Strategies to Reduce Ride-Hailing Fuel Consumption Caused by Pick-Up Trips: A Mathematical Model under Uncertainty

Abstract

Uber, Gojek, and Grab are companies providing new massive job opportunities for driver partners. Ride-hailing provides convenient services because passengers can determine the position of the vehicle picking the, up in real time. Ride-hailing also provides security because passengers can quickly determine the driver’s identity. However, the rapid development of ride-hailing has led to increased congestion and emissions. This study proposes pick-up strategies to reduce fuel consumption and emissions, formulated as an assignment model. The assignment problem is abstracted into a linear programming model by considering the uncertainty of the parameters represented by fuzzy numbers. The proposed assignment model can handle the uncertainty of travel delays caused by unpredictable traffic conditions. The assignment aims to minimize fuel consumption, travel delays, and unserviced requests. The assignment model is designed to work for platforms that allow passengers to walk according to their readiness and the maximum walking distance. The numerical simulation results show that allowing passengers to walk to the vehicle can maintain optimality and significantly reduce fuel consumption. The proposed model’s implementation is expected to enable sustainable transport and significantly mitigate emissions caused by vehicle mobility in picking up passengers.