Shrisan Iyer

Overall impacts of off-hour delivery programs in New York city metropolitan area

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 GPS-enabled 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

Use of Regional Transportation Planning Tool for Modeling Emergency Evacuation

147 to

Empirical Evacuation Response Curve During Hurricane Irene in Cape May County, New Jersey

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 OHD—that 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.

ASSIST-ME: Postprocessing Tool for Transportation Planning Model Output

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.

Quantifying Transportation Benefits of Transit-Oriented Development in New Jersey

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.

Ex Post Evaluation of Calibrated Simulation Models of Significantly Different Future Systems

This paper presents Advanced Software for Statewide Integrated Sustainable Transportation System Monitoring and Evaluation (ASSIST-ME), an application for visualizing and analyzing the output of transportation planning models in a geographic information system environment. ASSIST-ME was developed on a customized version of the ArcGIS 9.2 Developer Engine in the Microsoft .NET Framework. The tool is built on a flexible framework that allows for adoption of any traditional transportation planning model, as demonstrated with the output of two major transportation planning models on different software platforms: the New York Best Practice Model, running in TransCAD, and the North Jersey Regional Transportation Model–Enhanced, running in CUBE. ASSIST-ME allows agencies and planners to easily work with transportation planning model output, analysis of which is often time-consuming and requires extensive training. It offers four key functionalities: data visualization, demand analysis, path analysis, and benefit–cost analysis. Data visualization and demand analysis enable the user to work easily with direct model output; the custom path and cost analysis tools support analyses beyond those possible with other software packages. The benefit–cost analysis functions utilize the latest quantification–monetization approaches employed in research and by government agencies and require no external applications or procedures. This process can be used for any planning scenario, but ASSIST-ME also allows for customization to modify input data or analysis procedures according to the users needs. ASSIST-ME incorporates data visualization, data analysis, and output reporting functionalities in a single user-friendly setting that requires minimal training or knowledge of the models themselves.

Overall Impacts of Off-hour Delivery Programs in the New York City Metropolitan Area: Lessons for European Cities

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.

Commercial Vehicle Travel Time Estimation in Urban Networks Using GPS Data from Multiple Sources

The calibration and validation of traffic simulation models are critical procedures in ensuring that developed models accurately represent real-world conditions. When planned future systems are simulated, validation is not possible because field data cannot be collected for a system that has not yet been built. Instead, modelers have no choice but to follow standard calibration procedures and, in the absence of validating data, accept a model that appears to function correctly. Ex post evaluation of traffic simulation models is a neglected, yet valuable, area of research because it offers modelers a chance to validate their future system simulations with field data. The calibration assumptions used by modelers of future systems are investigated by checking whether improvised calibrations hold up to ex post evaluation. A case study directed at measuring the changes to user behavior in an existing and a reconstructed traffic system is presented. In addition, the benefits of ex post evaluation and methods to improve the calibration and validation of future models are discussed.