Assessing the impact of urban off-hour delivery program using city scale simulation models

Abstract

This paper describes two different types of models to assess the traffic impacts of an off-hour delivery program for the New York City (NYC) borough of Manhattan. Traffic impacts are measured in New York City metropolitan region using both a regional travel demand model and a mesoscopic simulation model. Analysis is conducted to determine the effectiveness and impacts of the scenarios modeled; focusing on the changes predicted by the traffic models. The results from both models are compared and analyzed, and a discussion on the usage of these models is presented. While macroscopic models can be used to measure traffic effects in a large urban region, mesoscopic models similar to the one used in this paper have their advantages in terms of better quantifying traffic impacts of system-wide benefits. However, simulation time makes it impractical to use mesoscopic simulation for large urban regions. In this work, both the macroscopic regional travel demand model and a mesoscopic sub-simulation network show a measurable impact to congestion and network conditions. However, even when the results show an increasing benefit in terms of travel time savings and increasing speeds, cost–benefit analysis show that when compared with the costs (in this case implementation costs by providing incentives), only small receiver participation justifies the costs of the off-hour deliveries (OHD) program. As incentive amounts increase, receiver participation increases greatly, though the monetized traffic benefits do not necessarily increase at the same rate. Additional analysis was also performed with a targeted program where large traffic generators and large businesses were the recipients of the incentive. The benefits of the targeted program are estimated to be roughly equivalent to the cheapest scenario run for the broad-based program ($5,000 tax incentive assumption) at a fraction of the cost.