摘要
发展城市轨道交通已经成为大城市解决拥堵问题和调整城市空间结构的重要手段。如何量化城市轨道交通在公共交通系统中的作用,是规划和决策部门的关注重点。鉴此,融合多源交通大数据构建公共交通时变网络,提出时变网络下出行成本的计算方法与基于累计机会模型的公共交通动态可达性及其可靠性的计算方法,分析城市轨道交通对公共交通动态可达性的贡献度。以深圳为例,结果表明:相较于地面公交,城市轨道交通可降低公共交通系统平均行程时间达8分钟,进而提升动态可达性和可达性置信度的比例分别为23.2%和6.2%。城市轨道交通的影响主要作用于其沿线及线路末端区域,将大幅度提升线路末端居民的出行能力。
Developing urban rail transit has become an important means for big cities to solve congestion problems and adjust urban spatial structure.How to quantify the role of urban rail transit in the public transportation system is the focus of planning and decision-making departments.In view of this,multi-source traffic big data is integrated to construct a time-varying public transportation network with and without urban rail transit.Based on this,the travel cost function under the time-varying network is constructed,and the concept of accessibility confidence is introduced to calculate and evaluate the dynamic accessibility of public transport based on the cumulative opportunity model,and to study the contribution of urban rail transit to the dynamic accessibility of public transport.The results of Shenzhen case show that urban rail transit reduces the average travel time between grids by 8 minutes,and improves the confidence of accessibility and accessibility by 23.2%and 6.2%respectively.The impact of urban rail transit mainly affects the areas along its route and at the end of the line,greatly improving the travel capacity of residents at the end of the line.
作者
孙世一
肖中圣
顾静航
陈越
许奇
SUN Shiyi;XIAO Zhongsheng;GU Jinghang;CHEN Yue;XU Qi(Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport,Ministry of Transport,Beijing Jiaotong University,Beijing 100044,China;Rail Transit Branch of China Communications Construction Co.,Ltd.Beijing 101300,China;China Metro Engineering Consulting Co.,Ltd.Beijing 100037,China;School of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,China)
出处
《综合运输》
2024年第6期46-53,共8页
China Transportation Review
基金
国家自然科学基金(71621001)。
关键词
公共交通
城市轨道交通
时变网络
动态可达性
多源大数据
Public transport
Urban rail transit
Time-varying network
Dynamic accessibility
Multi-source big data