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共享自动驾驶汽车是智慧交通和绿色交通的重要发展方向之一,但目前其相关研究仍不充分,影响用户使用共享自动驾驶汽车意愿的因素及其作用机理有待深入剖析。为此,本文首先通过引入感知风险、服务质量和社会影响三个潜变量,构建了扩展技术接受度模型。然后将扩展技术接受度模型的潜变量、个人社会经济属性变量和出行方式属性变量整合到多项Logit模型,构建混合选择模型,并以用户选择共享自动驾驶汽车出行的概率衡量用户使用共享自动驾驶汽车的意愿。最后基于SP调查数据标定模型参数,得到潜变量关系及关键影响因素,通过弹性分析研究关键因素对用户使用意愿的影响。结果表明,感知有用性、出行费用、感知易用性、等待时间的影响最为显著,对应的弹性值分别是0.0502、-0.0401、0.0385和-0.0350。本研究对相关企业及相关政府部门发展和推广共享自动驾驶汽车具有重要参考价值。
Abstract：The development of shared autonomous vehicles(SAVs) is an important direction in intelligent and green transportation,but the relevant research is insufficient.The choice behavior of SAV passengers needs additional analysis.To address this,we first constructed an extended technology acceptance model(ETAM) by introducing three latent variables:perceived risk,service quality,and social influence.A hybrid choice model was then constructed by integrating the latent variables of the ETAM,individual socioeconomic attributes,and travel mode attributes into a multinomial logit model.The probability of passengers choosing an SAV is taken as an evaluation index to measure passengers' willingness to take an SAV.Finally,based on the Stated Preference survey data,the model parameters were calibrated,and the pathways of latent variables and key influencing factors were obtained.The impact of key factors on passengers' willingness to take an SAV was studied through elastic analysis.The elastic analysis revealed that perceived usefulness(0.0502) is the most significant factor,followed by travel cost(-0.0401),perceived ease of use(0.0385),and waiting time(-0.0350).This study can provide theoretical support for relevant enterprises and government departments to develop and promote SAVs.
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基本信息:
DOI：10.19961/j.cnki.1672-4747.2021.02.003
中图分类号:U463.6
引用信息:
[1]胡晓伟,石腾跃,于璐,等.基于扩展技术接受度模型的共享自动驾驶汽车用户使用意愿研究[J],2021,19(03):1-12.DOI:10.19961/j.cnki.1672-4747.2021.02.003.
基金信息:
国家自然科学基金重大研究计划(91846301);; 黑龙江省哲学社会科学研究规划项目(20GLC204)