Dense Urban Environments Research Articles

On-Demand Autonomous Vehicles in Berlin: A Cost–Benefit Analysis

The technological development of autonomous vehicles (AVs) challenges their economic relevancy. Are AVs worth it? We adapted the cost–benefit analysis framework to the case of AV services. The appraisal methodology was applied to the introduction of an on-demand AV service in Berlin, simulated through MATSim, an agent-based model. The introduction of AVs in a dense urban environment would generate more pressure on the road network. This would cause private car users to experience longer travel times, resulting in a consumer surplus loss that would not offset the new AV users’ benefits. In one configuration, a stop-based routing service appeared to generate fewer externalities (e.g., congestion, emissions, accidents) and would be cheaper to operate than door-to-door routing. Another configuration assumed that private cars were banned. In that case, the consumer surplus significantly decreased, AV services were not able to absorb the entire demand, and the shares of other modes increased. However, the externalities were significantly reduced. Finally, in an urban environment where on-demand AVs were added to the available modes, the social impact was negative for all economic agents, with heterogeneity apparent on the impacts of the different externalities. This would benefit some travelers but would also involve additional congestion. In that case, a stop-based routing seemed preferable (but still negative) to a door-to-door one. Further works discussing the introduction of AVs into an urban environment should focus on line-based options such as automated bus services.

Air pollutant dispersion around high-rise building cluster forms: the case of Port City, Colombo, Sri Lanka.

Air quality in dense urban environments is a growing concern, especially in rapidly developing cities. In the face of growing traffic associated with urbanisation, there is evidence for high levels of pollutant concentration at street level which is influenced by building forms. In this paper, we examine the potential effects of high-rise, cluster developments permitted by the local planning authorities in the newly established Port City development in Colombo, Sri Lanka. We designed possible building forms based on specific guidelines for the development in terms of plot coverage, floor area ratio, and maximum height. The three-dimensional building clusters were simulated using the RANS RNG k-epsilon turbulence model, to determine pollutant dispersion of a complex street formation in a high-dense high-rise building cluster, within the development and the surrounding context (existing Colombo). Results show that while increased porosity within the built fabric facilitates better pollution dispersion, a low correlation was seen between wind velocity and pollution concentration, especially in deep narrow high-rise canyons. Dispersion patterns at street level and at the urban canopy differed with each built form and are dependent on each canyon geometry. Thus, the study highlights the need for building regulations to take a holistic approach to capture the various elements of a complex urban cluster rather than the current two-dimensional parameters proposed for Port City, Colombo.

Sky-GVINS: a sky-segmentation aided GNSS-Visual-Inertial system for robust navigation in urban canyons

ABSTRACT Integrating Global Navigation Satellite Systems (GNSS) in Simultaneous Localization and Mapping (SLAM) systems draws increasing attention to a global and continuous localization solution. Nonetheless, in dense urban environments, GNSS-based SLAM systems will suffer from the Non-Line-Of-Sight (NLOS) measurements, which might lead to a sharp deterioration in localization results. In this paper, we propose to detect the sky area from the up-looking camera to improve GNSS measurement reliability for more accurate position estimation. We present Sky-GVINS: a sky-aware GNSS-Visual-Inertial system based on a recent work called GVINS. Specifically, we adopt a global threshold method to segment the sky regions and non-sky regions in the fish-eye sky-pointing image and then project satellites to the image using the geometric relationship between satellites and the camera. After that, we reject satellites in non-sky regions to eliminate NLOS signals. We investigated various segmentation algorithms for sky detection and found that the Otsu algorithm reported the highest classification rate and computational efficiency, despite the algorithm’s simplicity and ease of implementation. To evaluate the effectiveness of Sky-GVINS, we built a ground robot and conducted extensive real-world experiments on campus. Experimental results show that our method improves localization accuracy in both open areas and dense urban environments compared to the baseline method. Finally, we also conduct a detailed analysis and point out possible further directions for future research. For detailed information, visit our project website at https://github.com/SJTU-ViSYS/Sky-GVINS.

Positioning performance analysis of real-time BDS-3 PPP-B2b/INS tightly coupled integration in urban environments

