Applying a structured simulation-based methodology to assess carpooling time-space potential

Increasing urban traffic congestion calls for the study of alternative measures. One such measure is carpooling, a system in which a person shares his private vehicle with one or more people in a commuter trip. In principle, this system could lead to potentially significant reductions in the use of private vehicles; however, in practice it has achieved limited success. In this paper, we apply a simulation-based methodology that uses aggregated data from commuter trips in an urban area to create compatible and feasible random trips. These are then analyzed through a heuristic process recursively to find grouping possibilities, thus producing indicators of carpooling potential such as the percentage of matched trips. Using this methodology, simulations are run for the Lisbon Metropolitan Area (Portugal) and results show that an increase in the number of participants in a carpooling scheme will only increase the probability of matching up to a certain point, and that this probability varies significantly with time-space trip attributes.