考虑个人偏好的观赛人群组合决策选择行为
Combined decision-choice behavior of spectators considering personal preferences
熊志华 1董黛悦 2董春娇 1郑炎 3解超4
作者信息
- 1. 北京交通大学 综合交通运输大数据应用技术交通运输行业重点实验室,北京 100044
- 2. 浙江省交通运输科学研究院,杭州 310000
- 3. 东南大学 交通学院,南京 211102
- 4. 中交信有限责任公司,北京 100029
- 折叠
摘要
掌握观赛人群出行行为特征是应对赛事举办期间交通量激增、保障城市交通正常运行的关键.基于个人属性、出行特征、观赛特性和出行意愿的954份调查样本,引入结构方程刻画安全性、便捷性、经济性和出行意向4个潜变量与11个显变量的因果作用关系,考虑个人偏好对出发时间和出行方式组合决策选择行为的潜在影响,构建了基于SEM-NLogit的观赛人群组合决策选择行为模型.研究表明,模型预测精度为87.06%,与巢式Logit和多元Logit模型相比精度提高了6.99%和18.18%.本文模型更好地刻画了"观赛人群年龄越大,更倾向于提前出发;同伴数量越多、收入越高,越倾向于选择小汽车出行"的特征,并得到了出行时更注重安全性与经济性等巢式Logit模型无法得到但更符合实际出行规律的个人偏好的选择行为.
Abstract
Understanding the travel behavior characteristics of spectators is the key to solve the problem of the surge in traffic during the event and ensure the normal operation of urban traffic.Combining the 954 survey samples of the individual attributes,travel characteristics,spectators behavior characteristics and travel intention of the spectators,a structural equation model(SEM)can describe the causal relationship between four latent variables and eleven obvious variables from the perspectives of safety,convenience,economy and travel intention.Considering the potential impact of personal preference in the combined departure time decision and travel mode chosen behavior,a SEM Nested Logit(SEM-NLogit)model is developed to investigate the combined decision-choice behavior of spectators.The results show that the developed SEM-NLogit model has the best fit and accuracy,and the prediction accuracy is 87.06%,which is 6.99%and 18.18%improvement compared to the NLogit and multivariate logit models respectively.Moreover,the findings show that the elders prefer to departure early,more companions,higher income,more likely to choose a car to travel,and the spectators more emphasis on safety and economy when traveling,which is the findings that NLogit model cannot obtain,but it is more in line with the actual travel law.
关键词
城市交通/大型赛事/组合决策选择行为/巢式Logit模型/结构方程模型Key words
urban traffic/large-scale events/combined decision-choice behavior/nested Logit model/structural equation model引用本文复制引用
基金项目
国家重点研发计划(2019YFF0301400)
中央高校基本科研业务费专项(2019JBM041)
出版年
2024
NETL
NSTL
万方数据