The ordered probit model is used to examine the contribution of several factors to the injury severity faced by motor-vehicle occupants involved in road accidents. The estimated results suggest that motor-vehicle occupants travelling in light-vehicles, at two-way roads, and on dry road surfaces tend to suffer more severe injuries than those who travel in heavy-vehicles, at one-way roads, and on wet road surfaces. Additionally, the driver's seat is clearly the safest seating position, urban areas seem to originate less serious accidents than rural areas, and women tend to be more likely to suffer serious or fatal injuries than men.
TICE.MOBILIDADE - Sistemas de Mobilidade Centrado no Utilizador
Journal
Transportation Research Procedia, Vol. 3, pp. 214-223, Francisco G. Benitez, Riccardo Rossi, October 2014
DOI
Cited by
Year 2018 : 3 citations
Dimitris Potoglou, Fabio Carlucci, Andrea Cira, Marialuisa Restaino."Factors associated with urban non-fatal road-accident severity", International Journal of Injury Control and Safety Promotion, 5:1-8, 2018.
[DOI: 10.1080/17457300.2018.1431945]
Ma, Z., Lu, X., Chien, S.I.J. and Hu, D. (2018). "Investigating factors influencing pedestrian injury severity at intersections", Traffic Injury Prevention, 19(2), pp. 159-164.
Alkhlaifi, A., Galadari, A. (2018). Identifying the risk factors affecting crash severity at intersections with considering crash characteristics and signal configuration using an ordered logistic model, Advances in Science and Engineering Technology International Conferences, ASET 2018, pp. 1-7
Year 2017 : 1 citations
Alkheder, S., Taamneh, M., Taamneh, S. (2017). Severity Prediction of Traffic Accident Using an Artificial Neural Network, Journal of Forecasting, 36(1), pp. 100-108.