Since 2020, the BeiDou-3 global navigation satellite system has provided real-time precision single-point positioning enhancement services (PPP-B2b). The real-time correction provideded by this service can make real-time precision single-point positioning achieve decimeter-level. However, a dense urban environment may cause frequent interruption of GNSS signals, and PPP-B2b alone cannot achieve continuous precision positioning. This study documents a study that attempts to combine PPP-B2b with an inertial navigation system (INS). A real-time tightly coupled integration model of PPP-B2b/INS based on PPP-B2b services was constructed, and a performance analysis of the tightly coupled integration positioning of PPP-B2b/INS in different urban environments was performed. The experiment shows that in an open-sky environment, the decimeter-level positioning accuracy (North: 31.7; East: 21.3; Up: 39.6 cm and North: 34.1; East: 27.6; Up: 41.0 cm) can only be achieved based on PPP-B2b (BDS only and GPS only), PPP-B2b/INS tightly coupled integration positioning accuracy (North: 17.2; East: 10.3; Up: 19.4 cm), and the convergence time is faster; In a dense urban environment, GNSS signals are frequently interrupted, and the positioning accuracy (North: 141.3; East: 95.2; Up: 156.6 cm and North: 147.5; East: 96.4; Up: 159.3 cm) increases significantly only based on PPP-B2b (BDS only and GPS only), and positioning interruption occurs frequently. However, PPP-B2b/INS tightly coupled integration could still achieve continuous decimetre-level positioning (North: 30.0; East: 28.4; Up: 46.3 cm).

RIS-aided Multi-hop Backhauling for 5G/6G UAV-assisted Access Points

Drones are considered to be an important part of future 6G telecommunication systems. Thanks to their quick deployment potential, they provide additional connectivity options in the form of a flying hotspot. However, in such use cases, they typically require a wireless backhaul link to facilitate their proper operation, which might be a challenging task in dense urban environments. One of the potential methods that may be relied upon to connect such nodes is the integrated access and backhaul (IAB) approach, where part of the spectrum allocated to users accessing the base station is used for wireless backhauling. Thus, in this work, we consider the problem of establishing a multi-hop wireless backhaul link following the IAB concept, with the aid of drone relay stations (DRSs) and reconfigurable intelligent surfaces (RISs). We formulate the problem of coverage improvement with a fixed number of relays, assuming certain throughput requirements for the backhaul link. The simulations show that the use of RISs offers a coverage improvement in such a scenario or a reduction in the number of nodes involved in ensuring the required backhaul performance.

NR5G-SAM: A SLAM Framework for Field Robot Applications Based on 5G New Radio.

Robot localization is a crucial task in robotic systems and is a pre-requisite for navigation. In outdoor environments, Global Navigation Satellite Systems (GNSS) have aided towards this direction, alongside laser and visual sensing. Despite their application in the field, GNSS suffers from limited availability in dense urban and rural environments. Light Detection and Ranging (LiDAR), inertial and visual methods are also prone to drift and can be susceptible to outliers due to environmental changes and illumination conditions. In this work, we propose a cellular Simultaneous Localization and Mapping (SLAM) framework based on 5G New Radio (NR) signals and inertial measurements for mobile robot localization with several gNodeB stations. The method outputs the pose of the robot along with a radio signal map based on the Received Signal Strength Indicator (RSSI) measurements for correction purposes. We then perform benchmarking against LiDAR-Inertial Odometry Smoothing and Mapping (LIO-SAM), a state-of-the-art LiDAR SLAM method, comparing performance via a simulator ground truth reference. Two experimental setups are presented and discussed using the sub-6 GHz and mmWave frequency bands for communication, while the transmission is based on down-link (DL) signals. Our results show that 5G positioning can be utilized for radio SLAM, providing increased robustness in outdoor environments and demonstrating its potential to assist in robot localization, as an additional absolute source of information when LiDAR methods fail and GNSS data is unreliable.

Communication and Control in Collaborative UAVs: Recent Advances and Future Trends

The recent progress in unmanned aerial vehicles (UAV) technology has significantly advanced UAV-based applications for military, civil, and commercial domains. Nevertheless, the challenges of establishing high-speed communication links, flexible control strategies, and developing efficient collaborative decision-making algorithms for a swarm of UAVs limit their autonomy, robustness, and reliability. Thus, a growing focus has been witnessed on collaborative communication to allow a swarm of UAVs to coordinate and communicate autonomously for the cooperative completion of tasks in a short time with improved efficiency and reliability. This work presents a comprehensive review of collaborative communication in a multi-UAV system. We thoroughly discuss the characteristics of intelligent UAVs and their communication and control requirements for autonomous collaboration and coordination. Moreover, we review various UAV collaboration tasks, summarize the applications of UAV swarm networks for dense urban environments and present the use case scenarios to highlight the current developments of UAV-based applications in various domains. Finally, we identify several exciting future research direction that needs attention for advancing the research in collaborative UAVs.

