基于站点的城市轨道线网规划方法研究
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摘要
近年来,我国大城市机动车快速增长,城市道路交通设施的建设却相对滞后,交通需求的增长远大于供给的增长,城市道路负荷日益严重,交通拥挤、道路阻塞、交通事故频发,由此导致的环境污染和经济损失越来越严重。通过优先发展城市公共交通来解决缓解交通问题,已经成为学术界和政府管理部门的一种共识。由于常规的地面公交系统运量有限,建设大运量、先进的快速公交系统,如BRT、轻轨、地铁等,已成为大城市公共交通系统发展的趋势。
线网的空间形态是整个线网规划的关键部分。该部分目前的规划方法主要是以定性分析与定量分析相结合、以定性分析为主的研究方法。在定量分析中很重要的一部分是轨道线网的客流预测。目前采用的客流预测方法基本以“四阶段法”为主,有一套比较完整的预测理论和方法。此模式采用交通需求预测的经典步骤：出行产生、出行分布、出行方式划分和交通分配。该类模型在理论上较为完善,但是在实际运用中存在一些不足。本次研究针对轨道线网的空间形态规划方法,探讨基于站点的轨道线网空间形态的关键技术,主要为基于站点的客流预测和利用遗传算法进行轨道线网空间优化,为线网构架规划提供更多的定量规划方法。
空间数据基于微观单元的分解为基于站点的可达性模型的构建创造了良好的基础。实际数据表明城市轨道站点主要吸引站点周边的步行到达客流。利用可达性原理,预测出站点周边步行到达的客流,可以推求出站点总的客流量。本文基于此原理,研究了利用站点可达性预测站点客流量的方法,并以武汉市为例进行了参数配置。结果表明此方法获得的预测值有一定的准确度。
基于站点的线网优化能很好的保证站点的覆盖率,在获得站点流量的基础上,探讨利用遗传算法进行轨道线网的优化。首先,利用随机行走原理,在城市道路网节点上计算各站点的权重,在考虑站点在城市交通系统中的地位的基础上,综合常规公交客流量,对城市道路网中的站点进行评价分级,获得优化后的重要站点作为城市候选轨道站点。接着,在首末站点对之间寻找符合约束条件的K最短路,作为候选线路集。然后,利用遗传算法在候选线路集中优选出一套完整的轨道线网。在项目组开发完成的规划程序上,以武汉市为例,进行了案例分析,得到的轨道线网关键指标与现实中的武汉市轨道线网规划指标较为接近。
Recently, especially in the swollen cities, the amount of motor vehicles is increasing rapidly. while the construction of transportation facilities is relatively lagging.so traffic demands is bigger than supply。 As a result, various traffic problems relevant come out. such as aggravating traffic jam, frequently happened traffic accident, and traffic environment deterioration. Now A consensus between political circles and academia has emerged that the priority of the development of urban public transportation so as to ease traffic problems.Limited by the capacity of bus system, the construction of the rapid transit has become a development tendency in large cities, such as BRT. light rail, and subway metro, etc.
The spatial form is the key point of network planning. The main research method in this area is to combine qualitative analysis and quantitative analysis, and qualitative analysis is used as the major method. Passenger volume forecast of rail net is an important part of quantitative analysis method. The four-step method is one of the widest applications in forecasting technology, has its own integrated theory system and technique。It has four stages namely:trip generation,trip distribution,model split and traffic assignment。This type of models has comparatively perfect theories, but suffers from a few drawbacks in practice. For the planning methods of spatial form, this article explores the key techniques of spatial form of rail network based on rail transit station so as to optimize the rail net using genetic algorithms and predict the passenger volume of rail transit station. Thus we can provide more quantitative analysis methods for the planning of network.
The decomposition of spatial data based on the microcosmic unit is good for build the model related to accessibility. The actual data indicate that passengers at the rail station mainly come from walkers around the site. Based on the principle about accessibility, we can predict the overall passenger volume of rail transit station by forecasting the pedestrian volume around the sites。Based on this principle, this paper studied the methods of passenger flow prediction at the rail station by analyzing the accessibility of the rail station. In the case of Wuhan, the results showed that the forecast data is accurate comparatively.
The optimization of network based on the rail station is favorable to ensuring the coverage percentage of the public transport station. Based on the volume of station, this paper studied the optimization of rail network using the genetic algorithm. Firstly, based on the principle of random process, we assessed the level of each station by computing the weight of each station, and the optimized nodes of higher level are seen as the candidate sites of the rail network.Secondly, under certain constraints, find out the K-shortest-paths between the terminal stops, and these paths are regarded as the set of candidate lines.Then, an integrated network is gained from the set of candidate lines by the application of genetic algorithms. In the case of Wuhan, we put this theory into practice using a program developed by our project group, the results showed that the forecast data of rail net is analogy to the real indicators of Wuhan urban rail transit network plan.
