Search Results (10)

Vehicle acceleration typically occurs at traffic lights, intersections, or congested sections within urban streets, where high densities of pedestrians and vehicles pose a direct threat to respiratory health due to PM_2.5 dispersion. Computational Fluid Dynamics (CFD) simulations, combined with the Dynamic Mode Decomposition (DMD) method, are used to analyze the dynamic characteristics of PM_2.5 dispersion during vehicle acceleration. The DMD method can effectively analyze the dynamic change in pollutant concentration in an unsteady flow field and clarify the influence mechanism of vehicle acceleration on pollutant dispersion. The results indicate that PM_2.5 dispersion during the initial stage of acceleration is primarily influenced by low-frequency and large-scale flows, such as exhaust emissions, natural wind, and trailing vortices. In the middle stage, PM_2.5 dispersion tends to stabilize, while in the final stage, high-frequency modes dominate, and intense flow field fluctuations significantly enhance PM_2.5 dispersion. Furthermore, the analysis reveals the critical role of upward and downward airflow phenomena around the vehicle in driving PM_2.5 dispersion. This study offers a new perspective on the dispersion characteristics of PM_2.5 under unsteady flow conditions in urban streets and provides a scientific basis for developing speed management strategies to mitigate the impact of pollutant dispersion. Full article

This paper addresses the growing importance of efficient street lighting management, driven by rising electricity costs and the need for municipalities to implement cost-effective solutions. Central to this study is the UNI 11248 Italian regulation, which extends the European EN 13201-1 standard introduced in 2016. These standards provide guidelines for designing, installing, operating, and maintaining lighting systems in pedestrian and vehicular traffic areas. Specifically, the UNI 11248 standard introduces the possibility to dynamically adjust light intensity through two alternative operating modes: (a) Traffic Adaptive Installation (TAI), which dims the light based solely on real-time traffic flow measurements; and (b) Full Adaptive Installation (FAI), which, in addition to traffic measurements, also requires evaluating road surface luminance and meteorological conditions. In this paper, we first present the general architecture and operation of an FAI-enabled lighting infrastructure, which relies on environmental sensors and a heterogeneous wireless communication network to connect intelligent, remotely controlled streetlights. Subsequently, we examine large-scale, in-field FAI infrastructures deployed in Vietnam and Italy as case studies, providing substantial measurement data. The paper offers insights into the measured energy consumption of these infrastructures, comparing them to that of conventional light-control strategies used in traditional installations. The measurements demonstrate the superiority of FAI as the most efficient solution. Full article

The impact of urban morphology on air quality, particularly within deep canyons with longer residence times for complex chemical processes, remains insufficiently addressed. A flexible multi-box framework was used to simulate air quality at different canyon heights (3 m and 12 m). This approach incorporated essential parameters, including ventilation rates, background concentrations, photochemical schemes, and reaction coefficients. A field campaign within a deep canyon with an aspect ratio of 3.7, in Naples, Italy was conducted and used for the model evaluation. The model performance demonstrated good agreement, especially at the street level, when employing a realistic light intensity profile and incorporating volatile organic compound (VOC) chemistry. Our findings indicate that peroxyl radical production affects NO₂ and O₃ levels by up to 9.5% in deep canyons and underscore the significance of vertical distribution (approximately 5% variance) in health assessments and urban air quality strategy development. The model response was sensitive to changes in emissions as expected, but also, somewhat more surprisingly, to background conditions, emphasizing that policies to remove pollution hotspots must include local and broader citywide action. This work advances the understanding of air quality dynamics in deep urban canyons and presents a valuable tool for effective air quality management in intricate urban environments. Full article

