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3 CHAPTER ONE INTRODUCTION BACKGROUND Some strategies in this list are already in widespread use (Corsi and Barnard 2003; Knipling et al. 2003; Belella et al. There are two broad ways in which motor carriers can improve 2009). Others are well established by research, yet not neces- the safety of their operations. One is to improve the safety sarily appreciated by industry. Still others have clear ratio- performance of their individual "assets"--that is, drivers nales, but are not firmly based on comparative data. Some risk and vehicles. Improving the safety performance of individ- avoidance strategies require proactive, executive-level strate- ual drivers and vehicles almost inevitably involves resource gic decisions by carriers. Others are dispatch and routing deci- expenditures, such as spending more time and money on driver sions made by operational managers, dispatchers, or drivers selection, training, management oversight, or vehicle safety themselves. All involve operational efficiency measures with equipment. These are proven ways to enhance safety. potential safety benefits when implemented intelligently. Another method is to deploy the same assets in ways that This synthesis report reviews the rationales and evidence minimize risk and increase opportunities for successful per- for these risk avoidance strategies, and reports survey findings formance. This might be considered analogous to the decisions on their advisability, use, and perceived safety effects. Motor a football coach makes on game day. The potential perfor- carrier executives and managers are the principal target audi- mance capabilities of individual "assets" (players) are largely ence, though government and industry officials involved in established before the game, but the coach's lineup decisions highway operations, regulations, or outreach may find some and plays called during the game greatly affect team success. results relevant. Many study topics are more relevant to truck- These methods do not primarily involve increased resource ing operations than to buses, primarily because trucking opera- expenditures, but rather resource deployment decisions. tions permit greater flexibility. Nevertheless, the study gathered data from both truck and bus sources, and provides findings Various aspects of motor carrier safety management might relevant to both of these commercial vehicle types. be considered risk avoidance as opposed to direct risk reduc- tion through safety performance enhancement (Dewar and Overview of Crash Risk Avoidance Olson 2002; Murray et al. 2003; Knipling 2009). These include strategies such as the following: Operational risk can be seen within the context of crash risk in general. Crash risk factors may be distinguished from prox- · Emphasize scheduled, preventive maintenance on trucks, imal causes. Risk factors exist before the crash event and affect as opposed to reactive repairs; the probability of a crash (Dewar and Olson 2002; Evans · Minimize deadhead (empty trailer) trips; 2004; Shinar 2007; Knipling 2009). Much of road safety · Minimize loading, unloading, and related delays; research seeks to identify crash risk factors and reduce risk. · Optimize routing and navigation; For example, the U.S.DOT Large Truck Crash Causation · Maximize travel on divided, limited-access roadways; Study (LTCCS) was done to "identify associations between · Minimize travel on undivided roads; various factors and an increased risk of crash involvement in · Avoid work zones; either relative or absolute terms" (Blower and Campbell 2005). · Avoid peak hours and congested roads; Crash proximal causes, termed Critical Reasons (CRs) in the · Avoid adverse weather and slick roads, when possible; LTCCS, are the critical driver errors or other failures (vehicle, · Assign familiar routes to drivers; roadway) immediately preceding and triggering crash events. · Encourage driving at off-peak times, when feasible; Figure 1, adapted from Knipling (2009), shows a simple time · Optimize the mix of vehicle sizes (e.g., in some opera- line of crash risk, cause, and occurrence. Both crash risk fac- tions, use larger trucks to reduce the number of trips); tors and causes may be human, vehicle, or environmental. · Use onboard computers; Most proximal crash causes are human errors. In the LTCCS, · Use mobile communications; CR assignments were 89% driver errors, 8% vehicle failures, · Use driver teams; and 3% roadway and environmental factors (Starnes 2006). · Use electronic onboard recorders (EOBRs); · Improve fuel economy; and The risk time line in Figure 1 is extended to the left to show · Monitor vehicle condition continuously. pre-trip and pre-crash threat periods. The operational practices
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4 FIGURE 1 Risk-cause crash timeline with extended pre-crash risk segments. Adapted from Knipling (2009). discussed in this report all fall into one or both of these speeds (i.e., not traveling over the posted speed limits), fast periods. Pre-trip practices that affect risk include preventive travel appears to be dramatically safer than slow travel. This maintenance, trip scheduling, pre-trip route optimization, is demonstrated in naturalistic driving studies comparing and use of driver teams. Pre-crash threat practices include exposure (based on a random sample of normal driving) to route selection to avoid undivided highways, traffic conges- crash-relevant driving incidents (crashes, near-crashes, other tion, and work zones. The dotted lines between the risk zones traffic conflicts) captured in onboard recorders. Figure 2, denote that many risk avoidance practices operate across based on data from an FMCSA-sponsored naturalistic driving the zones. The next chapter will extend this conception into study (Hickman et al. 2005), compares the vehicle speed pro- a two-dimensional framework for commercial motor vehicle file of a random sample of driving (representing exposure) to (CMV) risk avoidance strategies based on the Haddon Matrix vehicle speeds when incidents occurred. The first bar is the of road safety (Haddon 1980) and subsequent elaborations profile for exposure, the second the profile for incidents. For by CMV safety researchers (Faulks and Irwin 2002; Murray simplicity, just two travel conditions are shown: 50 mph and et al. 2003, 2009). 51+ mph. Comparing the two bars, we see that slow travel is far riskier than fast travel, at least in regard to the kind of close Efficiency and Safety Example: The Speed Paradox traffic interactions captured in naturalistic driving. Trucks in the study were traveling at 50 mph or less only 16% of the Are trucks safer when traveling fast or slowly? The answer time, but 63% of the incidents occurred at these slow speeds. provides a prologue to several of the operational efficiencies The risk odds ratio is a statistical measure of the relative risk discussed in this report. On one hand, driving too fast for of two situations. In these data, slow travel was 8.9 times existing conditions is the leading proximal cause of large- riskier than fast travel. The risk odds ratio was derived as truck crashes. In the LTCCS, "too fast for traffic or road con- follows: (63%/16%)/(37%/84%) = 3.94/0.44 = 8.9. ditions" was the "Critical Reason" for 21% of truck at-fault crashes, versus 17% for inattention or distraction, 12% for This counterintuitive finding may be termed the speed inadequate surveillance ("looked but did not see"), 10% for paradox (Knipling 2009). Though excessive speed is a major all vehicle causes combined, and 7% for asleep-at-the-wheel cause of serious crashes, most safety incidents occur when (Starnes 2006). commercial vehicles are traveling relatively slowly. To under- stand this, consider the situations in which commercial vehi- On the other hand, when one considers the entire fleet of cles must drive slower than regular highway speeds. Slow vehicles operating at any time and the normal ranges of truck travel is associated with heavier traffic, undivided roads, closer 16% 63% 84% 50 mph 51+ mph 37% Exposure Incidents FIGURE 2 Relative risk by vehicle speed.