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Comprehensive Truck Size and Weight Limits Study - Highway Safety and Truck Crash Comparative Analysis Technical Report

Chapter 6: Conclusions

The earlier chapters in this report have provided details of the three different types of safety analysis conducted in this effort – (1) crash-based analyses, (2) analysis of vehicle stability and control through simulation, and (3) analysis of safety inspections and violations data. The analyses conducted clearly indicate that the safety implications of the alternative vehicle configurations vary across the array of vehicles examined. Of interest here is whether the findings from the crash-based analyses, the vehicle stability and control analyses, and the inspection and violations analyses supported each other.

Tractor-Semitrailer Analyses

In general, for Scenarios 2 and 3, in the limited number of States that could be analyzed, the six-axle alternative truck configurations have higher crash rates than the five-axle tractor-semitrailer control truck configurations, particularly the 97,000-lb., six-axle alternative truck configuration. The consistency of results across the three States whose data were used strengthens the validity of the results.

The Scenario 2 crash analysis showed no significant differences in injury severity distributions between the control tractor-semitrailer and the alternative configuration. However, in the Scenario 3 analyses, both the Idaho and Michigan data indicated that the six-axle alternative configuration was generally involved in less severe crashes compared to the five-axle control configuration.

These crash-based findings for the five- and six-axle trucks differed from the findings for the vehicle stability and control modeling analysis and the safety inspection and violations analyses. The vehicle stability and control analyses showed marginal differences between the control tractor-semitrailer and the Scenario 2 and 3 alternative truck configurations for the maneuvers evaluated. The violations analyses did not indicate a clear pattern of association between control and alternative truck configurations in violations or out-of-service decisions and citations.

Comparative Analysis of Triple Trailer and Twin-trailer Configurations

In general, the Scenario 5 and 6 findings involving triple-trailer alternative configurations also differed to some extent between the three analyses. While no differences in crash rates between triple-trailer and twin-trailer configurations was seen in the Scenario 6 Kansas Turnpike data, the crash rate analyses for Idaho (Scenario 5) indicated the rates for the triple-trailer configuration to be significantly lower than those for the twin-trailer configuration.

With respect to crash severity, no difference was found between twin-trailer and triple-trailer configurations in the Scenario 6 Kansas Turnpike data. However, the Scenario 5 Idaho triple-trailer configuration involvements appear to be somewhat less severe than those of the twin-trailer configuration on rural Interstates (p=0.09). No differences are seen on urban Interstates or when urban and rural are combined. Fleet analyses indicate a higher likelihood of severe outcomes for the triple-trailer configurations compared to those of the double-trailer, but only when considering outcomes for non-truck occupants.

The crash-based findings of differences in both crash rate and crash severity in Scenario 5 differed from the vehicle stability and control and the violations findings. The vehicle stability and control analysis of the triple combinations showed minor differences between the twin-trailer control vehicle and the alternative truck configurations for the set of maneuvers evaluated. The greatest difference was in the low-speed off-tracking maneuver. The safety inspections and violations analysis did not produce any findings for twin trailer compared with triple-trailer configurations due to the small sample sizes. In both the control and alternative configuration analyses, the differences between the findings for crash rate and crash severity versus the findings for vehicle control and simulations could result from the fact that, while crash rates reflect actual operations with various drivers in a variety of traffic, roadway and environmental conditions, the simulation-based analyses addresses specific controlled conditions that lack real-world operators or operating conditions.

Data Improvement in Crash-Based and Inspection-Based Studies

A major conclusion of this overall effort is that crash-based studies of truck size and weight in the United States are very difficult to conduct successfully. This is particularly true if the studies are based on the primary data sources used in this study – State crash files, State roadway inventory data, State AADT data, and additional data on VMT for specific truck configurations. The issues found in the data used in this study are not new, and many of them have been documented before.

It is very likely that national-level questions concerning the safety effects of changes in truck size and weight will continue to be asked in the future. However, given the current data limitations, the same problems encountered in this study and in past studies will be encountered again. While existing roadway inventory and AADT data will likely be sufficient for use in future studies, major improvements are needed in the availability of crash data and VMT data for specific truck configurations.

Crash Data Needs

It is imperative that a data set be carefully assembled over time that includes precise information about the configurations and weights of the vehicles involved in crashes. While it may not be possible to have the investigating police officer report the actual GVW on crash report forms (since the truck operator does not possess that information), at a minimum, it should be possible for the investigating officer to accurately report a count of trailers, a count of total axles, and the length of each trailer for combination vehicles involved in crashes. However, only 7 of the 17 States allowing the operation of a triple-trailer configuration under the ISTEA LCV Freeze had an axle count variable, and 1 of them stopped collecting these data in 2010. Only 9 of the 15 States originally examined for heavy semitrailer operation had an axle count variable. Almost no States capture information on trailer length—again, a variable easily measured at the crash site.

Configuration-specific VMT Needs

The single current source of State and national truck VMT information for the configurations of interest in this study (plus additional configuration) is the WIM data described earlier. WIM data were used in this study to derive VMT estimates for 28 detailed vehicle classes. FHWA’s vehicle classification data includes 13 different vehicle types and combines both twin trailer and triple-trailer configurations with other truck types, so the routine counts had to be supplemented with WIM data to provide the needed classifications that include a gross vehicle weight attribute. Unfortunately, the number of WIM data collection points is limited enough that the needed VMT estimates could only be provided at the State functional class level. Even the VMT estimates for rural and urban Interstates for individual States were often based on a very limited number of WIM stations within each roadway classifications. In addition, they could not be used to estimate VMT for a specific configuration (e.g., heavy triple-trailer configurations) on a given route. The ability to extrapolate WIM estimates to specific routes would be very important in future attempts to model target truck crashes on non-Interstate roads or to better model truck crashes on Interstate routes such that the effect of AADT changes on truck crashes per mile driven can be more accurate defined.

Inspection-based Data Needs

The MCMIS inspection data used to support the inspection and violations analysis included the selection of the gross vehicle weight variable, “Gross Combination Vehicle Weight” (i.e. GROSS_COMB_VEH_WT), which is defined in the MCMIS data dictionary as the measured weight of the combination vehicle in the field. After the analysis was nearly complete, discussions with FMCSA indicated that this variable is not always available in the file as a measured weight. Subsequent discussions with FMCSA staff revealed that no better variable existed in MCMIS for a description of combination vehicle weight, so the team elected to proceed with the analysis. Consistent recording of accurate combination vehicle weight is necessary to support future studies.


In summary, without data improvements, future studies will continue to experience difficulties in quantifying the safety implications of alternative truck sizes and weights.

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