Smart Cities

The transportation landscape is in transition. Rising congestion, failing infrastructure, changing behaviors, adapting to a more inclusive definition of mobility, the desire for cleaner and more efficient engines, and grappling with the role of autonomous vehicles and drones, to name just some of the factors, demands that we take a fresh approach to designing for mobility. Yet the rapid pace of technology development is creating emerging trends that are driving change faster than our ability to model, design, and manage them. This could potentially result in undesirable economic,...

Miguel Street is a winding, narrow route through the Glen Park neighborhood of San Francisco. Until a few years ago, only those living along the road traveled it, and they understood its challenges well. Now it's packed with cars that use it as a shortcut from congested Mission Street to heavily traveled Market Street. Residents must struggle to get to their homes, and accidents are a daily occurrence. The problem began when smartphone apps like Waze, Apple Maps, and Google Maps came into widespread use, offering drivers real-time routing around traffic tie-ups. An estimated 1 billion...

The present work proposes a framework to calibrate MFD models using mobile phone data. The three major components to calibrate in the present context include MFD shape, regional trip lengths and path flow distribution. Time dependent penetration rates are estimated by fusing the OD matrix and the Loop Detector Data (LDD). The estimated MFDs are stable with very low scatter. In the following step, macro-paths and their corresponding trip lengths are estimated. Dynamic evolution of trip lengths is demonstrated using the present data, which is otherwise very difficult to capture with other...