This paper examines the chief findings of research conducted on policies to foster off-hour deliveries (OHDs) in the New York City metropolitan area. The goal was to estimate the overall impacts of eventual full implementation of an OHD program. As part of the research, a system of incentives was designed for the receivers of deliveries the system combined Global Positioning System (GPS) remote sensing monitoring with GPSenabled smart phones to induce a shift of deliveries to the off-hours from 7:00 p.m. to 6:00 a.m. The concept was pilot tested in Manhattan by 33 companies that switched delivery operations to the off-hours for a period of 1 month. At the in-depth interviews conducted after the test, the participants reported being very satisfied with the experience. As an alternative to road pricing schemes that target freight carriers, this was the first real-life trial of the use of financial incentives to delivery receivers. The analyses indicate that the economic benefits of a full implementation of the OHD program are in the range of $147 to $193 million per year, corresponding to savings on travel time and environmental pollution for regular-hour traffic as well as productivity increases for the freight industry. The pilot test also highlighted the great potential of unassisted OHDthat is, OHD made without personnel from the receiving establishment present-because almost all participants who used this modality decided to continue receiving OHD even after the financial incentive ended.

Understanding evacuation response behavior is critical for public officials in deciding when to issue emergency evacuation orders for an impending hurricane. Such behavior is typically measured by an evacuation response curve that represents the proportion of total evacuation demand over time. This study analyzes evacuation behavior and constructs an evacuation response curve on the basis of traffic data collected during Hurricane Irene in 2011 in Cape May County, New Jersey. The evacuation response curve follows a general S-shape with sharp upward changes in slope after the issuance of mandatory evacuation notices. These changes in slope represent quick response behavior, which may be caused in part by an easily mobilized tourist population, lack of hurricane evacuation experience, or the nature of the location, in this case a rural area with limited evacuation routes. Moreover, the widely used S-curves with different mathematical functions and the state-of-the-art behavior models are calibrated and compared with empirical data. The results show that the calibrated S-curves with logit and Rayleigh functions fit empirical data better. The evacuation behavior analysis and calibrated evacuation response models from this hurricane evacuation event may benefit evacuation planning in similar areas. In addition, traffic data used in this study may also be valuable for the comparative analysis of traffic patterns between the evacuation periods and regular weekdays and weekends.

Evacuation modeling and analysis are concerned primarily with identifying the types of traffic movements associated with a disaster evacuation, as well as the estimation of evacuation and clearance times. Thus, an efficient evacuation planning model is important in determining evacuation times, identifying critical locations in the transportation network, and assessing traffic operations strategies and evacuation policies. In this paper various scenarios, including a hurricane, a toxic chemical leak, dirty bombs, and a nuclear event, are studied to understand the evacuation and highway network effects of the evacuating population. Unlike corridor studies or bottleneck studies found in the literature, a network model with equilibrium assignment is used. The scenarios are tested with a case study of Northern New Jersey, modeled with the North Jersey Regional Transportation Model–Enhanced, a large-scale travel demand model of the region. The results presented in this paper focus on the effect of several assumptions and input data on the evacuation estimates, giving planners an idea of the necessary considerations for evacuation planning with a modeling context. The experience with this study shows that regional planning models are suitable tools to model evacuation; however, the modeler must be careful in their use. Multiple methodologies can be used, and assumptions, such as time of day, notice or no-notice, passengers per car, and background traffic in the network, have wide-ranging effects.

The cost of transportation plays an important role in residential location choice. Reducing transportation costs not only benefits the user but also improves the performance of the system as a whole. A direct impact of transit-oriented development (TOD) is the change in out-of-pocket costs for users, as well as the changes in costs of externalities and agency benefits. The prime mover for these changes is the shift in population when a TOD is built near train stations and the induced mode shifts from driving to transit. In this study several sites throughout New Jersey were evaluated to determine the cost of driving versus the cost of using rail transit to major employment destinations in New Jersey and New York City. Driving costs were composed of vehicle operating costs (including fuel, wear and tear, and depreciation), value of time based on the highway travel time from origin to destination, parking cost, and cost of externalities such as air and noise pollution, road maintenance, and accidents. Transit costs were composed of fares, parking costs, and values of travel time, waiting time, and transfer time. The likely changes in population resulting from the TOD were used to estimate changes in highway and transit trips. The costs were compared to derive the net benefit for transportation system users as a result of the TOD. Generally, TOD results in financial benefits to the user and the transportation system.

Abstract