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C H A P T E R 8 Conclusions and Recommendations for Future Data Collection Efforts The team reviewed reduced data from each candidate data set As revealed by the data, the factors that contributed to a in Chapter 4. The original reduced data were not detailed or crash usually were not caused by a sole factor but involved some specific enough to recognize contributing factors to safety- form of factor interaction. For example, the driver could be related events. Consequently, additional data reduction was distracted by both talking on a cell phone and adjusting the needed. The next section details the factors that contribute radio during an event, or the crash could have been caused by to crashes and near crashes, whether or not driver behavior both inattention of the driver and a poorly designed roadway. can be adjusted, and corresponding countermeasures are Therefore, as shown in Tables 8.2 and 8.3, the resulting sum recommended. of percentages of contributing factors may add up to more than 100%. Not all 18 conflict categories are listed in these tables. Most of the categories of events have driver factors Contributing Factors and involved as a contributing factor, especially for the single- Correctable Driver Behaviors and lead-vehicle crashes, as well as for the single-, lead-, and For Project 5, RDCWS FOT, the original data reduction did following-vehicle near crashes. These categories have more not specifically pinpoint contributing factors to events. The than 100% driver factorinvolved cases, demonstrating a high variables coded for drivers and the related environment stated probability of human errors. the situation only at the instant the events occurred. The team In some cases the contributing factors are descriptions performed additional data reduction and identified contribut- of the status of the driver, vehicle, and environment at the ing factors. As seen in Table 8.1, in most of the safety-related moment the event happened. For example, if the driver was events, driver-related decision errors are the contributing using a wireless device when the event happened, the driver factor. For both freeway and arterial safety-related events, more factor would be "Secondary task" under the "Inattention to than 80% of the cases are caused by factors in this category. Forward Roadway" category. It is possible that these factors The next largest category on both types of roads is recognition are not the direct causal factor leading to the events. To better errors in which drivers were distracted or failed to look. distinguish preventable events from others, additional data For Project 6, the 100-Car Study, the factors that precipitated reduction was performed by the team. Table 8.4 ascribes the a safety-related event, contributed to the event, and were crashes and near crashes to one mutually exclusive contribut- associated with the event were determined. These factors are ing category that can be considered as a dominant factor. The grouped into pre-event maneuvers, precipitating factors, con- categories listed in this table better serve the purpose of studying tributing factors, associated factors, and avoidance maneuvers. the relationship between behavior and travel time reliability. Of all the factors, contributing factors are the key in the study of In summary, the data collected in the 100-Car Study were driver behavior and were judged by trained data reductionists comprehensively and accurately reduced. The continuous to have directly influenced the presence or severity of a crash video and other data are suitable for studying driving behavior or near crash. Three subcategories were further constructed and its impact on travel time reliability. for contributing factors to identify the causes of crashes: For Project 7, DDWS FOT, more than one vehicle was infrastructure factors and driving environment factors, such involved in multiple crashes. Because only the subject vehicle as road surface, traffic density, and weather; driver factors, was equipped with data collection equipment, data reduc- such as driver inattention, drowsiness, and distraction; and tionists could observe only scenarios related to that vehicle. vehicle factors, such as flat tires and vehicle breakdowns. Contributing factors were analyzed based on the observations 64

