| 常态化疫情防控阶段旅客中长距离城际出行联合选择行为建模 |
| |
| 引用本文： | 方瑞韬,邵海鹏,林涛.常态化疫情防控阶段旅客中长距离城际出行联合选择行为建模[J].交通信息与安全,2023,41(1):151-160. |
| |
| 作者姓名： | 方瑞韬 邵海鹏 林涛 |
| |
| 作者单位： | 长安大学运输工程学院 西安 710064 |
| |
| 基金项目： | 国家重点研发计划项目2019YFB1600302 |
| |
| 摘 要： | 新冠肺炎疫情对旅客中长距离的城际交通出行影响巨大，现有研究侧重疫情暴发初期疫情对城际交通出行的影响，针对常态化疫情防控阶段旅客城际出行选择行为的研究相对较少，因此，本文旨在研究常态化疫情防控阶段旅客中长距离城际出行选择行为。针对民航、高铁、普铁和自驾等方式分别建立包含4种城际出行方式的多指标多因果出行选择模型（MIMIC），模型中引入感知防疫安全程度、防疫策略、乘车体验与出行习惯4个潜变量，探究潜变量与观测变量的因子载荷并辨识模型参数，求取各潜变量的拟合值；在此基础上建立考虑出行方式特性、旅客社会经济属性与潜变量的多出行方式联合选择行为模型（MIMIC-Logit），探究常态化疫情防控阶段旅客出行心理对其出行决策的影响；假设出行费用、时间与距离等变量的随机系数服从正态分布，采用抽样1000次的Halton序列对随机系数进行仿真求解，得到随机系数的回归分析结果。以2021年4月—6月到达西安旅客的调查数据为例进行实证研究，结果发现:所提MIMIC-Logit模型的拟合优度与命中率分别为43.621%与83.312%，均高于多项Logit模型与随机系数Logit模型；旅客对不同方式的出行费用、时间与距离的偏好具有异质性，且出行方式特性、社会经济属性与潜变量都对出行选择的效用有显著影响。弹性分析表明，当感知防疫安全程度与防疫策略提升了100%时，旅客选择民航出行的概率分别提升了23.207%与21.349%；而当乘车体验提升了100%时，旅客选择高铁出行的概率提升了18.229%。综上，所提方法揭示了潜变量对旅客出行选择行为的显著影响；通过提升感知防疫安全程度、防疫策略与乘车体验等手段，可以提升旅客选择高铁、民航出行的概率。
|
| 关 键 词： | 交通工程 城际出行选择 MIMIC-Logit模型 潜变量 新冠疫情 |
| 收稿时间： | 2022-07-01 |
A Joint Mode Choice Behavior Model of Long-distance Intercity Passenger Travel during the Periods with Regular Epidemic Prevention and Control Measures |
| |
| Affiliation: | College of Transportation Engineering, Chang'an University, Xi'an 710064, China |
| |
| Abstract: | The impact of COVID-19 on long-distance intercity travel is enormous. Existing studies have investigated the impact of COVID-19 on intercity travel at the early stage of the epidemic outbreak, while few of them have studied its impact during the periods with regular prevention and control measures. To fill the gap, this paper focuses on the mode choice behavior of long-distance intercity travel under the impact of regular prevention and control measures of the COVID-19 epidemic. First, a set of multiple indicators and multiple causes (MIMIC) models are developed for civil aviation, high-speed rail, train, and passenger car, independently, and each covers the four modes. The perceived level of safety of prevention measures, epidemic prevention strategies, riding experience, and travel habits are considered in the MIMIC choice behavior model, which are used to explore the relationship between observed and latent variables, to identify the parameters of the model, and to estimate each latent variable. Secondly, to investigate the impact of passengers' psychology on their travel mode choices, a MIMIC-Logit model considering the characteristics of travel modes, socio-economic attributes of passengers, and latent variables is developed. Then, assuming that the random coefficients of passengers' travel expenses, travel time, and travel distance follow a normal distribution, the Halton sequence drawn from the original data through 1000 samplings is used to estimate the utility coefficients of the MIMIC-Logit model. Lastly, the survey data of passengers arriving in Xi'an between April and June 2021 is employed to validate the proposed model. Study results show that (1) the goodness of fit and hit ratio of the MIMIC-Logit model with latent variables is 43.621% and 83.312%, respectively, which are higher than the comparative multinomial-Logit model and the random coefficient Logit model; (2) the preferences of passengers towards different travel modes of travel expenses, travel time, and travel distance are heterogeneous, and the characteristics of travel modes, socio-economic attributes, and latent variables all have a significant impact on mode choices; (3) when the variables representing perceived level of safety of the COVID-19 prevention measures and epidemic prevention strategies is increased by 100%, the probability of choosing civil aviation is increased by 23.207% and 21.349%, respectively; (4) when the variable representing travel experience is increased by 100%, the probability of passengers choosing high-speed rail is increased by 18.229%. In general, the proposed method reveals that the latent variables representing passenger's psychology has a significant impact on mode choice behavior, and the probability of choosing high-speed rail and civil aviation can be increased by improving the perceived level of safety of prevention measures, epidemic prevention strategies, and riding experience. |
| |
| Keywords: | |
|
| 点击此处可从《交通信息与安全》浏览原始摘要信息 |
|
点击此处可从《交通信息与安全》下载全文 |
|
