Developing Ridesharing, but for Which Trip Category? A Comparative Analysis for the Paris Region

While ridesharing is expected to grow rapidly, a major policy issue is to know which trips should be targeted first, e.g., long trips or frequent yet often shorter trips. This paper develops an algorithm to investigate various ridesharing adoption patterns based on distinct trip characteristics, in order to evaluate which leads to the greatest improvement regarding traffic conditions and the environment. The trip characteristics considered are distance, travel time, and trip frequency. This leads to three ridesharing scenarios, which are then evaluated using a traffic assignment model. The methodology is applied to a Paris region case study. We find that ridesharing growth scenarios based on trip frequency contribute more to the mitigation of traffic congestion and CO₂ emissions than scenarios based on trip distance and on travel time. Some policy recommendations about this effective factor for ridesharing are discussed.