Travel Patterns and Street Networks: A Novel Visualization Methodology of City-Level Traffic Flows and Network Usability

Street Networks, knitted in the urban fabric, facilitate spatial movement and control the flow of urbanization. The interrelation between a city’s spatial network and how the residents travel over it has always been of high interest to scholars. Over the years, multifaceted visualization methods have emerged to better express this travel trend from small to large scale. This study proposes a novel approach to 1) visualize city-wide travel patterns with respect to the street network orientation and 2) analyze the discrepancies between travel patterns and streets to evaluate network usability. The visualizations adopt histograms and rose diagrams to provide several insights into network-wide traffic flows. The visualization of four New York City (NYC) boroughs including Queens, Brooklyn, Bronx, and Staten Island was generated for the daily traffic and the average hourly flows in the morning and evening rush hours. Then the contrasts between built-in street network topology and travel orientation were drawn to show where people travel over the network, travel demand, and finally which segments experience high or light traffic, revealing the true picture of network usability. The findings of the study provide an insight into the novel and innovative approach that can help better understand the travel behavior lucidly and assist policymakers in decision making to maintain a balance between urban topology and travel demands. In addition, the study demonstrates how to further investigate city street networks and urbanization from different diverse dimensions.

Street network patterns for mitigating urban heat islands in arid climates

This study explores the impact of street pattern measurements on urban heat islands(UHI)in the arid climate of Mashhad,Iran.The Landsat-8 top-of-the-atmosphere(TOA)brightness images from 2013 to 2021,average values of normalized difference vegetation index(NDvI)and land surface temperature(LST)were calculated.Street pattern measurements,including closeness-centrality,straightness,and street orientation,were employed to analyse the patterns in each district.The results indicated that districts with higher straightness and lower closeness-centrality exhibit,cooler surface temperatures.Strong correlations were observed between LST and NDVl,straightness,and local closeness-centrality.The research highlighted the importance of considering street network measurements in long-term urban planning and design to mitigate the UHI effect in arid regions.A moderate grid street pattern with a reasonable distribution of green spaces throughout the region is suggested to reduce surface temperatures sustainably.Street pattern indexes,such as straightness and local closeness-centrality,are identified as significant factors in urban design to mitigate UHl.These findings have implications for urban planners,who can use this information to create street network patterns with lower UHI effects by reducing local closeness-centrality and increasing straightness.

Sustainability-oriented configurational analysis of the street network of China's superblocks:Beyond Marshall's model

The duality in China's traffic planning has given rise to the basic unit of urban form and function called the superblock,which is defined and bound by an arterial street network.The street network of China's superblock un derpins the coexiste nee and in teraction of global and local movement,the public and daily space,and affects place diversity and local characteristics.However,its configuration remains to be articulated because of the lack of a systematic representation method,and the associations between configuration and performance,cognition and design cannot be determi ned.This study proposes an improved representation method for the street network of China's superblocks based on Marshall's route structure analysis to explore the configurational characteristics and sustainability of the network.To fit local conditions,this study improves Marshall's route structure analysis from four perspectives,namely,the judgement of relative hierarchy,the node construction principle,and the deletion and addition of the original indicators.The improved method is then applied to calculate and compare the depth,connectivity,and complexity of the street networks of 10 sample superblocks in Nanjing,which are classified into six types by construction backgrounds,each having two seenarios differing by the level of publicity.Results indicate that the types formed in accordance with the"The Capital Plan"of the Republic of China,which presents a combination of fine orthogonal grids and radiations,and by the renewal of the traditional street-andlane network,which has the"characteristic structure" defined by Marshall,perform best in terms of configurational sustainability.The an alysis also reveals that the addition of semipublic streets formed mainly from the bottom up narrows the sustainability gap among the samples.This study provides a tool for elaborate urban study and design and provides in sights into the cognitive and practical aspects of China's urban planning and design.

Street networks in relation to landforms： Implications for fast-growing cities

In addition to socio-economic factors, major landforms may affect the city structure and urban form. Here we show that landforms have significant effects on the city shape and street patterns of the fast-growing Iranian cities of Dezful （a river） and Khorramabad （moun- tains and valleys）, but no clear effects on the cities of Yazd and Nain. Also, where the street orientation is peaked, the Gibbs/Shannon entropy （a measure of dispersion or spread） is low, but increases as the distribution becomes more uniform because of landform constraints. The streets in the old inner parts of all the cities are, on average, shorter and denser （more streets per unit area） than the streets of the newer outer parts. The entropies of the outer parts are also greater than those of the inner parts, implying that the street-length distribution gradually becomes more dispersed or spread as the city expands. All these cities have been fast growing in the past decades, with the newer outer parts expanding rapidly. As shown here, the rapidly formed outer parts （with greater dispersion in street patterns） have significantly different textures from those of the older inner parts, indicating different functionality and growth processes. These quantitative methods for street-network analysis can be used worldwide, particularly for analysing the effects of landforms on city shape and texture.

