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Walnut Creek, CA, United States

Dau-Ngo T.,Port of Long Beach | Gonzalez I.,Parsons Brinckerhoff | Hilde L.,Fehr and Peers | Jim M.,Parsons Brinckerhoff
Green Streets, Highways, and Development 2013: Advancing the Practice - Proceedings of the 2nd Green Streets, Highways, and Development Conference | Year: 2013

While transportation management plans (TMPs) are commonly developed to address work-zone safety and mobility needs of the traveling public during construction of highway projects, TMPs have yet to be firmly ingrained in the transit planning process. Coordinating and streamlining TMP strategies for both types of transportation projects is increasingly critical given the overlapping needs to maintain the operations of existing transportation systems during construction activities and the growing trend toward sustainability in transportation, including reducing traffic congestion and related air quality impacts. Beyond their traditional application, TMPs can serve as a means for accommodating the construction of transportation improvements while supporting the shift to more sustainable travel patterns once a project is in operation. This paper discusses the process for developing TMPs, while integrating strong sustainability principles. Topics that are addressed include 1) current national and regional TMP guidelines; 2) harnessing the use of the Internet, social media, and mobile-based applications as part of the overall approach to informing the traveling public of construction-related transportation impacts and alternative means of travel; and 3) balancing cost-effective TMP strategies with promoting alternative transportation modes during construction and after a project opens. Proposed recommendations include how to integrate sustainability elements into TMP strategies, how to leverage TMPs to engage the public in minimizing transportation impacts during construction, and how to approach developing TMPs, especially for transit projects. © 2013 American Society of Civil Engineers.


Stanek P.E. D.,Fehr and Peers
Institute of Transportation Engineers Annual Meeting and Exhibit 2012 | Year: 2012

Several analysis methods have been proposed to analyze the vehicular capacity of roundabouts. Some are deterministic equations based on regression equations of observed capacity or observed gap acceptance. Others are stochastic models that simulate driver behavior. Some are equations that can be applied manually or using spreadsheets. Others require computer software to implement. Given these differences, it may not be apparent which method is the best to use for a particular case. When comparing capacity analysis methods, it would be useful to know how the various methods perform over a range of approach and conflicting volumes. This paper reports on the approach capacity for a single-lane roundabout based on the maximum entering and conflicting circulating volumes for several analysis methods. In Roundabouts: An Informational Guide (FHWA, 2000), Figure 4-3 shows a capacity chart according to the recommended capacity equations. Similar capacity charts were prepared for six additional methods: HCM 2000, HCM 2010, SIDRA INTERSECTION, SimTraffic, VISSIM, and Paramics. When applying an analysis methodology, the procedure should be calibrated and validated to field measurements in the study area - particularly for simulation models, which have many adjustable parameters. However, for the comparison presented in this paper, the default parameters were used so that a baseline comparison could be provided. For a particular range of conflicting and entering volumes, some analysis methods predicted higher capacity than others. For different ranges on volumes, other analysis methods were higher. Given this variation, the use of more than one analysis method is suggested so that the analyst will have a higher confidence in the final design recommendation.


Tian G.,University of Utah | Ewing R.,University of Utah | White A.,University of Utah | Hamidi S.,University of Utah | And 3 more authors.
Transportation Research Record | Year: 2015

Current methods of traffic impact analysis, which rely on rates and adjustments from ITE, are believed to understate the traffic benefits of mixed-use developments (MXDs) and therefore to lead to higher exactions and development fees than necessary and to discourage otherwise desirable developments. The purpose of this study was to improve methodology for predicting the traffic impacts of MXDs. Standard protocols were used to identify and generate data sets for MXDs in 13 large and diverse metropolitan regions. Data from household travel surveys and geographic information system databases were pooled for these MXDs, and travel and built-environment variables were consistently defined across regions. Hierarchical modeling was used to estimate models for internal capture of trips within MXDs and for walking, biking, and transit use on external trips. MXDs with diverse activities on site were shown to capture a large share of trips internally, so that the traffic impacts of the MXDs were reduced relative to conventional suburban developments. Smaller MXDs in walkable areas with good transit access generated significant shares of walk, bike, and transit trips and thus also mitigated traffic impacts.


Rixey R.,Fehr and Peers
Transportation Research Record | Year: 2013

This study investigated the effects on bikesharing ridership levels of demographic and built environment characteristics near bikesharing stations in three operational U.S. systems. Although earlier studies focused on the analysis of a single system, the increasing availability of station-level ridership data has created the opportunity to compare experiences across systems. In this study, particular attention was paid to data quality and consistency issues raised by a multicity analysis. This project also expanded on earlier studies with the inclusion of the network effects of the size and spatial distribution of the bikesharing station network, which contributed to a more robust regression model for the prediction of station ridership. The regression analysis identified a number of variables that had statistically significant correlations with station-level bikesharing ridership: population density; retail job density; bike, walk, and transit commuters; median income; education; presence of bikeways; nonwhite population (negative association); days of precipitation (negative association); and proximity to a network of other bikesharing stations. Proximity to a greater number of other bikesharing stations exhibited a strong positive correlation with ridership in a variety of model specifications. This finding suggested that, with the other demographic and built environment variables controlled for, access to a comprehensive network of stations was a critical factor to support ridership. Compared with earlier models, this model is more widely applicable to a diverse range of communities and can help those interested in the adoption of bikesharing systems to predict potential levels of ridership and to identify station locations that serve the greatest number of riders.


Ewing R.,University of Utah | Greenwald M.,Lane Council of Governments | Greenwald M.,Urban Design 4 Health Inc. | Zhang M.,University of Texas at Austin | And 5 more authors.
Journal of Urban Planning and Development | Year: 2011

Current methods of traffic impact analysis, which rely on rates and adjustments from the Institute of Transportation Engineers, are believed to understate the traffic benefits of mixed-use developments (MXDs), leading to higher exactions and development fees than necessary and discouraging otherwise desirable developments. The purpose of this study is to create new methodology for more accurately predicting the traffic impacts of MXDs. Standard protocols were used to identify and generate data sets for MXDs in six large and diverse metropolitan regions. Data from household travel surveys and geographic information system (GIS) databases were pooled for these MXDs, and travel and built environmental variables were consistently defined across regions. Hierarchical modeling was used to estimate models for internal capture of trips within MXDs, walking and transit use on external trips, and trip length for external automobile trips. MXDs with diverse activities on-site are shown to capture a large share of trips internally, reducing their traffic impacts relative to conventional suburban developments. Smaller MXDs in walkable areas with good transit access generate significant shares of walk and transit trips, thus also mitigating traffic impacts. Centrally located MXDs, small and large, generate shorter vehicle trips, which reduces their impacts relative to outlying developments. © 2011 American Society of Civil Engineers.

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