A downtown on-street parking model with urban truck delivery behavior

In this study we present an on-street parking model for downtowns in urban centers that incorporates the often-neglected delivery demand of delivery trucks. The behavior of truck deliveries is distinctly different from commuter parking: trucks do not cruise for parking spaces, and demand for goods delivery is driven by customers and is practically inelastic to the delivery costs. We generalize the downtown on-street parking model from Arnott and Inci (2006) to study the relationship between passenger vehicles' parking and truck delivery behaviors, and provide tools for policy makers to optimize the trade-offs in parking space allocation, pricing, and aggregate network congestion. The social optimum can be obtained by solving a nonlinear optimization problem. The parking model is able to replicate the commuter-only scenario as a special case. It is shown that ignoring truck delivery behavior can significantly overestimate travel speeds and cruising stock. We applied the model to a case study of downtown Toronto and found that compared to a baseline scenario representative of Toronto in 2015, increasing parking fees from CAD $4/h to nearly CAD $7.85/h and assigning 4.1% of parking spaces to truck deliveries would eliminate cruising and truck double-parking, resulting in a social surplus gain of over CAD $14,304/h/mile2. In a first-best allocation scenario where total parking spaces can also change, we found that increasing total parking spaces by 18%, having 3.5% truck delivery allocation, and reducing parking fees to CAD $2.47/h would eliminate cruising and double-parking while increasing social surplus by CAD $24,883/h/mile2. These model findings are along the same level of effect as demonstrated in the literature.