A congestion bottleneck analysis model for tourist block street network

The development of the tourism industry has led to increased pressure of people flow in tourist blocks.Therefore,it is critical to ease the traffic pressure in these blocks.This paper aims to identify the bottleneck links of street networks in tourist blocks to achieve the effective prevention of congestion accidents.A logit stochastic user equilibrium model combined with spatial syntax is presented to study the travelers’route choice behavior.The nonlinear Bureau of Public Roads function is applied to calculate the time impedance of each street.A case analysis of the Chongqing Ciqikou tourist block shows that the bottleneck link has the features of high integration and a large degree of negative time impedance evolution.The research’s results are more consistent with practical circumstances because the influence of the road network topological structure on pedestrian path selection has been considered.

基于跨层次聚合网络的实时城市街景语义分割

随着自动驾驶技术的迅速发展,精确高效的场景理解显得尤为重要。城市街景语义分割旨在准确识别并分割出行人、障碍物、道路和标志物等要素,为自动驾驶技术提供必要的道路信息。然而,当前的语义分割算法在城市街景分割中仍然面临一些挑战,主要表现为不同类别的像素区分不够清晰、对于复杂场景结构的理解不够精准以及对小尺度对象或大尺度结构的分割不准确等问题。为此,本文提出一种基于跨层次聚合网络的实时城市街景语义分割算法。首先,在编码器末端设计了结合跨层次聚合的金字塔池化模块,用于高效提取多尺度上下文信息;其次,在编码器和解码器之间设计了跨层次聚合模块,通过引入通道注意力机制增强信息的表征能力,逐级聚合编码器阶段的特征以充分实现特征复用;最后,在解码器阶段设计了多尺度融合模块,在通道维度聚合全局信息与局部信息,促进深层特征与浅层特征的融合。将所提算法在两个通用的城市街景数据集上进行了验证。在一张RTX3090显卡上(TensorRT测速环境),本文算法在Cityscapes测试集以294 FPS的实时性达到73.0%mIoU的准确性,在更高分辨率的图像上以164 FPS的实时性达到75.8%mIoU的准确性;在CamVid数据集以239 FPS的实时性达到74.8%mIoU的准确性。实验结果表明,本文算法在准确性与实时性之间取得了有效平衡,对比其他算法的语义分割性能具有显著提升,为实时城市街景语义分割领域带来了新的突破。

基于网络点评的游憩体验质量与包装设计关系探究——以杭州清河坊街为例

近年来,游憩体验质量被提出并用于衡量游客满意水平,同时大众对旅游产品包装设计的要求也与日俱增。本文以杭州清河坊街区游客的网络点评为研究对象,运用网络文本分析方法,对游憩体验质量与包装设计的关系进行了探究。研究发现包装设计与游憩体验质量有显著联系,与包装设计有关的点评总体呈现积极的情感色彩,消极体验主要由于包装设计的潜在欺骗性与辨识度缺失。基于发现,提出可持续的旅游产品包装设计建议。

基于Walnut Street修正模型的短波信道仿真算法

传统短波信道Watterson模型只能模拟信道短期变化规律。为模拟短波信道在各种长度时间段内的变化,针对短波信道接收端信噪比统计特性,提出了一种基于信噪比重放的短波信道仿真算法。该算法以Walnut Street信道模型为基础,通过对实际观测数据进行分析处理,建立接收端信噪比变化的中期和长期变化统计模型,联合Watterson模型实现信道模拟。仿真结果表明,该算法可反映实际信噪比变化规律,为短波网络仿真提供精确的信道质量模拟。

基于ZigBee网络和自适应PSD算法的路灯分布式节能控制方法

当前照明系统缺乏分布式路灯动态化控制,浪费大量能源,为此,提出了基于ZigBee网络和自适应PSD算法的路灯分布式节能控制方法。通过ZigBee网络通信连接系统传感器、控制中心和照明终端,协调设备通信功能,实现信息快速传输储存。利用神经网络处理信号数据,提高系统信号检测和处理效率。在此基础上,利用自适应PSD算法识别路灯信号动态特征,进行自适应信号检测,调节信号数据偏差,精确检测数据结果,增强系统节能控制稳定程度,实现路灯分布式节能控制。由实验结果可知,研究方法将分布式路灯检测精准度提高到99%,熔池宽度稳定在3.5W/mm,具有良好的检测精准度和控制稳定性,可以对路灯进行节能控制。

