TY  - JOUR
PY  - 2024//
TI  - Crash contributing factors and patterns associated with fatal truck-involved crashes in Bangladesh: findings from the text mining approach
JO  - Transportation research record
A1  - Hossain, Ahmed
A1  - Sun, Xiaoduan
A1  - Alam, Shah
A1  - Das, Subasish
A1  - Sheykhfard, Abbas
SP  - 706
EP  - 725
VL  - 2678
IS  - 7
N2  - Despite extensive research on traffic injury severities, relatively little is known about the factors contributing to truck-involved crashes in developing countries, especially in the context of Bangladesh. Because of the unavailability of authentic crash data sources, this study collected data from alternative sources such as online English news media reports. The current study prepared a database of 144 truck-involved fatal crash reports during the period of 12 months (January 2021 to December 2021). The crash reports contain a bag of 15,300 words. Several state-of-the-art text mining tools were utilized to identify crash patterns, including word cloud analysis, word frequency analysis, word co-occurrence network analysis, rapid automatic keyword extraction, and topic modeling. The analysis revealed several important crash contributing factors, such as the type of vehicle involved (auto-rickshaw, bus, van, motorcycle), the manner of collision (head-on), the time of the day (morning, night), driver behavior (speeding, overtaking, wrong-way driving), and environmental factors (dense fog). In addition, "coming from opposite direction" and "head-on collision" are two important sequences of events in truck-involved crashes. Truck drivers are also involved in crashes with trains at rail crossings. The findings of this research can assist policymakers in identifying crash avoidance strategies to lower truck-related crashes in Bangladesh.<p />  <p>Language: en</p>
LA  - en
SN  - 0361-1981
UR  - http://dx.doi.org/10.1177/03611981231209031
ID  - ref1
ER  -