Ride-pooling adoption model for $\mathrm{CO_2}$ emission estimation

Abstract

With the climate emergency and growing challenges ranging from pollution to congestion, ride-pooling (rp) has been floated as a potential solution for less congested, low-carbon and more space-efficient urban transportation. However, it is unclear which system configurations will enable an economically viable case for shared pooled mobility. To develop a more profound comprehension of the mechanisms underlying this subject, we here develop a simplified model to analyze the switching potential and \coo emissions of ride-pooling systems for a specified number of transport users, road network topology, and other system parameter values. This analysis is conducted across a broad range of switching probability functions (defined as the probability that a car or public transport user switches to ride-pooling) between an upper and lower bound of switching behaviour assumptions. Based on current Berlin parameters and the basic switching probability function, we find that ride-pooling can reduce the carbon emissions resulting from local transportation in Berlin by approximately 39\%. Policies that reduce the time factor - such as the provision of priority lanes - have the greatest effect in encouraging ride-pooling. For the system to be efficient and achieve measurable reductions in carbon emissions, the fleet size must be large enough. Across the range of switching probability functions, our results demonstrate that a fleet of 6,000 to 23,000 minibuses would be optimal to serve Berlin and reduce system-wide emissions.