Exploring Location Pattern of Commercial Stores in Shichahai, Beijing from a Street Centrality Perspective

The location pattern of different commercial stores in Shichahai, a historic conservation area in Beijing, was investigated from a street centrality perspective. Many previous studies have investigated the relationship between street centrality and land use patterns or commercial activities at interurban or intraurban scales. We considered Shichahai in this study to determine if street centrality applied at the street scale and if the street network was the only factor influencing the selection of store location. First, the nearest neighbor index, nearest neighbor hierarchical spatial cluster(NNHSC), and kernel density estimation(KDE) methods were used to provide baseline spatial distributions of commercial stores. Second, urban network analysis(UNA) tools were used to measure the street centrality indices under two conditions, with and without the weighting of cultural relics calculated by a principal component analysis(PCA). Finally, both store locations and centrality values at nodes were transformed to one unit(raster pixel) for a correlation analysis.The results showed that three of the four store types were clustered and had their own hotspots that were mostly located in the eastern and central parts of city blocks. The most momentous findings were determined from the street centrality indices. Among the three store types with correlation coefficients above 0.5, all centrality indices with landmark weighting, except straightness, had higher correlations,with closeness with landmark weighting having the highest correlation, followed by betweenness with landmark weighting. Therefore,we statistically concluded that street centrality could apply at the street scale and that the street network was not the only factor that influenced store location pattern, with landmarks also playing a significant role. The results provide guidance in determining the selection strategy for stores in a historic conservation area.

探析医院建筑柱网柱跨的合理确定

介绍了国内医院建筑柱网柱跨相关研究进展;分析了地下室停车位、“双通道”设计、未来开设公共服务空间的需求等因素对医院建筑柱网柱跨的影响;对8100 mm和8400 mm柱跨形成的诊室、病房进行了对比,并对柱跨选择提出了具体建议。

特殊软件工具在典型街区发展情景判断中的应用

历史文化街区存有一定数量、规模和比例的历史建筑物、构筑物和传统街巷空间格局,因其能反映城市历史发展过程并呈现鲜明的地方特色,因而深受游客青睐。临海紫阳街是台州府城文化旅游区的重要组成部分,拥有丰富的文化旅游资源。文章基于扎根理论,借助软件对紫阳街的网络评价进行网络文本词频分析和情感分析,深入梳理临海紫阳街开发过程中面临的优势与不足,进而提出了如何充分发挥临海紫阳街独特的优势,实现旅游功能、产业功能和城市功能有机联动的具体建议。

基于“高程-边界”耦合算法的街巷肌理测绘研究

针对街巷肌理结构复杂,测绘难度大,精度难以控制的问题,本文基于无人机航测技术,运用“高程-边界”耦合算法实现街巷要素的快速、高精度测绘,并选取街巷肌理复杂、测绘难度较大的某城市更新项目进行实例研究。结果表明,“高程-边界”耦合算法在保障街巷肌理测绘成果精度和提高测绘效率方面均具有良好的应用效果。

Smart Street Lighting Control and Monitoring System for Electrical Power Saving by Using VANET

The huge amount of electrical power of many countries is consumed in lighting the streets. However, vehicles pass with very low rate in specific periods of time and parts of the streets are not occupied by vehicles over time. In this paper, we propose a system that automatically switches off the light for the parts of the streets having no vehicles and turns on the light for these parts once there are some vehicles that are going to come. Logically, this system may save a large amount of the electrical power. In addition, it may increase the lifetime of the lamps and reduce the pollutions. This system automatically controls and monitors the light of the streets. It can light only the parts that have vehicles and help on the maintenance of the lighting equipments. Vehicular Ad-Hoc Networks (VANET) make it possible to propose such system. VANET enables the possibility to know the presence of vehicles, their locations, their directions and their speeds in real time. These quantities are what are needed to develop this system. An advantage of using VANET is that there is no need to use specific network and equipments to design the system, but VANET infrastructure will be used. This decreases the cost and speed up the deployment of such system. This paper focuses on the proposal of different possible architectures of this system. Results show that the saved energy may reach up to 65% and an increase of the lifetime of the lamps of 53%.

