A pairing ridesharing model to reduce congestion in large urban areas.

Modern world is facing difficult times with regard to newly developed concepts like livability and sustainability. Increasingly growing urban areas are dealing with an escalation of traffic congestion and all its consequences in terms of overall delay experienced by travelers. Ridesharing is intuitively a practical solution to improve the congestion issues in our modern cities. The largely unused capacity of the private vehicles would be utilized in place of other vehicles to satisfy the mobility needs of individual passengers. A large-scale proper implementation of it would be one of the effective methods to satisfy the mobility need of travelers and reduce congestion effects. This research utilizes the available large dataset of taxi data from the City of Chicago. Taxi demand is analyzed and spatial-temporal distributions are developed to perform simulation analyses intended to investigate the effects on the transportation network assuming a percentage of the demand is willing to be served in a ridesharing mode. Service level constraints are considered to ensure acceptable quality for travelers in terms of added journey time and waiting time. We are considering the pairing model, consisting of assuming only pairs of compatible passengers are combined. The goal is to maximize the total mileage saving and therefore reduce the total driving time on the road network. The main finding of this study includes quantification of the mileage saving as a function of: 1) The participation of the passengers in the ridesharing mode; 2) The service level guaranteed to participating customers, in terms of maximum waiting time and additional riding time. The findings provide convincing tools and detailed information for planners and policy makers to consider incentives for the transformation of traditional taxi services to ridesharing service, improving traffic congestion conditions. [ABSTRACT FROM AUTHOR]