Happiness, life satisfaction, and the greenness of urban surroundings

Cities’ environmental factors are pivotal for the quality of life of the population, and green space is increasingly recognized as a significant environmental factor in this regard. In this analysis, we study the contribution of green space to happiness in a mid-sized city in the Global South. We use a population survey and open satellite imagery to assess the relationship between self-reported happiness and the surrounding greenness of the respondent's place of residence while controlling for age, gender, and socioeconomic status. We measure surrounding greenness using the average NDVI value within different distances from the home address, calculated with open satellite imagery. The results show that age and surrounding greenness are significantly correlated with happiness, while the relationships with gender and socioeconomic status appear to be not significant. Our results indicate that increases of 10% in surrounding greenness at different distances from 100 up to 500 m increase the likelihood of self-reported happiness between 13% and 18%. When quality aspects of green areas are considered, they are also significantly correlated with happiness. This paper contributes to the knowledge of surrounding greenness and subjective well-being in one of the most urbanized regions in the world and promotes the discussion of well-being policies in urban planning. The results indicate that increasing surrounding greenness and its quality in dense urban environments could help to improve the quality of life and well-being of the urban populations in Global South cities like Cali.

Exploring the Spatial Intersection of Small Firm Innovation, Urban Form, and Demographics in the Washington, DC, Metropolitan Area

In an increasingly competitive global market for human and financial capital, cities have embraced a variety of strategies to lure investment and incubate lucrative businesses and industries in situ. Among other strategies, it has been suggested that local governments can both attract and catalyze the rise of knowledge-intensive businesses and innovative startups by cultivating dense, walkable, and transit-accessible urban environments where knowledge spillovers might be more likely and creative and knowledge workers can access an abundance of consumption amenities. This intensive case study of the Washington, DC, metropolitan area explores the potential spatial associations between attributes of urban form and innovation productivity as assessed using small business innovation awards. In addition to largely corroborating previous findings indicating a strong positive spatial correlation between small and midsized firm innovation and neighborhood walkability and transit quality, the results suggest the importance of other key supportive amenities including small business incubators or accelerators and local research universities, and highlight socioeconomic and demographic disparities between innovation hot spots and cold spots.

Projected Effects of a Deep Excavation Pit on the Existing Metro Tunnel and Findings of Geotechnical Monitoring: A Comparative Analysis

With the evolution of modern cosmopolitan cities, subterranean spaces have developed in dense urban environments. Hence, new metro tunnels often intersect with those in operation. The top-priority task of designers is to evaluate the effect of new construction projects. The experience accumulated in this field should contribute to the design of a realistic geotechnical model to simulate long-term displacements in the future. This paper includes a backward analysis of a design scheme developed for a tunnel construction area above an existing tunnel with a 10.3 m diameter, according to the results of geotechnical monitoring performed in PLAXIS 2D. The authors identified the optimum combination of the distance from the tunnel bottom to the lower boundary of the design model, the soil model, and tunnel lining stiffness. The authors derived regression equations describing vertical and horizontal displacements of the tunnel at the stage of excavation to the elevation datum as the excavation pit bottom. These equations can be applied to preliminarily predict the displacements of the tunnel depending on geometrical parameters at the initial design stage. Geometrical parameters include the distance from the tunnel to the excavation pit, the depth of the tunnel from the surface to the crown, the depth of the designed excavation pit, and the distance from the bottom of the excavation pit to the bottom of the tunnel. In addition, the effect of the Muir–Wood coefficient on the vertical displacements of the tunnel was investigated. This work found a reduction in the stiffness of the bearing structure of the tunnel and an increase of 4.8% in deformations on average when this coefficient was considered.

Investigating the Performance of Wi-Fi Mesh Networks in Dense Urban Environments

Investigating the Performance of Wi-Fi Mesh Networks in Dense Urban Environments

A Probabilistic Propagation Graph Modeling Method for Channel Characterization in Dense Urban Environments

With the rapid development of mobile broadband communications such as the “fifth generation (5G)” systems, accurate and efficient simulation-based channel modeling becomes more essential for propagation channel characterization in the complicated environments. In the previous works, the so-called “propagation-graph-based channel modeling” method has been introduced and effectively applied to the simulation of channel characteristics. Compared with the conventional ray-tracing-based approaches, the graph-based modeling may significantly reduce the computational complexity. In this contribution, without increasing computational complexity, the graph-based channel modeling method is proposed for channel characterization in the dense urban environments with the following improvements, i.e. realistic geometry-assisted scattering point placement, scattering coefficient definition, and line-of-sight (LoS) path presence probability settings. By comparing the simulated channel characteristics with those obtained in the real measurements in two urban scenarios, the proposed improvements are demonstrated in predicting channel characteristics more accurately.

