Research Publications

Efficient urban transportation is critical to the sustainability of any urban systems. Cities suffering from severe congestions, which not only increases energy consumption leading to decreased air quality, but also reduces road safety and raises the cost of living. Recent development in information and communications technology such as smart phones and varies applications (apps) enables people to exchange information in real-time and makes participation in the “shared economy” more feasible. For example, Uber has announced its soon to be launched ride sharing function UberPool. How much would a city benefit environmentally from ride sharing? This research quantifies the “sharability” of individual mobility needs in Beijing, China as a case study and evaluates the potential changes in energy consumption, greenhouse gas emissions, and criteria pollutants that ride sharing can bring. Using large-scale vehicle trajectory data for private vehicles and taxis, we first evaluate trip origin-destination pairs to characterize individual travel demands. We then optimize this network to quantify the “sharability” of trips. We integrate network analysis with traditional environmental assessment methods to measure the associated environmental implications of ride sharing. Temporal variations of the mobility demands are considered to ensure the feasibility of ride sharing. We also compare multiple ride sharing mechanisms (e. g. two people share a taxi versus six people share a van) and transportation modes (e. g. door-to-door service versus hub-to-hub service connected by multi-mode transportation) to inform sustainable transportation policy decisions.