线网的空间形态是整个线网规划的关键部分。该部分目前的规划方法主要是以定性分析与定量分析相结合、以定性分析为主的研究方法。在定量分析中很重要的一部分是轨道线网的客流预测。目前采用的客流预测方法基本以“四阶段法”为主,有一套比较完整的预测理论和方法。此模式采用交通需求预测的经典步骤：出行产生、出行分布、出行方式划分和交通分配。该类模型在理论上较为完善,但是在实际运用中存在一些不足。本次研究针对轨道线网的空间形态规划方法,探讨基于站点的轨道线网空间形态的关键技术,主要为基于站点的客流预测和利用遗传算法进行轨道线网空间优化,为线网构架规划提供更多的定量规划方法。
空间数据基于微观单元的分解为基于站点的可达性模型的构建创造了良好的基础。实际数据表明城市轨道站点主要吸引站点周边的步行到达客流。利用可达性原理,预测出站点周边步行到达的客流,可以推求出站点总的客流量。本文基于此原理,研究了利用站点可达性预测站点客流量的方法,并以武汉市为例进行了参数配置。结果表明此方法获得的预测值有一定的准确度。
基于站点的线网优化能很好的保证站点的覆盖率,在获得站点流量的基础上,探讨利用遗传算法进行轨道线网的优化。首先,利用随机行走原理,在城市道路网节点上计算各站点的权重,在考虑站点在城市交通系统中的地位的基础上,综合常规公交客流量,对城市道路网中的站点进行评价分级,获得优化后的重要站点作为城市候选轨道站点。接着,在首末站点对之间寻找符合约束条件的K最短路,作为候选线路集。然后,利用遗传算法在候选线路集中优选出一套完整的轨道线网。在项目组开发完成的规划程序上,以武汉市为例,进行了案例分析,得到的轨道线网关键指标与现实中的武汉市轨道线网规划指标较为接近。
Recently, especially in the swollen cities, the amount of motor vehicles is increasing rapidly. while the construction of transportation facilities is relatively lagging.so traffic demands is bigger than supply。 As a result, various traffic problems relevant come out. such as aggravating traffic jam, frequently happened traffic accident, and traffic environment deterioration. Now A consensus between political circles and academia has emerged that the priority of the development of urban public transportation so as to ease traffic problems.Limited by the capacity of bus system, the construction of the rapid transit has become a development tendency in large cities, such as BRT. light rail, and subway metro, etc.
The spatial form is the key point of network planning. The main research method in this area is to combine qualitative analysis and quantitative analysis, and qualitative analysis is used as the major method. Passenger volume forecast of rail net is an important part of quantitative analysis method. The four-step method is one of the widest applications in forecasting technology, has its own integrated theory system and technique。It has four stages namely:trip generation,trip distribution,model split and traffic assignment。This type of models has comparatively perfect theories, but suffers from a few drawbacks in practice. For the planning methods of spatial form, this article explores the key techniques of spatial form of rail network based on rail transit station so as to optimize the rail net using genetic algorithms and predict the passenger volume of rail transit station. Thus we can provide more quantitative analysis methods for the planning of network.
The decomposition of spatial data based on the microcosmic unit is good for build the model related to accessibility. The actual data indicate that passengers at the rail station mainly come from walkers around the site. Based on the principle about accessibility, we can predict the overall passenger volume of rail transit station by forecasting the pedestrian volume around the sites。Based on this principle, this paper studied the methods of passenger flow prediction at the rail station by analyzing the accessibility of the rail station. In the case of Wuhan, the results showed that the forecast data is accurate comparatively.
The optimization of network based on the rail station is favorable to ensuring the coverage percentage of the public transport station. Based on the volume of station, this paper studied the optimization of rail network using the genetic algorithm. Firstly, based on the principle of random process, we assessed the level of each station by computing the weight of each station, and the optimized nodes of higher level are seen as the candidate sites of the rail network.Secondly, under certain constraints, find out the K-shortest-paths between the terminal stops, and these paths are regarded as the set of candidate lines.Then, an integrated network is gained from the set of candidate lines by the application of genetic algorithms. In the case of Wuhan, we put this theory into practice using a program developed by our project group, the results showed that the forecast data of rail net is analogy to the real indicators of Wuhan urban rail transit network plan.
引文
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