城市群结构及其交通需求特性研究

本文首先辨析了都市圈与城市群的定义,然后分析了城市群结构特征以及在不同结构下的交通需求特性。论文分析了城市群土地利用与交通系统的互动关系,并在总结日本东京城市群经验的基础上,提出了城市群发展的若干经验与建议。     

中原城市群城际轨道交通线网规划方案研究

中原城市群作为我国中部五个城市群之一,在实现区域经济协调发展战略、促进中部崛起中具有重要意义。本文采用点线面要素层次分析法和功能层次分析法相结合的线网规划方法,在中原城市群空间布局规划的宏观指导下,详细分析城际客运需求,提出中原城市群线网构架,并通过不同线网构架的优缺点分析,给出推荐线网方案。     

湘江长株潭港口水运优势分析

<正>“以武汉城市圈、中原城市群、长株潭城市群、皖江城市带为重点,形成支撑经济发展和人口焦聚的城市群,带动周边地区发展。”2006年4月,随着中共     

TOD模式下轨道交通站点周边土地利用优化模型

为了改善城市无序蔓延、道路交通拥挤等问题,建立以轨道交通为主体的TOD(Transitoriented development)模式,针对轨道交通站点周边的土地利用结构,提出以土地容积率为决策变量,以最大化轨道交通客流量、最大化土地增值、最大化居住环境舒适度为目标的多目标优化模型。采用遗传算法求Pareto最优解,定量分析适宜TOD模式的合理容积率。以成都市轨道交通2号线犀浦站为例,对其周边土地利用进行优化,调整后的土地利用结构对比调整前,略微降低了居住环境舒适度,显著提升了轨道交通客流量和土地增值,对TOD模式下的轨道交通站点周边土地利用规划具有一定的参考价值。     

城市群航空和铁路连通性分析与协同发展策略

本文选取长三角城市群、珠三角城市群、京津冀城市群、长江中游城市群、中原城市群、成渝城市群等城市群为研究对象,使用2016年3月份航班及列车时刻表的数据,建立各主要城市间连通度模型,分析各主要城市群之间的航空和铁路连通度,并提出各城市群之间航空与铁路的协同发展策略。     

城市群内外城际出行特征比较分析——以长三角城市群为例

以长三角城市群为例,从客运总量、交通设施、交通方式和旅客出行特征四个方面比较分析了城市群内外城际出行的特征。结果表明,城市群内部城际出行的客运总量大于城市群外的客运总量,并且城市群内各城市之间有更快速和完善的交通通道和交通设施。城市群内各城市之间主要依托于发达的轨道交通和道路交通,城市群外的城际出行主要依托于铁路和航空运输。城市群内外城际出行旅客在职业、收入和出行形式方面也有差异。     

推进郑州市轨道交通网络一体化发展

郑州地处中华腹地，在全国经济发展格局中发挥承东启西、贯通南北的重要作用，具有非常有利的区位优势；此外，郑州又是河南省政治、经济、文化中心，还定位为中原城市群的核心城市，是带动中原城市群发展的龙头。郑州拥有丰富的多层次轨道交通资源，为满足经济发展需要创造了有利的交通条件，加快构筑发达、系统的多层次轨道交通体系以及实现各层次轨道交通网络一体化，可有效加强城市群内部及与外部的交通联系，减少以生产、消费和商务为目的的出行在空间、时间上的阻碍，是进一步提高区位优势，实现中原城市群发展战略的重要前提，也是区域经济一体化最重要的基础。     

邯郸市构建区域交通中心的战略思考

<正>邯郸市地处河北省的"南梢",东部与山东省相连,西部与山西省相邻,南部与河南省相接,位于晋冀鲁豫四省的交界处,并连接中部地区与环渤海地区,与中原城市群、半岛城市群、京津冀城市群相距均在200公里左右。独特的区位不仅使邯郸成为连接中部地区与环渤海地区最重要的纽带,同时也成为四省交界区域的中心城市,是河北省实施"东出西联"战略的重要节点和陆地桥头堡,是河北省建设沿海强省的重要战略区域。     