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65 Table 8.1. Critical Contributing Factors for Project 5 Critical Factor Freeway Arterial Total Driver-related factor (critical nonperformance errors), including sleep; heart attack or other 0 (0.0%) 0 (0.0%) 0 (0.0%) physical impairment of the ability to act; drowsiness, fatigue, or other reduced alertness; other critical nonperformance Driver-related factor (recognition errors), including inattention; internal distraction; external 5 (6.5%) 0 (0.0%) 5 (5.0%) distraction; inadequate surveillance (e.g., failure to look); other or unknown recognition error Driver-related factor (decision errors), including too fast or too slow; misjudgment of gap; 66 (85.7%) 19 (82.6%) 85 (85.0%) following too closely or unable to respond to unexpected actions; false assumption of other road user's actions; apparently intentional sign or signal violation; illegal U-turn or other illegal maneuver; failure to turn on headlamps; inadequate evasive action; aggressive driving; other or unknown decision error Driver-related factor (performance errors), including panic or freezing; overcompensation; 0 (0.0%) 0 (0.0%) 0 (0.0%) poor directional control; other or unknown performance error Environment-related factor, including sign missing; view obstruction by roadway design; 0 (0.0%) 0 (0.0%) 0 (0.0%) roadway geometry; sight distance; maintenance problems; slick roads; other highway-related conditions Environment-related factor, including glare, blowing debris, animal or object in roadway 0 (0.0%) 0 (0.0%) 0 (0.0%) Crashes or near crashes caused by others 1 (1.3%) 1 (4.3%) 2 (2.0%) Unknown reasons 5 (6.5%) 3 (13.0%) 8 (8/0%) Total 77 (100%) 23 (100%) 100 (100%) from equipped vehicles. The most frequent critical reason for was conducted more recently than Project 6; consequently, crashes was "object in roadway," which constituted 57% of the the instrumentation used to collect the data was more accurate. total events. The next largest groups were driver-related factors Because only commercial trucks were studied, the data set (recognition errors) and driver-related factors (performance has certain limitations with regard to the versatility of drivers errors); each group had more than 14% of the cases. For tire and vehicles. strike cases, most were attributed to environment-related For Project 8, NTDS, a total of 320,011 triggers were visu- factors. For near crashes, driver-related factors (recognition ally inspected during data reduction. From those triggers, errors and decision errors) constituted nearly half of all cases. 2,899 safety-critical events were identified, including 13 crashes Details of the critical factors are enumerated in Table 8.5. (eight of those were tire strikes), 61 near crashes, 1,594 crash- In summary, the data collected in this study were com- relevant conflicts, 1,215 unintentional lane deviations, and prehensive, and the data reduction was extensive. This study 16 illegal maneuvers. Additionally, a random sample of Table 8.2. Contributing Factors for Crashes in Project 6 Factor Category Crashes Total Number Driver Environmental Vehicle Single vehicle 24 121% 38% 0% Lead vehicle 15 127% 13% 0% Following vehicle 12 83% 8% 0% Object obstacle 9 144% 56% 0% Parked vehicle 4 100% 50% 0% Animal 2 0% 100% 0% Turning across opposite direction 2 100% 50% 0% Adjacent vehicle 1 100% 0% 0%

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66 Table 8.3. Contributing Factors for Near Crashes in Project 6 Factor Category Near Crashes Total Number Driver Environmental Vehicle Single vehicle 48 135% 29% 0% Lead vehicle 380 119% 9% 0% Following vehicle 70 110% 9% 0% Object obstacle 6 83% 50% 0% Parked vehicle 5 60% 0% 0% Animal 10 70% 10% 0% Turning across opposite direction 27 96% 30% 0% Adjacent vehicle 115 90% 11% 0% Merging vehicle 6 33% 67% 0% Across path through intersection 27 89% 30% 0% Oncoming 27 96% 30% 0% Other 2 100% 50% 0% Pedestrian 6 133% 50% 0% Turning across in same direction 3 44% 11% 0% Turning in same direction 28 54% 21% 0% Unknown 1 200% 0% 0% Table 8.4. Critical Factors Contributing to Crashes and Near Crashes Critical Factor Crashes Near Crashes Driver-related factor (critical nonperformance errors), including sleep; heart attack or other physical impairment of the ability to act; drowsiness, fatigue, or other reduced alertness; other critical nonperformance 8 (11.6%) 33 (4.3%) Driver-related factor (recognition errors), including inattention; internal distraction; external distraction; inadequate surveillance (e.g., failure to look); other or unknown recognition error 22 (31.9%) 201 (26.4%) Driver-related factor (decision errors), including too fast or too slow; misjudgment of gap; following too closely or unable to respond to unexpected actions; false assumption of other road user's actions; apparently intentional sign or signal violation; illegal U-turn or other illegal maneuver; failure to turn on headlamps; inadequate evasive action; aggressive driving; other or unknown decision error 19 (27.5%) 218 (28.6%) Driver-related factor (performance errors), including panic or freezing; overcompensation; poor directional control; other or unknown performance error 1 (1.4%) 30 (3.9%) Environment-related factor, including sign missing; view obstruction by roadway design; roadway geometry; sight distance; maintenance problems; slick roads; other highway-related conditions 2 (2.9%) 26 (3.4%) Environment-related factor, including glare, blowing debris, animal or object in roadway 4 (5.8%) 29 (3.8%) Crashes or near crashes caused by others 13 (18.8%) 224 (29.4%) Total 69 (100%) 761 (100%)