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Urban Freight Lab

Research Topic: Truck Travel Time Performance Measurement and Modeling

Truck travel times measure the flow of freight and identify speed trends over time. They are valuable for assessing the efficiency and performance of transportation systems and are essential for planning, designing, and building better transportation facilities.

Paper

A Framework for Determining Highway Truck-Freight Benefits and Economic Impacts

 
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URL: http://dx.doi.org/10.5399/osu/jtrf.52.2.4156
Publication: Journal of the Transportation Research Forum
Volume: 52
Pages: 27-43
Publication Date: 2013
Summary:
This paper proposes a method for calculating both the direct freight benefits and the larger economic impacts of transportation projects. The identified direct freight benefits included in the methodology are travel time savings, operating cost savings, and environmental impacts. These are estimated using regional travel demand models (TDM) and additional factors. Economic impacts are estimated using a regional Computable General Equilibrium (CGE) model. The total project impacts are estimated combining the outputs of the transportation model and an economic model. A Washington State highway widening project is used as a case study to demonstrate the method. The proposed method is transparent and can be used to identify freight specific benefits and generated impacts.
Though the Washington State Department of Transportation (WSDOT) has a long standing Mobility Project Prioritization Process (MPPP) (WSDOT 2000), which is a Benefit-Cost Analysis (BCA) framework used for mobility program assessment, it does not separately evaluate or account for the truck freight benefits of proposed highway infrastructure projects. It is therefore unable to evaluate and consider the economic impacts of highway projects that accrue to freight-dependent industries (those heavily reliant on goods movement) or non-freight-dependent firms (service sector) that are perhaps indirectly impacted by the productivity of the freight system. The established evaluation criteria of any transportation project largely influences the project selection and direction, thus for freight to become an integrated component of a managing agency’s transportation program, it must be recognized and acknowledged through the project evaluation criteria (NCHRP 2007). Before implementing any freight project evaluation criteria, an agency must first be able to identify the measures that matter to freight and freight-related systems. At this time there is no known nationally accepted framework for analyzing the full range of freight-related impacts stemming from transportation infrastructure projects. Complex interactions with separate, but not isolated, effects among economic, environmental, and social components with sometimes conflicting priorities make freight impacts more difficult to measure than those of other highway users (Belella 2005).
To successfully compete in a new funding world with significantly reduced monies for transportation infrastructure, states must become even more pragmatic about the means by which they emphasize and prioritize investments. Identification of the necessity to include freight performance measures in local, state, and national transportation plans, and rise above anecdotal understandings of system performance, is becoming evident as more municipalities and state agencies move toward implementing freight-related plans (MnDOT 2008, Harrison et al. 2006). Therefore, WSDOT has undertaken the development of an improved methodology to assess highway truck-freight project benefits designed to be integrated into the department’s existing prioritization processes. This paper lays out the development process of this effort and the resulting methodology. The contribution of this paper to the literature is to present a methodology that includes a truck-specific determination of the economic value of a project in addition to the economic impacts captured by a regional Highway Truck-Freight Benefits 28 computable general equilibrium (CGE) framework. The proposed method is transparent, and can be used to identify freight-specific benefits and generated impacts.
The remainder of this paper is organized as follows: the second section provides a brief review of the state of practice in the evaluation of transportation infrastructure investments; the third section details the process by which the benefits to be included in the analysis were selected and the methodology subsequently developed; the next section applies the methodologies to a case study and provides its result; the last section offers conclusions of the proposed methodology as well as the limitations of the study and directions for future work on fully incorporating freight into state DOT investment decisions.

 

 

Authors: Dr. Anne Goodchild
Recommended Citation:
Wang, Zun, Jeremy Sage, Anne Goodchild, Eric Jessup, Kenneth Casavant, and Rachel L. Knutson. "A framework for determining highway truck-freight benefits and economic impacts." In Journal of the Transportation Research Forum, vol. 52, no. 1424-2016-118048, pp. 27-43. 2013.
Paper

Identifying Truck Route Choice Priorities: The Implications for Travel Models

URL: https://doi.org/10.1179/1942787514Y.0000000015
Publication: Transportation Letters
Volume: 6 (2)
Pages: 98-106
Publication Date: 2014
Summary:

This article identifies the truck routing priorities of freight companies through a survey of Washington state shippers, carriers, and receivers. To elicit these priorities, the survey prompted the respondents to rate 15 items believed to affect route choice decision making with respect to each item’s influence on route choice. Item response theory (IRT) and latent class analysis (LCA) highlights priorities that were common among all survey respondents and priorities that were different among the sample.

