摘要
轨道交通统计生命价值是轨道交通安全项目成本效益分析中不可或缺的基础指标.利用参数服从对数正态分布的混合logit模型,构建轨道交通统计生命价值的评价模型;利用意愿选择法和正交试验法设计"出行路径选择"调查问卷,并在大连地区实施交通意向调查获得调查数据;利用贝叶斯估计中的马尔科夫链蒙特卡洛方法对模型进行参数估计,最终获得轨道交通统计生命价值的评估值.研究结果表明:通过对马尔科夫链的收敛性诊断,表明参数服从对数正态分布的ML模型具有较高的精确性;基于贝叶斯估计的轨道交通统计生命价值评估值为508.41万元,评估结果具有合理性.
The value of a statistical life(VOSL)in rail traffic is an indispensably basic indicator for the cost-benefit analysis on rail traffic safety projects.The evaluation model on VOSL in rail traffic was constructed based on the mixed logit(ML)model with the parameters obeying to lognormal distribution.A route-choice questionnaire was designed by stated choice method and orthogonal experiment method,and the traffic survey was carried out in Dalian with survey data obtained.Markov Chain Monte Carlo in Bayesian algorithm was used to calibrate model parameters.Finally,the estimation of VOSL in rail traffic was obtained.The research results indicate that by the convergence diagnosis of Markov chain,the ML models with the parameters obeying to lognormal distribution have a high accuracy.The estimate result of VOSL in rail traffic is 5084100 RMB,which is reasonable.
作者
刘文歌
杨晶
LIU Wenge;YANG Jing(School of Economics and Management,Dalian Jiaotong University,Dalian 116028,China)
出处
《大连交通大学学报》
CAS
2020年第6期23-27,共5页
Journal of Dalian Jiaotong University
基金
国家自然科学基金资助项目(51608088)
教育部人文社会科学青年基金资助项目(16YJC630075)
辽宁省社会科学规划基金资助项目(L15BGL003)
辽宁省博士科研启动基金资助项目(201601261)。
