Cover Image

Not for Sale

View/Hide Left Panel
Click for next page ( 10

The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement

Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 9
9 enduring (e.g., driver personality, vehicle design, and road- involved truck was given a full safety inspection. Other crash way design) and those that are temporary (e.g., driver rest data files based on standard police investigations usually status, vehicle condition, and weather). Accordingly, each of generate lower percentages because these investigations these three categories can be split into enduring versus tempo- only note obvious system failures (Blower 2009). Roadside rary, for finer classification of safety interventions. Additional inspection statistics for FY2010 indicate that 19.5% of trucks columns are added for macro-level (government, industry, and and 6.5% of buses were placed out-of-service (OOS) owing society) and motor carrier factors, though most often these to vehicle faults (FMCSA 2010). Note, however, that road- actors affect safety through specific effects on drivers, vehicles, side inspections are targeted toward higher-risk carriers and or roadways. Table 2 includes these expanded breakouts and thus do not represent a random sample of commercial vehi- classifies the safety strategies of this report into an expanded cles in transport. CVO Safety Matrix based on the project review of the research and product literature, project surveys, and carrier interviews. In spite of these statistics, better carriers, including those All of the strategies addressed in this report are pre-trip and accessible to this study through project surveys, generally pre-threat interventions affecting one or more of the following have well-established and effective vehicle maintenance pro- factors: grams. In well-managed fleets, as much as 80% of vehicle maintenance is planned rather than reactive (Arsenault 2010). Driver temporary states; Corsi and Barnard (2003) conducted a survey of "best safety Vehicle design and equipment; performers" to identify and define their safety management Vehicle condition; programs and policies, including some practices covered in Roadway design and traffic patterns; and this report. They identified 148 safe motor carriers through a Road environment condition (e.g., weather). two-step process that included review of SafeStat perfor- mance data and obtaining recommendations from FMCSA In most cases, the safety benefits of the practices listed in State Division Directors. An extensive survey was completed Table 2 are well established. For at least two interventions by these 148 safe carriers and formed the basis for their (vehicle size changes and onboard computers and communi- report. The study found that 56% of these fleets used com- cations), net safety benefits or disbenefits are not exclusively puterized equipment maintenance programs, with the per- determined. They are still listed as strategies for considera- centage ranging from 78% for the largest fleets to 23% for the tion. One intervention, optimizing times of travel, relates smallest. Most (61%) of their computerized programs gener- strongly to two crash risk factors: driver temporary states ated specific part failure analyses. Such percentages would (e.g., night driving during low circadian periods) and road- likely be higher today, given the advancement of technolo- way design and traffic patterns (i.e., varying traffic density at gies and data systems supporting vehicle maintenance. different times). These factors may operate in opposite direc- tions at different travel times, thus complicating the problem Supportive attitudes toward fleet vehicle maintenance were of optimizing times of travel. strong in the Corsi and Barnard (2003) study. About 76% of carriers agreed or strongly agreed with the statement, "Cost is PREVENTIVE MAINTENANCE no issue when it comes to keeping our vehicles defect-free." About 80% agreed that, "Deploying a defect-free fleet is the Mechanical deficiencies are common in large trucks, reflec- most important thing we can do to ensure highway safety." tive of their large size, many components, and operational In CTBSSP Synthesis 1, Effective Commercial Truck and Bus use. In the LTCCS, 40% of crash-involved trucks had some Safety Management Techniques (Knipling et al. 2003), the vehicle-related deficiency or malfunction, although these project safety survey asked managers to rate the effectiveness were the proximal cause (Critical Reason or CR) for only of 28 fleet safety management practices. Regularly scheduled about 4% of crashes (excluding cargo shifts, which were vehicle inspection and maintenance was rated the most effec- another 2%). In the LTCCS, vehicle deficiencies as associ- tive of the 28 practices. In the present project survey, 77 of 79 ated factors were more common for combination-unit trucks safety-manager respondents reported using a preventive main- (CTs) (43% of involvements) than for single-unit trucks tenance (PM) schedule and record for each vehicle, and 62 of (STs) (33%). There was a clear association with crash cate- 78 used PM software or spreadsheets. Both practices were gory and fault (CR assignment), as follows: rated among the most effective of the carrier practices pre- sented. Ironically, perhaps, vehicle condition was rated as Truck single-vehicle crash involvements: 62%; among the factors with the least effect on overall crash risk Truck multivehicle involvements, truck at-fault: 50%; among the five factors presented (enduring driver traits, tem- and porary driver states, vehicle factors, roadway characteristics Truck multivehicle involvements, truck not-at-fault: and traffic, and weather). This finding might partially reflect 21%. that, as with the two earlier surveys cited, the current survey drew its respondents primarily from among safety-conscious These high percentages for vehicle condition as an asso- fleets. These results may characterize these better fleets, but ciated factor were seen in the LTCCS because every crash- should not be considered representative of the entire industry.