| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 572867 | Accident Analysis & Prevention | 2011 | 8 Pages |
The Alabama State Department of Education and the Governor's Study Group on School Bus Seat Belts authorized and funded a research project to investigate the effects of lap-shoulder seat belts on Alabama school buses. This article performs an empirical analysis to address an important component of the study – factors that impact students’ decisions about wearing seat belts or not on school buses. Discrete choice modeling framework is applied to quantify relative influences of various factors. To obtain the disaggregate level information on individual student's characteristics and trip properties, a new data collection protocol is developed. Eleven variables are investigated and eight of them are found to have significant impacts. They are age, gender, the home county of a student, a student's trip length, time of day, presence and active involvement of bus aide, and two levels of bus driver involvement. The resulting model fits the data well and reveals several trends that have been overlooked or underestimated in the literature. The model can also be used to predict the change of seat belt usage rate caused by the change of impact factors. This is helpful in identifying the most cost-effective ways to improve compliance rate, which is critical to bring the added safety benefit of seat belts into effect. This article is the first to quantify relative impacts of a range of variables using rigorous statistical modeling techniques. This study will contribute to the literature and provide valuable insights to the practice of school transportation management.
► Statistical model reveals factors impacting students’ usage of school bus seat belts. ► This is the first study to quantify relative importance of various factors. ► New data collection protocol is developed to obtain disaggregate level information. ► Eight variables of student characteristics and trip properties are significant. ► New trends identified about age and other variables differ from common perceptions.