构筑中国沿海发展轴的骨干——建设上海北至大连、南至香港沿海大铁路

<正> 一、构筑沿海综合交通走廊势在必行 中国东部沿海地带,土地面积占全国13％,人口占41％。目前,该地带工农业总产值已占全国59％,国民生产总值占52％;不到1/7的国土,构成中国经济的半壁江山。今后,随着沿海开放的深化、香港、澳门的回归和中国统一进程的加速,沿海地带将出现四个巨大城市群:①以北京、天津、大连为中心的环渤海城市群;②以上海、南京、杭州为中心的长江三角洲城市群;③以厦门、福州、台北为中心的闽台海峡城市群;④以广州、香港、澳门为中心的珠江三角洲城市群。这四大城市群,集中了全国最先进和最庞大的生产力、创新力和影响力,是带动中国现     

物流节点用地网运分离发展模式探讨

随着物流业的发展,物流网络节点的数量和规模不断扩展,用地需求不断增加。本文针对物流节点用地开发利用的部门分离(纵向一体)模式的缺陷,提出了物流节点用地的网运分离(横向一体)开发利用模式,以高效集约利用土地。     

Distinguishing the land use effects of road pricing based on the urban form attributes

This paper studies the effects of road pricing on land use under different development scenarios (business as usual scenario and transit oriented development scenario) by a quantitative method, which combines the integrated land use and transport interaction model (TRANUS model) with the scenario-planning techniques. Moreover, in order to further analyze the differences of the land use effects of road pricing on traffic analysis zones (TAZs) with different urban form attributes, a quantitative classification method combining factor analysis and cluster analysis is then used to quantitatively classify TAZs. The results demonstrate that the effects of road pricing on the land use of a specific region depend on the urban form attributes of the region. The higher the densities of employments and population, and better street design (high densities of street and intersections) and public transportation condition, the less the region is negatively affected by road pricing, and vice versa. More importantly, rail transit can alleviate the negative impact of road pricing on commercial development and population concentration of the region. Therefore, before introducing a road pricing policy, it is necessary to develop public transport system, especially rail transit.     

基于灰色关联度的交通安全道路影响因素辨析

道路系统中诸因素共同作用决定了系统的交通安全发展态势。如何在众多因素中寻找主要致因,是进行道路安全改善时所必须面对的问题。考虑到数据获取贫信息的特点,采用灰色关联分析,不但可以提高现有数据的利用率,而且弥补常用数理统计方法作系统分析所导致的缺憾。实例分析表明:采用此方法所得到的主要道路影响因素和交通安全之间的关联度大小与实地踏查结果相吻合,结果说明灰色关联度可以简单而高效地进行系统因素辨析。     

Analyzing the impact of a planned transit-oriented development on mode share and traffic conditions

ABSTRACT

Transit-oriented development (TOD) is a popular planning strategy used to maximize accessibility to transit for various trip purposes. The quantitative effects of TOD on travel mode shift and traffic congestion have not been extensively tested in the current literature. This paper utilizes a seemingly unrelated regressions (SUR) mode share model and a mesoscopic dynamic traffic assignment (DTA) model to analyze the impact of a planned TOD in Maryland. The proposed model aims at improving the understanding of the quantitative impacts of such a TOD on mode share and traffic congestion. The main result of the mode share model indicates that the increase in transit ridership for a transit accessible shopping center is not that significant. Local traffic conditions will deteriorate due to a lack of investment in road infrastructure planned for the TOD area. The proposed method could be a valuable tool for other indicative land development or transportation policy analyses.     

Enhanced traffic information dissemination to facilitate toll road utilization: a nested logit model of a stated preference survey in Texas

This paper investigates the effects of the provision of traffic information on toll road usage based on a stated preference survey conducted in central Texas. Although many researchers have studied congestion pricing and traffic information dissemination extensively, most of them focused on the effects that these instruments individually produce on transportation system performance. Few studies have been conducted to elaborate on the impacts of traffic information dissemination on toll road utilization. In this study, 716 individuals completed a survey to measure representative public opinions and preferences for toll road usage in support of various traffic information dissemination classified by different modes, contents, and timeliness categories. A nested logit model was developed and estimated to identify the significant attributes of traffic information dissemination, traveler commuting patterns, routing behavior, and demographic characteristics, and analyze their impacts on toll road utilization. The results revealed that the travelers using dynamic message sign systems as their primary mode of receiving traffic information are more likely to choose toll roads. The potential toll road users also indicated their desire to obtain traffic information via internet. Information regarding accident locations, road hazard warnings, and congested roads is frequently sought by travelers. Furthermore, high-quality congested road information dissemination can significantly enhance travelers’ preferences of toll road usage. Specifically the study found that travelers anticipated an average travel time saving of about 11.3 min from better information; this is about 30 % of travelers’ average one-way commuting time. The mean value of the time savings was found to be about $11.82 per hour, close to ½ of the average Austin wage rate. The model specifications and result analyses provide in-depth insights in interpreting travelers’ behavioral tendencies of toll road utilization in support of traffic information. The results are also helpful to shape and develop future transportation toll system and transportation policy.     

