A downtown on-street parking model with urban truck delivery behavior Ahmed Amer a , Joseph Y.J. Chow b,⇑ a Department of Civil Engineering, Ryerson University, Toronto, ON, Canada b Department of Civil and Urban Engineering, New York University, New York, NY, USA article info Article history: Available online 12 September 2016 Keywords: Downtown parking model Delivery trucks Truck deliveries Double parking City logistics abstract 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 park- ing 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 repli- cate 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 sce- nario 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 cruis- ing and truck double-parking, resulting in a social surplus gain of over CAD $14,304/h/ mile 2 . 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/mile 2 . These model findings are along the same level of effect as demonstrated in the literature. Ó 2016 Elsevier Ltd. All rights reserved. 1. Introduction As the rate of urbanization increases, societies struggle to develop policies to make the most efficient use of space to cope with congestion. Parking management is one such policy. Poorly implemented parking policies can lead to ‘‘cruising” for parking spaces, which can account for more than 30% of downtown traffic in some cases (Shoup, 2005). On the other hand, parking pricing strategies can be more effective than road pricing strategies because of a greater public acceptance. The effectiveness of parking policies can also be enhanced by such engineered technologies as real time information systems (e.g. Cao and Menendez, 2015) like SFpark.org or data-driven parking pricing (Qian and Rajagopal, 2013; Mackowski et al., 2015). http://dx.doi.org/10.1016/j.tra.2016.08.013 0965-8564/Ó 2016 Elsevier Ltd. All rights reserved. ⇑ Corresponding author. E-mail address: joseph.chow@nyu.edu (J.Y.J. Chow). Transportation Research Part A 102 (2017) 51–67 Contents lists available at ScienceDirect Transportation Research Part A journal homepage: www.elsevier.com/locate/tra