Comparative Study on Value of a Statistical Life in Road Traffic Based on Mixed Logit Model

In order to further improve the accuracy of evaluation models on value of a statistical life (VOSL) in road traffic, four mixed logit (ML) models of route-choice with truncated normal distribution and lognormal distribution were used to construct VOSL models. A route-choice questionnaire was designed by the stated choice method, and the traffic survey was carried out in Dalian with survey data obtained. Monte Carlo simulation algorithm was used to calibrate parameters by 150 simulations, and the 4 ML models were analyzed comparatively. Finally, the VOSL estimate of private drivers in Dalian and its distribution function were obtained. The research results indicate: ML model with truncated normal distribution has \(\overline{\rho}^{2}\) of 0.1516 and hit ratio of 70.42%, which has a lower accuracy. 3 ML models with lognormal distribution have a high accuracy, whose \(\overline{\rho}^{2}\) are all between (0.2–0.4) and hit ratios all above 80%. The 4th ML model whose parameters of fatal risk and travel cost obeying lognormal distribution simultaneously has the highest accuracy, with the greatest \(\overline{\rho}^{2}\) (0.2534) and the highest hit ratio (84.76%). VOSL in road traffic based on the 4th ML model obeys lognormal distribution with parameters (2.0622, 0.6740²) with the mathematical expectation of 986,840 RMB. The maximum probability is 9.45% when VOSL is 500,000 RMB.