Minimizing cost and meeting customer requirements were priorities for all. The influence of other items such as road grade, hours of service limits, and driver availability depended on whether the respondent was best described as a long-haul, local-regional, or urban trucking provider. These three classes of companies were derived from the LCA, and each class has a distinct response pattern to the 15 routing items. This result suggests that truck routing priorities are not constant and uniform across a state’s trucking industry but rather variable and largely dependent on trip length. The paper concludes with practical recommendations as to how these priorities can be implemented within a truck routing model.

Authors: Dr. Anne Goodchild, Maura Rowell, Andrea Gagliano
Recommended Citation:
Rowell, Maura, Andrea Gagliano, and Anne Goodchild. "Identifying Truck Route Choice Priorities: The Implications for Travel Models." Transportation Letters 6, no. 2 (2014): 98-106. 
Chapter

Guide for Identifying, Classifying, Evaluating, and Mitigating Truck Freight Bottlenecks

 
Download PDF  (0.78 MB)
URL: http://www.trb.org/Publications/Blurbs/176115.aspx
Publication: Transportation Research Board - NCHRP Research Report
Volume: 854
Publication Date: 2017
Summary:

The demand for truck transportation increases alongside growth in population and economic activity. As both truck and passenger traffic outstrip roadway capacity, the result is congestion, which the freight community experiences as truck bottlenecks. This NCHRP project produced a Guidebook that provides state-of-the-practice information to transportation professionals on practices and measures for identifying, classifying, evaluating, and mitigating truck freight bottlenecks. The intent is to help decision-makers in developing cost-effective solutions to address different types of truck freight bottlenecks.

The Guidebook is designed for use by transportation planners and research and operational staff. Its contents

  • Define a common language related to truck freight bottlenecks
  • Classify truck freight bottleneck categories based on causal and contributing factors
  • Describe truck bottleneck state of the practice
  • Provide highlights from several case studies related to truck bottlenecks
  • Describe data sources used for truck bottleneck analysis
  • Provide a spatially scalable methodology for identifying truck freight bottlenecks
  • Describe quantitative measures for truck freight bottleneck categories for determining bottleneck severity, impact, and ranking and subsequent decision-making
  • Describe mitigation options for truck freight bottlenecks
  • Describe how to integrate freight bottleneck analysis into the planning process.

The Guidebook embraces a broad term for “truck freight bottlenecks” as any condition that acts as an impediment to efficient truck travel, thereby leading to travel times in excess of what would normally occur. This definition encompasses a wide range of events and conditions, all of which add time to the delivery of truck freight shipments, from the time those shipments leave their origin to the time they arrive at their destination.

The Guidebook describes two methodologies for identifying truck freight bottlenecks:

  • A travel speed-based delay methodology, and
  • A process or operation delay-based methodology.

The bottleneck analysis described in the Guidebook focuses on utilizing truck probe data rather than traditional travel demand models. Truck probe speed data can be used in conjunction with other data sources (e.g., crash data, weather data, volume data) to identify the causes of bottlenecks. The methodologies are scalable in multiple ways, and this will allow agencies to use their available data resources regardless of the source or size of those resources. In addition, the same analytical approach will work whether the analysis is performed for an entire state highway network, a regional network, or even a specific city. The recommended approach can also be applied to a single road segment, multiple roads within a geographic corridor, an entire region, to all roads in the state, or to all roads in a multistate region. Finally, the methodology can be used to demonstrate the benefit of bottleneck improvements to truckers, policy decision-makers, and the general public. This is particularly true for bottlenecks based on operational restrictions (such as geometric or height restrictions or truck bans).

Authors: Dr. Anne GoodchildDr. Ed McCormack, Dike Ahanotu, Richard Margiotta, Bill Eisele, Mark Hallenbeck
Recommended Citation:
Ahanotu, Dike, Richard Margiotta, Bill Eisele, Mark Hallenbeck, Anne Goodchild, and Ed McCormack. (2017) Guide for Identifying, Classifying, Evaluating, and Mitigating Truck Freight Bottlenecks. Transportation Research Board. Project 08-98. 2017.