Study on road section environmental traffic capacity model and algorithm under double constraints

The coordinated development of city traffic and environment is a key research content in traffic field in twenty-first Century. Among them, road section environmental traffic capacity analysis is one of the important research issues. It can provide solid theoretical basis and reliable data support for road network traffic optimization control, road traffic pollution control and city traffic structure optimization. This paper analyzed main factors which impacted environmental traffic capacity from two aspects, including road capacity constraint conditions and road traffic pollution control constraint conditions. Then, road section environmental traffic capacity optimization model was established, and method of improved augmented Lagrange function was used to solve the model. Case study showed that, (1) The environmental traffic capacity optimal model and methodology were effective; (2) In order to ensure road section environmental traffic capacity greater than (or equal to) road capacity, some measures could be taken including adjusting motor vehicle type proportion as well as improving emission characteristics of motor vehicles exhausting pollutants.     

Bayesian network-based formulation and analysis for toll road utilization supported by traffic information provision

Congestion pricing has been proposed and investigated as an effective means of optimizing traffic assignment, alleviating congestion, and enhancing traffic operation efficiencies. Meanwhile, advanced traffic information dissemination systems, such as Advanced Traveler Information System (ATIS), have been developed and deployed to provide real-time, accurate, and complete network-wide traffic information to facilitate travelers’ trip plans and routing selections. Recent advances in ATIS technologies, especially telecommunication technology, allow dynamic, personalized, and multimodal traffic information to be disseminated and impact travelers’ choices of departure times, alternative routes, and travel modes in the context of congestion pricing. However, few studies were conducted to determine the impact of traffic information dissemination on toll road utilizations. In this study, the effects of the provisions of traffic information on toll road usage are investigated and analyzed based on a stated preference survey conducted in Texas. A Bayesian Network (BN)-based approach is developed to discover travelers’ opinions and preferences for toll road utilization supported by network-wide traffic information provisions. The probabilistic interdependencies among various attributes, including routing choice, departure time, traffic information dissemination mode, content, coverage, commuter demographic information, and travel patterns, are identified and their impacts on toll road usage are quantified. The results indicate that the BN model performs reasonably well in travelers’ preference classifications for toll road utilization and knowledge extraction. The BN Most Probable Explanation (MPE) measurement, probability inference and variable influence analysis results illustrate travelers using highway advisory radio and internet as their primary mode of receiving traffic information are more likely to comply with routing recommendations and use toll roads. Traffic information regarding congested roads, road hazard warnings, and accident locations is of great interest to travelers, who tend to acquire such information and use toll roads more frequently. Travel time formation for home-based trips can considerably enhance travelers’ preferences for toll road usage. Female travelers tend to seek traffic information and utilize toll roads more frequently. As expected, the information provided at both pre-trip and en-route stages can positively influence travelers’ preferences for toll road usage. The proposed methodology and research findings advance our previous study and provide insight into travelers’ behavioral tendencies concerning toll road utilization in support of traffic information dissemination.     

