|Principal Investigator||Daniel Rodríguez Román, Ph.D.|
|Final Report (DOI)||Available Soon|
|Policy Brief||Available Soon|
|RIP||View RIP entry|
A new travel demand management (TDM) strategy is proposed that integrates ride-matching and parking management to tackle traffic congestion and air pollution problems that arise when the demand for parking spaces exceeds parking supply. The standard TDM policy to address this problem is parking pricing, which, although efficient, presents significant social equity challenges. Income-based equity concerns are sidestepped in the proposed strategy by implementing a centralized optimization system that assigns parking spaces, free of out-of-pocket costs, according to users’ reservation requests, users’ travel schedules, and available parking supply. Concurrent to the parking assignment process, the system coordinates carpools by finding minimum cost matches between drivers whose parking requests were accepted and system participants that require transportation, either because their parking requests were denied by the system or because they do not have other means of transportation. The project’s main objectives are to i) define and explore the potential features and challenges of the proposed parking assignment and ride-matching (PARM) policy, ii) develop a mathematical optimization approach to jointly solve the parking assignment and ride-matching problem underlying the TDM strategy, iii) evaluate the public’s perception of the strategy, and iv) create a proof-of-concept application of a PARM system. Surveys and discrete choice experiments will be used to evaluate the public response to the new TDM strategy, particularly relative to parking pricing and in the context of universities and office buildings. The strategy’s potential impacts will be explored by implementing a prototype PARM system at the University of Puerto Rico at Mayagüez.