混合Logit模型的参数估计与应用研究

混合Logit模型具有较高的灵活性，其效用变量的系数可以服从正态分布、对数正态分布、SB分布等多种形式. 本文以北京市居民出行调查数据为基础，建立交通方式选择的混合Logit模型，允许系数取不同分布类型的组合，采用极大模拟似然法完成参数估计. 在模拟中使用拟随机数序列计算模拟概率，首先使用变序Halton序列给出几种高精度的结果，进一步采用MLHS（Modified Latin Hypercube Sampling）方法对其中最好的假设模拟求解，为效用变量的系数确定了合适的随机分布函数. 参数的估计值清晰地解释了影响人们出行的各种因素.

Parameter Estimation of the Mixed Logit Model and Its Application

The mixed Logit model is flexible for application becous the coefficients associated with the attributes of the utility variables could be distributed in normal, lognormal, SB, and other types. On the basis of Beijing’s resident daily travel survey, a mixed Logit model is presented and calibrated in this paper. The method of maximum simulated likelihood, in which quasi-random number sequences of shuffled Halton and the MLHS (Modified Latin Hypercube Sampling) are used for simulation, is developed to estimate the coefficients, and hence to determine suitable distributions for them. The estimated values give clear explanations to the factors influencing the resident’s mode choice behavior.