TRUE Lab analyzes various traffic accident data, and we have utilized 5 year Seoul traffic accident data in order to find out the vulnerability of senior occupants in various seat positions and restraint use with multinomial logit model. The general approach to multinomial data is to nominate one of the response categories as a baseline, calculate odds ratio for all other categories relative to the baseline. In this analysis, we picked the non-severe injury as a baseline, and calculated odds ratio for severe injury for each explored variable. This case, the multinomial logit model converges to a binary logit model since binary response (severe and non-severe) was used. We examined how much the senior occupants are at risk regarding various vehicle seat positions and use of seatbelts. The graph below shows that seniors are more likely to have severe injury than mid-age group in all seat positions, especially in the front passenger seat and the rear seat. When seatbelt is off, the ORs increased, but it decreased sharply with a large magnitude when seatbelt is on.