(1) Background: A three-dimensional (3D) real scene is a digital representation of the multidimensional dynamic real-world structure that enables the realistic and stereoscopic expression of actual scenarios, and is an important technological tool for urban refinement management. The above-ground biomass (AGB) of urban forests is an important indicator that reflects the urban ecological environment; therefore, the accurate estimation of AGB is of great significance for evaluating urban ecological functions. (2) Methods: In this study, multiangle aerial photographs of urban street trees were obtained via an unmanned aerial vehicle (UAV) single-lens five-way flight, from 0°, 0°, 90°, 180°, 270°, and five other directions. The multiple view stereo (MVS) algorithm was used to construct three-dimensional realistic models of two tree species: ginkgo and camphor. Then, structural parameters such as tree height, crown diameter, and crown volume were estimated from the 3D real-scene models. Lastly, single-tree AGB models were developed based on structural parameters. (3) Results: The results of this study indicated the following: (A) The UAV visible-light realistic 3D model had clear texture and truly reflected the structural characteristics of two tree species, ginkgo and camphor. (B) There was a significant correlation between the reference tree height, crown diameter and crown volume obtained from the realistic 3D model and the measured values; the R² for ginkgo height was 0.90, the R² for camphor crown diameter was 0.87, and the R² for ginkgo crown volume was 0.89. (C) The accuracy of the AGB estimation models constructed with tree height and canopy volume as variables was generally higher than that of models with tree height and canopy diameter; the model with the highest accuracy of AGB estimation for ginkgo was the linear model with a validation accuracy R² of 0.96 and RMSE of 8.21 kg, while the model with the highest accuracy of AGB estimation for camphor was the quadratic polynomial model with a validation accuracy R² of 0.92 and RMSE of 27.74 kg. (4) Conclusions: This study demonstrated that the UAV 3D real-scene model can achieve high accuracy in estimating single-wood biomass in urban forests. In addition, for both tree species, there was no significant difference between the AGB estimates based on the UAV 3D real scene and LiDAR and the measured AGB. These results of urban single-wood AGB estimation based on the UAV 3D real-scene model were consistent with those of LiDAR and even with the measured AGB. Therefore, based on the UAV 3D real-scene model, the single-wood biomass can be estimated with high accuracy. This represents a new technical approach to urban forest resource monitoring and ecological environment function evaluation. Full article

Understanding the biomass, characteristics, and carbon sequestration of urban forests is crucial for maintaining and improving the quality of life and ensuring sustainable urban planning. Approaches to urban forest management have been incorporated into interdisciplinary, multifunctional, and technical efforts. In this review, we evaluate recent developments in urban forest research methods, compare the accuracy and efficiency of different methods, and identify emerging themes in urban forest assessment. This review focuses on urban forest biomass estimation and individual tree feature detection, showing that the rapid development of remote sensing technology and applications in recent years has greatly benefited the study of forest dynamics. Included in the review are light detection and ranging-based techniques for estimating urban forest biomass, deep learning algorithms that can extract tree crowns and identify tree species, methods for measuring large canopies using unmanned aerial vehicles to estimate forest structure, and approaches for capturing street tree information using street view images. Conventional methods based on field measurements are highly beneficial for accurately recording species-specific characteristics. There is an urgent need to combine multi-scale and spatiotemporal methods to improve urban forest detection at different scales. Full article

Numerous approaches have attempted to develop systems that more appropriately manage street crossings in cities in recent years. Solutions range from intelligent traffic lights to complex, centralized protocols that evaluate the policies that vehicles must comply with at intersections. Such works attempt to provide traffic-control strategies at intersections where the complexity of a dynamic environment, with vehicles crossing in different directions and multiple conflict points, pose a significant challenge for city traffic optimization. Traditionally, a traffic-control system at an intersection gives the green light to one lane while keeping the other lanes on red. But there may be situations in which there are different levels of vehicle priority; for example, emergency vehicles may have priority at intersections. Thus, this work proposes a distributed junction-management protocol that pays special attention to emergency vehicles. The proposed algorithm implements rules based on the distributed intersection management (DIM) protocol; such rules are used by vehicles while negotiating their crossing through the intersection. The proposal also seeks to affect the traffic flow of non-priority vehicles minimally. An evaluation and comparison of the proposed algorithm are presented in the paper. Full article

Complete streets scheme makes seminal contributions to securing the basic public right-of-way (ROW), improving road safety, and maintaining high traffic efficiency for all modes of commute. However, such a popular street design paradigm also faces endogenous pressures like the appeal to a more balanced ROW for non-vehicular users. In addition, the deployment of Autonomous Vehicle (AV) mobility is likely to challenge the conventional use of the street space as well as this scheme. Previous studies have invented automated control techniques for specific road management issues, such as traffic light control and lane management. Whereas models and algorithms that dynamically calibrate the ROW of road space corresponding to travel demands and place-making requirements still represent a research gap. This study proposes a novel optimal control method that decides the ROW of road space assigned to driveways and sidewalks in real-time. To solve this optimal control task, a reinforcement learning method is introduced that employs a microscopic traffic simulator, namely SUMO, as its environment. The model was trained for 150 episodes using a four-legged intersection and joint AVs-pedestrian travel demands of a day. Results evidenced the effectiveness of the model in both symmetric and asymmetric road settings. After being trained by 150 episodes, our proposed model significantly increased its comprehensive reward of both pedestrians and vehicular traffic efficiency and sidewalk ratio by 10.39%. Decisions on the balanced ROW are optimised as 90.16% of the edges decrease the driveways supply and raise sidewalk shares by approximately 9%. Moreover, during 18.22% of the tested time slots, a lane-width equivalent space is shifted from driveways to sidewalks, minimising the travel costs for both an AV fleet and pedestrians. Our study primarily contributes to the modelling architecture and algorithms concerning centralised and real-time ROW management. Prospective applications out of this method are likely to facilitate AV mobility-oriented road management and pedestrian-friendly street space design in the near future. Full article

