenges of introducing ODM using the Northern California region (including major cities like San Francisco, Sacramento, and San Jose) as an area of study and a second, less rigorous analysis for the Washington-Baltimore region. A model was developed to estimate mode choice behavior and to estimate ODM demand based on existing travel behavior and patterns in the Northern California region. There are significant challenges associated with the service including ability to operate in bad weather, vehicle operating cost, siting and cost of landing sites, and overall public acceptance of small, remotely operated aircraft. The results from the model yielded sensitivity of demand to these challenges and especially showed a great difference in demand as the cost of operating the car decreases in the future, making it a great competitor to the ODM concept. The major challenge that aerospace engineers face is designing an aircraft capable of achieving lower operational costs. The results showed that in order for the ODM to be a competitive mode, the cost per passenger-mile should be kept at $1.

Public transport is an efficient way to transport large volumes of travellers. However, there are systemic issues that make it hard for conventional public transport to provide efficient service on finer levels, like first- and last-mile problems or low-demand areas. One of the potential solutions that has been getting a lot of attention recently in research and real practice is Demand-Responsive Transport(DRT). The main difference between demand-responsive services and conventional public transport is the need for explicit requests for a trip from the travellers. The service then adapts the routes of the vehicles to satisfy the requests as efficiently as possible. One of the aims of such transport services is to combine the flexibility and accessibility of travel modes like taxis and private cars with the efficiency of buses achieved through ride-sharing.DRT has the potential to improve public transport in, for example, low population density areas or for people with mobility limitations who could request a trip directly to a home door. Historically DRT has been extensively used for special transportation while the recent trend in research and practice explores the possibility of using this service type for the general population.The history of DRT shows a large degree of discontinued trials and services together with low utilisation of vehicles and limited efficiency levels. In practice, this leads to measures restricting the trip destination, times when service is available, or eligibility to use the service at all in case of special transport DRT. Due to the limited use of DRT services, there is little data collected on the efficiency of the service and transport agencies exploring the possibility of introducing this new service type face difficulties in estimating its potential.The main goal of this thesis is to contribute towards developing a decisionsupport method for transport analysts, planners, or decision-makers who want to evaluate the systemic effect of a DRT service such as costs, emissions and effecton society. Decision-makers should be able to evaluate and compare a large variety of DRT design choices like booking time restrictions, vehicle fleet type, target trip quality level, or stop allocation pattern. Using a design science, we develop a simulation approach which is evaluated with two simulation experiments. The simulation experiments themselves provide valuable insight into the potential of DRT services, explore the niche where DRT could provide the most benefits and advocate taking into account the sustainability perspective for a comprehensive comparison of transport modes. The findings from the simulation experiments indicate that DRT, even in its extreme forms like fully autonomous shared taxis, does not show the level of efficiency that could result in a revolution in transportation — it is hard to compete inefficiency with conventional public transport in urban zones. However, in scenarios with lower demand levels, it could be more efficient to replace conventional buses with a DRT service when considering costs and emissions. We also show that, when integrated with conventional public transport, DRT could help alleviate the last-mile problem by improving accessibility to long-distance lines. Additionally, if car users are attracted to public transport with the help of DRT, there is a potential to significantly reduce the total level of emissions. The simulation results indicate that the proposed simulation method can be applied for the evaluation of DRT. The implementation of trip planning combining DRT and conventional public transport is a major contribution of this thesis. We show that the integration between services may be important for the efficiency of the service, especially when considering the sustainability aspects. Finally, this thesis indicates the direction for further research. The proposed simulation approach is suitable for the estimation of the potential of DRT but lacks the ability to make a prediction of the demand for DRT. Integration of a realistic mode choice model and day-to-day simulations are important for making predictions. We also note the complexity of the DRT routing for large-scale problems which prohibits a realistic estimation with simulation and the efficient operation of the service.

Ride sharing—the bundling of simultaneous trips of several people in one vehicle—may help to reduce the carbon footprint of human mobility. However, the complex collective dynamics pose a challenge when predicting the efficiency and sustainability of ride sharing systems. Standard door-to-door ride sharing services trade reduced route length for increased user travel times and come with the burden of many stops and detours to pick up individual users. Requiring some users to walk to nearby shared stops reduces detours, but could become inefficient if spatio-temporal demand patterns do not well fit the stop locations. Here, we present a simple model of dynamic stop pooling with flexible stop positions. We analyze the performance of ride sharing services with and without stop pooling by numerically and analytically evaluating the steady state dynamics of the vehicles and requests of the ride sharing service. Dynamic stop pooling does a priori not save route length, but occupancy. Intriguingly, it also reduces the travel time, although users walk parts of their trip. Together, these insights explain how dynamic stop pooling may break the trade-off between route lengths and travel time in door-to-door ride sharing, thus enabling higher sustainability and service quality.