Making Trucks Count: Innovative Strategies for Obtaining Comprehensive Truck Activity Data (2014) / Chapter Skim
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Pages 18-36
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18 C H A P T E R 3 This research is about innovation that could be used to implement or guide how truck-activity data might be obtained. The research team relied on our experience and expertise as well as project panel input to identify possible strategies for doing so.
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19 feasibility of each alternative considered. The star ratings were summed to calculate a total feasibility score for each strategy.
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20 3.1.1.1 Developing O/D Data for Farm to Assembly Points Farm shipments to assembly points are not included in the CFS at present. Stockyards and grain storage facilities are included.
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21 competent statistical design and logistical handling of these multifold efforts, and the multimodal character of the undertakings would make BTS the only feasible entity for these prospective programs. The strategies would require negotiating institutional responsibilities and cost coverage, which could require considerable time and resources and lower the institutional feasibility rating.
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22 The main focus of the survey is revenues; thus, it has the potential to gather important information on valuemiles by commodity and vehicle type. It is also a potential source of derived information on VMT and ton-miles (see Table 3-3)
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23 resource intensive. Technically, changes can be made in the survey design.
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24 payloads and VMT, and truck VMT could be estimated from VIUS payloads times FAF tonnages (see Table 3-4)
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25 be addressed through future research or in conjunction with a pilot study. Other operational issues include the following: • There may need to be operational changes at the Census Bureau were the survey conducted under the their auspices.
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26 components from many suppliers who use materials from many sources who, in turn, get raw materials from multiple origins. The remainder of this section discusses some of the contingent issues.
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27 Deloitte, such data are highly aggregate and are more attitudinal than behavioral. The sponsor of a supply chain survey obtaining relevant information for transportation policy and planning would need to be a government agency (e.g., sub-unit of the Department of Transportation, Department of Agriculture, Department of Commerce, or Census Bureau)
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28 3.5.3 Operational Feasibility Analysis tools could be constructed easily to produce accurate truck VMT counts using operations data available from publically available HPMS reports. Such data, used in conjunction with operations data from a states-count program or the TMAS database, could help in understanding the amount of freight that flows in monitored corridors by truck.
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29 industry has already largely adopted the technology to provide data for fleet management, greatly reducing the barriers for adoption of GPS devices for this strategy. Nevertheless, relying on this strategy would require resolving several other technological issues.
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30 3.6.5 Financial Feasibility The largest financial barrier to implementing a national freight GPS framework would be the collection of data. There are a number of options for collecting GPS data from the nation's private trucking fleets that would reduce cost barriers.
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31 The first challenge relates to accessing data on a national basis. LPR systems are typically acquired and operated by individual jurisdictions, or perhaps by several neighboring jurisdictions.
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32 different vendors use varying data formats and transfer protocols that make sharing difficult. As technologies mature, markets typically converge toward standardized formats, easing interoperability.
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33 3.8.4 Geographic Scalability This could be applied at any geographic level. One has the exact address of the firms and would be able to geocode the stratified sample desired and determine its geographic reach.
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34 3.9.5 Financial Feasibility The cost of Polk data varies by the amount and type of information purchased. There do not appear to be published price schedules, and cost proposals are produced on a customer-bycustomer basis.
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35 schedule trips and routes for their trucks, based on an internal decision rule and orders from shippers. Since the question is about the number of trucks and their route assignment, a higher resolution model that includes truck driver decisions might not bring additional benefits and unnecessarily increase the modeling burden.
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36 Total feasibility scores indicated the levels of risk (low score) and the chances of success (high scores)
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