Over the last few years, there has been a significant increase in people’s dependence on passenger and freight transport. As a result, traffic infrastructure is congested, especially in big city centers and, at critical times, this is to the point of traffic collapse. This has led to the need to address this situation by the progressive deployment of Intelligent Transport Systems (ITS), which are used to optimize traffic, to increase traffic flow, and to improve transport safety, including reduction of adverse environmental impacts. In 2018, the first results of the C-Roads Platform which is a joint initiative of European Member States and road operators for testing and implementing C-ITS services in light of cross-border harmonization and interoperability (C-ROADS) Czech Republic project were put into operation in Brno, closely related to the international initiative to support the data structure for future communication between vehicles and intelligent transport infrastructure. A system of transport organization and safety was introduced in the city of Brno, which manages key information and ensures central management of partial systems of transport organization and safety. The most important part of this system is the parking organization system discussed in this article. The main objective was to streamline the parking system in the city center of Brno and in the immediate vicinity by preventing unauthorized long-term parking, ensuring an increased number of parking places for residents and visitors by increasing the turnover of parking. The aim of the research was to investigate (i) the possibility and optimal use of Geographic Information System (GIS) technology for resident parking system solutions, (ii) the integration of Global Satellite Navigation Systems (GNSS) satellite data and image data collected by cameras on the move and (iii) the possibility of using network algorithms to optimize mobile data collection planning. The aim of our study is to design and optimize the integrated collection of image data localized by satellite GNSS technologies in the GIS environment to support the resident parking system, including an evaluation of its effectiveness. To achieve this goal, a residential parking monitoring system was designed and implemented, based on dynamic monitoring of the parking state using a vehicle equipped with a digital camera system and Global Satellite Navigation Systems (GNSS) technology for measuring the vehicle position, controlled by spatial and attribute data flow from static and dynamic spatial databases in the Geographic Information System (GIS), which integrate the whole monitoring system. The control algorithm of a vehicle passing through the street network works on the basis of graph theory with a defined recurrence interval for the same route, taking into account other parameters such as the throughput of the street network at a given time, its traffic signs and the usual level of traffic density. Statistics after one year of operation show that the proposed system significantly increased the economic yield from parking areas from the original 30% to 90%, and reduced the overall violation of parking rules to only 10%. It further increased turnover and thus the possibility of short-term parking for visitors and also ensured availability of parking for residents in the historical center of Brno and surrounding monitored areas. Full article

Violence among spectators at sports events has become a serious problem, not only for its evident impact on safety, but also from the perspective of environmental, cultural, economic and social sustainability. Although it could be considered a purely social problem, some solutions could come from a smart and efficient design and management of the lighting installations. Thus, the management of sports installations requires deep considerations of lighting technology for three reasons: (1) accurate illumination allows the users to achieve their visual task with comfort and safety; (2) the energy consumption of sports facilities can be decreased with an efficient design of the lighting installation; and (3) the lighting impacts some psychological and physiological aspects such as arousal, stress or relaxation which are directly related to violence. In this work, the recent advances on the matter of light sources and non-visual effects of light are deployed within a new proposal of dynamic Light-emitting diode (LED) lighting to decrease violence among spectators. Here, sustainable sports facilities are considered from a global perspective where accurate illumination in each zone (court, bleachers, training rooms and surrounding streets) plays an important role in violence avoidance. Full article

Internet of Things (IoT) seems a viable way to enable the Smart Cities of the future. iNUIT (Internet of Things for Urban Innovation) is a multi-year research program that aims to create an ecosystem that exploits the variety of data coming from multiple sensors and connected objects installed on the scale of a city, in order to meet specific needs in terms of development of new services (physical security, resource management, etc.). Among the multiple research activities within iNUIT, we present two projects: SmartCrowd and OpEc. SmartCrowd aims at monitoring the crowd’s movement during large events. It focuses on real-time tracking using sensors available in smartphones and on the use of a crowd simulator to detect possible dangerous scenarios. A proof-of-concept of the application has been tested at the Paléo Festival (Switzerland) showing the feasibility of the approach. OpEc (Optimisation de l’Eclairage public) aims at using IoT to implement dynamic street light management and control with the goal of reducing street light energy consumption while guaranteeing the same level of security of traditional illumination. The system has been tested during two months in a street in St-Imier (Switzerland) without interruption, validating its stability and resulting in an overall energy saving of about 56%. Full article