A Ride-Sharing System with High Capacity Vehicles and Flexible Meeting Points

In many major cities, fixed route transit systems such as bus and rail serve millions of trips per day. These systems have people collect at common locations (the station or stop), and board at common times (for example according to a predetermined schedule or headway). By using common service locations and times, these modes can consolidate many trips that have similar origins and destinations or overlapping routes. However, the routes are not sensitive to changing travel patterns, and have no way of identifying which trips are going unserved, or are poorly served, by the existing routes. On the opposite end of the spectrum, personal modes of transportation, such as a private vehicle or taxi, offer service to and from the exact origin and destination of a rider, at close to exactly the time they desire to travel. Despite the apparent increased convenience to users, the presence of a large number of small vehicles results in a disorganized, and potentially congested road network during high demand periods. The focus of the research presented in this paper is to develop a system that possesses both the on-demand nature of a personal mode, with the efficiency of shared modes. In this system, users submit their request for travel, but are asked to make small compromises in their origin and destination location by walking to a nearby meeting point, as well as slightly modifying their time of travel, in order to accommodate other passengers. Because the origin and destination location of the request can be adjusted, this is a more general case of the Dial-a-Ride problem with time windows. The solution methodology uses a graph clustering algorithm coupled with a greedy insertion technique. A case study is presented using actual requests for taxi trips in Washington DC, and shows a significant decrease in the number of vehicles required to serve the demand.

Emerging Infectious Disease: Host and Parasite Perspectives

Avian malaria and related haematozoa are nearly ubiquitous parasites that can impose fitness costs of variable severity and may, in some cases, cause substantial mortality in their host populations. One example of the latter, the emergence of avian malaria in the endemic avifauna of Hawaii, has become a model for understanding the consequences of human-mediated disease introduction. The drastic declines of native Hawaiian birds due to avian malaria provided the impetus for examining more closely several aspects of host-parasite interactions in this system. Host-specificity is an important character determining the extent to which a parasite may emerge. Traditional parasite classification, however, has used host information as a character in taxonomical identification, potentially obscuring the true host range of many parasites. To improve upon previous methods, I first developed molecular tools to identify parasites infecting a particular host. I then used these molecular techniques to characterize host-specificity of parasites in the genera Plasmodium and Haemoproteus. I show that parasites in the genus Plasmodium exhibit low specificity and are therefore most likely to emerge in new hosts in the future. Subsequently, I characterized the global distribution of the single lineage of P. relictum that has emerged in Hawaii. I demonstrate that this parasite has a broad host distribution worldwide, that it is likely of Old World origin and that it has been introduced to numerous islands around the world, where it may have been overlooked as a cause of decline in native birds. I also demonstrate that morphological classification of P. relictum does not capture differences among groups of parasites that appear to be reproductively isolated based on molecular evidence. Finally, I examined whether reduced immunological capacity, which has been proposed to explain the susceptibility of Hawaiian endemics, is a general feature of an "island syndrome" in isolated avifauna of the remote Pacific. I show that, over multiple time scales, changes in immune response are not uniform and that observed changes probably reflect differences in genetic diversity, parasite exposure and life history that are unique to each species.