Modeling Injury Severity of Unconventional Vehicle Occupants: A Hybrid of Latent Segment and Random Parameters Logit Model

Unconventional vehicles such as human-pulled and engine-operated three-wheeler vehicles are popular travel modes in developing countries. These slower moving vehicles have limited safety features, posing significant injury risks to their occupants. This study investigates injury severity of unconventional vehicle occupants (UVOs). A hybrid latent segmentation-based random parameters logit (LSRPL) model is developed utilizing 5-year police reported collision records from Dhaka, Bangladesh. LSRPL model captures multi-dimensional heterogeneity by allocating victims into discrete latent segments (i.e. inter-segment heterogeneity) and allowing a continuous distribution of parameters within the segments (i.e. inter-segment heterogeneity). The model is estimated for two segments using victim and crash attributes: segment one is a lower-risk segment, and segment two is a higher-risk segment. The model results suggest that victim and driver profile, crash attributes, environmental factors, road network attributes, and transportation infrastructure and land use attributes influence injury severity of UVOs. For example, human-pulled three-wheeler vehicle and engine-operated three-wheeler paratransit passengers, head-on and right-angle collisions, and crashes at 3-way and 4-way intersections have a higher likelihood to result in severe injury. The model confirms the existence of significant inter-segment heterogeneity. For example, mid-block crashes are more likely to result in severe injury in higher-risk segment, and show a lower likelihood for severe injury in lower-risk segment. The model further confirms intra-segment heterogeneity for higher mixed land use. For example, in the case of mid-block crashes, higher mixed land use shows significantly lower mean for high-risk segment, revealing a lower likelihood of severe injury in higher mixed land use areas.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: References; Tables;
  • Pagination: 16p

Subject/Index Terms

Filing Info

  • Accession Number: 01764443
  • Record Type: Publication
  • Report/Paper Numbers: TRBAM-21-03310
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 23 2020 11:25AM