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Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
Although farm vehicle public road crashes are relatively infrequent events, they are more likely to result in injury and fatality than non-farm vehicle crashes. Farmers are concerned about their safety when driving farm vehicles on public roads, yet research attention to the issue is lacking. Drawing on transportation crash prevention models, this study posited that a combination of driver, vehicle, farm and public road environmental characteristics are associated with farm vehicle public road crash group membership. A case-control study compared farms reporting a farm vehicle public road crash (1992-2003) with farms that had not experienced one. A total of 14,800 phone numbers were called. The calling list was randomly selected and ordered from a USDA agricultural program database (n = 46,910) of North Carolina resident farm operators and owner/operators. Approximately 76 percent of numbers called allowed successful screening. Approximately 26 percent of calls screened met inclusion eligibility. Response to a 20-minute telephone survey was 100 percent among eligible farm operators and owner/operators actively farming, 18 years or older, and driving farm vehicles on public roads. A sample of n = 200 crash cases and n = 185 no-crash controls were available for data analysis for an approximate 1:1 case : control ratio. The combined logistic regression model of eighteen driver, vehicle and environmental characteristics was significant for crash group membership differences (X2 = 192, df = 18, p
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
Although farm vehicle public road crashes are relatively infrequent events, they are more likely to result in injury and fatality than non-farm vehicle crashes. Farmers are concerned about their safety when driving farm vehicles on public roads, yet research attention to the issue is lacking. Drawing on transportation crash prevention models, this study posited that a combination of driver, vehicle, farm and public road environmental characteristics are associated with farm vehicle public road crash group membership. A case-control study compared farms reporting a farm vehicle public road crash (1992-2003) with farms that had not experienced one. A total of 14,800 phone numbers were called. The calling list was randomly selected and ordered from a USDA agricultural program database (n = 46,910) of North Carolina resident farm operators and owner/operators. Approximately 76 percent of numbers called allowed successful screening. Approximately 26 percent of calls screened met inclusion eligibility. Response to a 20-minute telephone survey was 100 percent among eligible farm operators and owner/operators actively farming, 18 years or older, and driving farm vehicles on public roads. A sample of n = 200 crash cases and n = 185 no-crash controls were available for data analysis for an approximate 1:1 case : control ratio. The combined logistic regression model of eighteen driver, vehicle and environmental characteristics was significant for crash group membership differences (X2 = 192, df = 18, p
Author: Mitchell Joseph Greenan Publisher: ISBN: Category : Farm equipment Languages : en Pages : 54
Book Description
Tractors and other self-propelled farm equipment, such as combines, sprayers, and towed grain carts, are often used on public roadways as the primary means for traveling from homestead to homestead or from homestead to a distributer. Increased roadway exposure has led to a growing concern for crashes involving farm equipment on the public roadway. A handful of studies exist examining public roadway crashes involving farm equipment using crash data, but none thus far have evaluated road segment data to identify road-specific risk factors. The objective of this study is to identify if roadway characteristics (traffic density, speed limit, road type, surface type, road width, and shoulder width) affect the risk of a crash involving farm equipment on Iowa public roadways. A retrospective cohort study of Iowa roads was conducted to identify the types of roads that are at an increased risk of having a farm-equipment crash on them. Crash data from the Iowa Department of Transportation (to identify crashes) were spatial linked to Iowa roadway data using Geographic Information Systems (GIS). Logistic regression was used to calculate ORs and 95% CL. Out of 319,705 road segments in Iowa, 0.4% segments (n=1,337) had a farm equipment crash from 2005-2011. The odds of having a farm equipment crash were significantly higher for road segments with increased traffic density and speed limit. Roads with an average daily traffic volume of at least 1,251 vehicles were at a 5.53 times greater odds of having a crash than roads with a daily traffic volume between 0-30 vehicles. (CI: 3.90-7.83). Roads with a posted speed limit between 50mph and 60mph were at a 4.88 times greater odds of having a crash than roads with a posted speed limit of 30mph or less. (CI: 3.85-6.20). Specific roadway characteristics such as roadway and shoulder width were also associated with the risk of a crash. For every 5 foot increase in road width, the odds for a crash decreased by 6 percent (CI: 0.89-0.99) and for every 5 foot increase in shoulder width, the odds of a crash decreased by 8 percent. (CI: 0.86-0.98). Although not statically significant, unpaved roads increased the odds of a crash by 17 percent. (CI: 0.91-1.50) Lastly, it was found that Farm to Market routes increased the odds of a crash by two fold compared to local roads (which make up roughly 67 percent of Iowa public roads). (CI: 1.72-2.43) When the same model was stratified by rurality (urban/rural), it was found that high traffic density leads to a higher risk of a crash in rural areas. Iowa routes and Farm to Market routes had a greater odds of a crash in urban than rural areas, and road and shoulder width were more protective in rural than urban areas. When only using roads with a crash involving an injury versus all other roads as the outcome, Iowa routes and roads with increased speed limits had higher odds for an injury-involved crash, while increased road width were more protective against crashes involving injuries. Findings from the study suggest that several roadway characteristics were associated with farm-equipment crashes. Through administrative and engineering controls, the six static explanatory variables used in this study may be modified to decrease the risk of a farm equipment crash. Speed limit can be modified through administrative controls while traffic density, road and shoulder width, road type, and surface type can be modified through engineering controls. Results from this study provide information that will aid policy-makers in developing safer roads for farm equipment.
Author: U S Government Accountability Office (G Publisher: BiblioGov ISBN: 9781289039288 Category : Languages : en Pages : 56
Book Description
Pursuant to a congressional request, GAO examined the factors that contribute to vehicular crashes, focusing on: (1) drivers' age, gender, and driving history; and (2) vehicle size and age. GAO found that: (1) driver characteristics far outweigh vehicle factors in predicting vehicular crashes; (2) drivers who are younger, male, and have a history of traffic violations, particularly alcohol violations, are more likely to be involved in single-vehicle crashes; (3) drivers 65 and older are the second most likely group to be involved in crashes; (4) older vehicles are slightly more at risk for crash involvement, but other factors that are linked to vehicle age may also play a part in older cars' involvement in crashes; (5) light cars are three times more likely to be involved in single-vehicle rollover crashes than heavy cars; (6) a car's wheel-base or engine size is a better predictor of crash involvement; and (7) light trucks and vans show a similar crash-involvement pattern except that driver gender is generally not a significant factor in predicting light truck and van crashes.
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Author: Theresa Mary Costello
Author: Mitchell Joseph Greenan
Author: Indiana University. Institute for Research in Public Safety
Author: U S Government Accountability Office (G
Author: N. Pronk
Author: David Klein
Author: Grand Rapids (Mich.). Dept. of Public Safety
Author: United States. National Highway Traffic Safety Administration
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