Map matching imprecise trajectories for smart mobility applications - Jagadeesh, George Rosario (Nanyang Technological University, 2019)
Trajectory data generated by smart mobile devices are useful for inferring traffic conditions and travel patterns in order to enable smart mobility. The effective utilisation of such data depends on a crucial step known as map matching that matches raw trajectories to paths in a transport network. Existing trajectory-based applications mostly rely on relatively precise trajectories generated by the Global Positioning System (GPS). However, it is preferable to use noisy trajectories generated by alternative technologies such as Wi-Fi positioning and cellular network positioning due to their high energy efficiency, availability in GPS-denied environments and better privacy protection. Furthermore, bandwidth and storage-space considerations dictate that trajectories be sampled sparsely. This thesis examines the challenging problem of map matching such noisy and sparse trajectories in an accurate and efficient manner.