基于UWB的智能道路照明系统的设计与实现

针对目前道路照明智能化过程中存在的路灯定位不准、通信质量不佳、智能化不足等问题,基于超宽带(UWB)技术设计了一种街巷智能路灯控制系统。该系统以UWB通信技术为基础,主要由路灯管理中心、智能配电柜、LED单灯控制器组成,使用循环迭代和卡尔曼滤波实现了使用有限数量的UWB基站实现了对全部路灯的精确定位,同时设计了基于结点状态的贪婪周边无状态路由协议(GPSR)自组网路由算法将路灯形成了数据通信网。测试表明该系统的响应迅速,平均单跳延时小于150 ms,分组投递率超过了90%,组网稳定可靠,通信实时性高,有效提高了道路照明系统的智能化,同时降低了建设、运营成本。

基于空间句法的清华大学校园历史与人文景观空间形态演变研究

基于空间句法中整合率与穿行率2个指标,对清华大学校园景观空间形态及其演变展开建模、分析与论述。通过对景观形态特征与历史社会经济特点的讨论,将清华大学校园景观形态的演变分为4个时期作为理解景观形态发展的框架,包括熙春园时期、美式校园时期、单位制时期和书院回归时期。结果表明,熙春园时期的3个重要历史景观均为现代校园师生出行的重要空间节点。不同时期关键景观节点具备通过空间形态特征,反映校园发展过程中典型文化意识形态的潜力。历史与人文景观空间节点在师生出行中逐渐向穿行地的角色靠拢。同时基于聚类分析,发现清华大学1954年前后建成的景观空间差异性较大。

智慧路灯自动控制与测试装置的设计与实现

为满足智慧城市对道路智能照明的需求,提出一种基于模糊控制理论的智慧路灯自动控制与测试装置设计方案。结合6LoWPAN通信协议的无线传感器网络和Visual Basic的可视化编程技术,设计一套基于模糊控制规则的智慧路灯自动控制与测试装置。经过软硬件调试,该套装置实现了路灯亮度的自动调整、远程控制和相关路灯数据的远程传输功能。实验结果表明,该装置可以使路灯“智慧”地根据其周围自然光的强弱实时调控亮度,实现智能化的节能调节效果,并将路灯的相关数据远程传输。

基于空间句法的古镇街道空间网络更新——以东溪古镇为例

东溪古镇作为川渝千年古镇,现有的街道已不能满足当前快速的城市化发展。如何更加科学、系统地对古镇的街巷空间进行更新与改造是目前古镇发展的一大难题。文章通过引入空间句法理论,对古镇现有的街巷空间进行梳理,建立古镇街道空间轴线模型。借助DepthmapX软件对街道的可达性、穿行度与可理解度进行定量分析,并结合现状资料与实地调研,提出了街道空间更新的几点建议,以期为未来古镇街道空间更新提供一定的理论依据。

基于街景影像和深度学习技术的城市流动商贩空间分布制图

流动商贩是城市社会生态系统中不可或缺的组成部分,高效治理流动商贩问题需要全面调查他们的经营规模和空间聚集信息。然而,传统方法在大规模流动商贩信息(尤其是他们的空间分布)的自动调查存在不足。文章提出一种基于街景影像和深度学习目标识别模型的流动商贩空间分布自动调查方法。按城市路网的固定间隔距离采集街景影像,通过人机交互的方式选取1957张包含一个或以上商贩的图像建立流动商贩标签数据。构建基于YOLO v4深度神经网络的图像目标检测模型识别街景影像库中的流动商贩,模型的平均F1值为0.77、mAP为0.67。精度能满足覆盖城市主要道路的流动商贩数量和位置调查的需要,进而应用核密度分布模型评估流动商贩的空间分布格局。以广州市的街头流动商贩为案例,通过所建立的自动调查模型在3339062幅街景影像中识别出26119名街头商贩,结果表明,流动商贩在中心城区以多中心聚集模式分布,主要集中在地铁站、城中村附近等人流量大的区域,随着道路等级的下降其数量上升,而且流动商贩偏好分布于租金中等的地区。文章提出的方法有助于实现高效、低成本和城市尺度的街头摊贩分布制图,所得结果有助于制定和实施非正规经济的空间治理政策,并进一步为街景图像丰富且开放的城市的空间治理政策的改进和实施提供建议。识别结果可用于对从业者的区位偏好分析、“邻避效应”探究以及疏导区的划定提供决策参考依据。

以提升步行体验为目标的窄路密网型街道景观设计研究

传统的交通型街道通常是将“以车为本”作为主要设计原则,而疏于考虑行人的感受。而窄路密网理念下的街道界面宽度变窄,可有效限制车速,并为行人营造安全舒适的步行空间,更符合“以人为本”的街道设计原则。论文从景观专业的角度,以打造绿色街道和活力街道为目标,提出适合窄路密网型街道的设计方法,以打造满足步行需求为主要导向的街道空间。