A traffic noise model for road intersections in the city of Cartagena de Indias,Colombia

Road traffic noise models are fundamental tools for designing and implementing appropriate prevention plans to minimize and control noise levels in urban areas. The objective of this study is to develop a traffic noise model to simulate the average equivalent sound pressure level at road intersections based on traffic flow and site characteristics, in the city of Cartagena de Indias (Cartagena), Colombia. Motorcycles are included as an additional vehicle category since they represent more than 30% of the total traffic flow and a distinctive source of noise that needs to be characterized. Noise measurements are collected using a sound level meter Type II. The data analysis leads to the development of noise maps and a general mathematical model for the city of Cartagena, Colombia, which correlates the sound levels as a function of vehicle flow within road intersections. The highest noise levels were 79.7 dB(A) for the road intersection María Auxiliadora during the week (business days) and 77.7 dB(A) for the road intersection India Catalina during weekends (non-business days). Although traffic and noise are naturally related, the intersections with higher vehicle flow did not have the highest noise levels. The roadway noise for these intersections in the city of Cartagena exceeds current limit standards. The roadway noise model is able to satisfactorily predict noise emissions for road intersections in the city of Cartagena, Colombia.     

A comparative study of the emissions by road maintenance works and the disrupted traffic using life cycle assessment and micro-simulation

Life cycle assessment is being accepted by the road industry to measure such key environmental impacts as the energy consumption and carbon footprint of its materials and laying processes. Previous life cycle studies have indicated that the traffic vehicles account for the majority of fuel consumption and emissions from a road. Contractors and road agencies are looking for road maintenance works that have the least overall environmental impact considering both the roadwork itself and the disrupted traffic. We review life cycle assessment studies and describe the development of a model for pavement construction and maintenance, detailing the methodology and data sources. The model is applied to an asphalt pavement rehabilitation project in the UK, and the micro-simulation program VISSIM is used to model the traffic on that road section. The simulation results are fed into a traffic emissions model and emissions from the roadwork and the traffic are compared. The additional fuel consumption and emissions by the traffic during the roadwork are significant. This indicates that traffic management at road maintenance projects should be included in the life cycle assessment analysis of such work.     

How tube strikes affect macroscopic and link travel times in London

Abstract

The purpose of this study was to investigate the impact of the five strikes on the London Underground (metro) rail system, which occurred in 2009 and 2010, on macroscopic and road link travel times. A consequence of these strikes was an increase in road traffic flows above usual levels. This provides an opportunity to observe the operation of the road network under unusually high flows. The first objective involves the examination of strike effects on inbound (IT) and outbound traffic (OT) within central, inner and outer London. Travel time data obtained from automatic number plate recognition cameras are used within the first part of the analysis. The second more detailed objective was to investigate in spatio-temporal effects on travel times on five road links. Correlation analyses and general linear models are developed using both traffic flow and travel time data. According to the results of the study, the morning IT had approximately twice as much delay as the OT. Central London experienced the highest delays, followed by inner and outer London. As would be expected, the unique full-day strike in 2009 yielded the worst impact on the network with the highest percentage increase in total travel time (60%) occurring during the morning peak in the IT in inner London. The results from the link-level analysis showed statistical significance amongst the examined links indicating heterogeneous effects from one link to another. It was also found that travel time changes may be more effectively captured through time-of-day terms compared to hourly traffic flows.     

Analyzing spatiotemporal traffic line source emissions based on massive didi online car-hailing service data

Nowadays, the massive car-hailing data has become a popular source for analyzing traffic operation and road congestion status, which unfortunately has seldom been extended to capture detailed on-road traffic emissions. This study aims to investigate the relationship between road traffic emissions and the related built environment factors, as well as land uses. The Computer Program to Calculate Emissions from Road Transport (COPERT) model from European Environment Agency (EEA) was introduced to estimate the 24-h NOx emission pattern of road segments with the parameters extracted from Didi massive trajectory data. Then, the temporal Fuzzy C-Means (FCM) Clustering was used to classify road segments based on the 24-h emission rates, while Geographical Detector and MORAN’s I were introduced to verify the impact of built environment on line source emissions and the similarity of emissions generated from the nearby road segments. As a result, the spatial autoregressive moving average (SARMA) regression model was incorporated to assess the impact of selected built environment factors on the road segment emission rate based on the probabilistic results from FCM. It was found that short road length, being close to city center, high density of bus stations, more ramps nearby and high proportion of residential or commercial land would substantially increase the emission rate. Finally, the 24-h atmospheric NO₂ concentrations were obtained from the environmental monitor stations, to calculate the time variational trend by comparing with the line source traffic emissions, which to some extent explains the contribution of on-road traffic to the overall atmospheric pollution. Result of this study could guide urban planning, so as to avoid transportation related built environment attributes which may contribute to serious atmospheric environment pollutions.