多交路运营是中国城市轨道交通网络化运营组织的重要组成部分,研究乘客在多交路运营条件下的出行选择行为,对把握乘客出行规律、满足多样化出行需求具有重要意义.基于随机后悔最小化模型,引入乘客对路径属性感知的异质性,构建融合效用...多交路运营是中国城市轨道交通网络化运营组织的重要组成部分,研究乘客在多交路运营条件下的出行选择行为,对把握乘客出行规律、满足多样化出行需求具有重要意义.基于随机后悔最小化模型,引入乘客对路径属性感知的异质性,构建融合效用与后悔机制的多尺度混合模型,克服了传统模型未考虑路径熟悉度导致的乘客出行行为与实际出行行为之间的决策偏差.通过整合容忍阈值与决策惯性,提出一种多交路出行选择建模方法,基于典型案例的陈述偏好(stated preference,SP)调查数据,完成模型参数估计与性能验证.研究结果表明,乘客对出行时间属性的容忍阈值为6.98 min;相较于基准模型,考虑决策惯性的模型在似然值、贝叶斯信息准则(Bayesian information criterion,BIC)及命中率指标上均表现更优,表明其具备更强的数据拟合能力;支付意愿分析进一步揭示乘客愿意为服务提升承担额外时间成本,从而验证了所提模型的有效性与实用性.展开更多
The accessibility of urban public transit directly influences residents’quality of life,travel behavior,and social equity.Its correlation with housing prices has garnered significant attention across disciplines such...The accessibility of urban public transit directly influences residents’quality of life,travel behavior,and social equity.Its correlation with housing prices has garnered significant attention across disciplines such as geography,economics,and urban planning.Although much existing research focuses on the impact of individual transportation facilities on housing prices,there is a notable gap in comprehensive analyses that assess the influence of overall urban transit accessibility on housing market dynamics.This study selected the main urban area of Hefei,China,as a case to investigate the spatial distribution of housing prices and evaluate public transit accessibility in 2022.Employing techniques such as the optimized parameter geographical detector and local spatial regression models,the study aimed to elucidate the effects and underlying mechanisms of urban transit accessibility on housing prices.The findings revealed that:1)housing prices in Hefei exhibited a clustered spatial pattern,with high prices concentrated in the city center and lower prices in peripheral areas,forming three distinct high-price hotspots with a‘belt-like’distribution;2)public transit accessibility showed a‘coreperiphery’structure,with accessibility declining in a‘circumferential’pattern around the city center.Based on the‘housing price-accessibility’dimension,four categories were identified:high price-high accessibility(37.25%),high price-low accessibility(19.07%),low price-high accessibility(21.95%),and low price-low accessibility(21.73%);3)the impact of transit accessibility on housing prices was spatially heterogeneous,with bus travel showing the strongest explanatory power(0.692),followed by automobile,subway,and bicycle travel.The interaction of these transportation modes generated a synergistic effect on housing price differentiation,with most influencing factors contributing more than 25%.These findings offer valuable insights for optimizing the spatial distribution of public transit infrastructure and improving both urban housing quality and residents’living standards.展开更多
文摘多交路运营是中国城市轨道交通网络化运营组织的重要组成部分,研究乘客在多交路运营条件下的出行选择行为,对把握乘客出行规律、满足多样化出行需求具有重要意义.基于随机后悔最小化模型,引入乘客对路径属性感知的异质性,构建融合效用与后悔机制的多尺度混合模型,克服了传统模型未考虑路径熟悉度导致的乘客出行行为与实际出行行为之间的决策偏差.通过整合容忍阈值与决策惯性,提出一种多交路出行选择建模方法,基于典型案例的陈述偏好(stated preference,SP)调查数据,完成模型参数估计与性能验证.研究结果表明,乘客对出行时间属性的容忍阈值为6.98 min;相较于基准模型,考虑决策惯性的模型在似然值、贝叶斯信息准则(Bayesian information criterion,BIC)及命中率指标上均表现更优,表明其具备更强的数据拟合能力;支付意愿分析进一步揭示乘客愿意为服务提升承担额外时间成本,从而验证了所提模型的有效性与实用性.
基金Under the auspices of the National Natural Science Foundation of China(No.42271224,41901193)Ministry of Edu cation Humanities and Social Sciences Research Planning Fund Project of China(No.24YJAZH190)+1 种基金Anhui Province Excellent Youth Research Project in Universities(No.2022AH030019)Anhui Social Sciences Innovation Development Research Project(No.2024CXQ503)。
文摘The accessibility of urban public transit directly influences residents’quality of life,travel behavior,and social equity.Its correlation with housing prices has garnered significant attention across disciplines such as geography,economics,and urban planning.Although much existing research focuses on the impact of individual transportation facilities on housing prices,there is a notable gap in comprehensive analyses that assess the influence of overall urban transit accessibility on housing market dynamics.This study selected the main urban area of Hefei,China,as a case to investigate the spatial distribution of housing prices and evaluate public transit accessibility in 2022.Employing techniques such as the optimized parameter geographical detector and local spatial regression models,the study aimed to elucidate the effects and underlying mechanisms of urban transit accessibility on housing prices.The findings revealed that:1)housing prices in Hefei exhibited a clustered spatial pattern,with high prices concentrated in the city center and lower prices in peripheral areas,forming three distinct high-price hotspots with a‘belt-like’distribution;2)public transit accessibility showed a‘coreperiphery’structure,with accessibility declining in a‘circumferential’pattern around the city center.Based on the‘housing price-accessibility’dimension,four categories were identified:high price-high accessibility(37.25%),high price-low accessibility(19.07%),low price-high accessibility(21.95%),and low price-low accessibility(21.73%);3)the impact of transit accessibility on housing prices was spatially heterogeneous,with bus travel showing the strongest explanatory power(0.692),followed by automobile,subway,and bicycle travel.The interaction of these transportation modes generated a synergistic effect on housing price differentiation,with most influencing factors contributing more than 25%.These findings offer valuable insights for optimizing the spatial distribution of public transit infrastructure and improving both urban housing quality and residents’living standards.