SAT3D: Slot Attention Transformer for 3D Point Cloud Semantic Segmentation

Semantic segmentation of 3D point cloud is a key task in numerous intelligent transportation system applications, e.g. self-driving vehicles, traffic monitoring. Due to the sparsity and varying density of points in the outdoor point clouds, it becomes particularly challenging to extract object-centric features from data. This leads to poor semantic segmentation, especially for the rare object classes. To address that, we introduce the first-ever Slot Attention Transformer based technique to effectively model object-centric features in point cloud data. Our method uses cylindrical splits of space for voxelization and computes channel-wise positional embeddings before repetitively encoding the point cloud with slot attentions. Our second major contribution is a Large-Scale Outdoor Point Cloud dataset (SWAN), collected in a dense urban environment, driving 150km distance. It provides 16 billion points in more than 200K frames. The dataset also provides annotations for 10K frames for 24 classes. We also contribute a data augmentation scheme to handle rare object classes in real-world point clouds. Besides benchmarking popular existing methods on SWAN for the first time, we thoroughly evaluate our technique on the existing large-scale datasets, Semantic KITTI and nuScenes. Our results demonstrate a consistent performance gain for our technique, and verify the need of the more challenging SWAN dataset.

MONITORING THE ENVIRONMENT IN SMART CITIES: THE IMPORTANCE OF GEOSPATIAL LOCATION REFERENCING

Abstract. The Smart City concept is taking momentum recently as big metropolises as well as mid-size cities are intensifying their efforts to improve the life of people living in dense urban environment. Local governments are eager to have up-to-date information of every aspect of city life, including environmental data, such as air and water quality parameters; mobility data, such as traffic flow, including vehicles, transit passengers; crowd control, such as public events, mobility in hospitals; life quality data, such as social status, education level, health records; etc. Monitoring all these very different data streams in space and time is a formidable challenge. While on the data acquisition side, tremendous progress has been achieved, as sensors have been deployed in increasingly large numbers on both mobile and static platforms, there is a lack of creating accurate geotags, as the quality of georeferencing varies over a large scale. It is important to note that the data acquisition is becoming largely customer-based, as smart devices are efficient sensor systems and with advancing communication technologies, crowdsourcing is quickly becoming the dominant data source on mobile platforms. In this paper, we investigate the potential to exploit the ranging capabilities of imaging and communication sensors and use the strength of the spatial network formed by the sensors to improve the georeferencing of a group of platforms operating in a close environment, such as UAS swarm or a platoon of autonomous vehicles. Transportation in cities and in general mobility are of great interest to Smart Cities, they represent one of the most significant components of the activities, so having an optimized transportation system is essential to reduce carbon footprint, decrease commute time, and just improve the quality of life. To assess the performance of collaborative navigation based accurate georeferencing, data was acquired at a simulated intersection area at The Ohio State University, where multiple vehicles, pedestrians and cyclists were moving around. In addition, drones were flying above the area. Here we report about our initial results.

The role of baseflow and stormwater in transport of tire and bitumen particles in Tehran city: A dense urban environment

Urban stormwater runoff is the main terrestrial source of tire and bitumen particles as emerging pollutants, which have adverse effects on receiving aquatic and terrestrial environments. In this study, the occurrence and characteristics of tire and bitumen particles in four rainfall events and three baseflow had been measured at the end of a dense urban catchment in Tehran metropolis. Particles were classified to 37–300, 300–500, and 500–5000 μm with stainless steel sieves, and hydrogen peroxide 30% was used for digestion of organic matter, following density separation with ZnCl2 (1.7–1.75 g/mL) to separate tire and bitumen particles from minerals. The type of tire and bitumen particles was determined by Micro-Raman and FTIR ATR. The number of tire and bitumen particles in rainfall events was 3.3–60.5 and 3.5–73 particles/L, respectively, and in the base flow were 0.5–3 and 0.8–6.5 particles/L, respectively. The most abundant size of tire and bitumen particles was 37–300 μm. The highest abundance of tire and bitumen particles was observed during a rainfall event in peak discharge. The results indicate the important role of urban stormwater runoff, where there are high vehicle traffic and high road density, in the release into the environment of bitumen and rubber.

Consensus-Based Autonomous Navigation of a Team of RIS-Equipped UAVs for LoS Wireless Communication With Mobile Nodes in High-Density Areas

The reconfigurable intelligent surface (RIS) technology has gained increased attention for improving the performance and efficiency of the fifth-generation (5G) millimeter-wave (mmWave) wireless communication by obviating the propagation and blockage issues. On the other hand, the great flexibility of unmanned aerial vehicles (UAVs) has made them effective gadgets to enhance the coverage of wireless communication networks. Combining these two emerging technologies, the RIS-outfitted UAV (RISoUAV) is a promising solution for providing line-of-sight (LoS) wireless links for mobile targets (MTs) in obstructed high-dense urban areas. In this light, high-speed real-time communication is essential for some vital municipal services like ambulances, fire engines, security guards, police, etc. This important goal is achievable thanks to the RISoUAV-assisted 5G/quasi-optic wireless communication. This paper develops a framework for optimal navigation of a team of RISoUAVs for maintaining LoS links with a team of ground vehicles in a dense urban area. The trajectories of the RISoUAVs are optimized considering the energy efficiency, communication channel gains, and constraints associated with RISoUAVs motion and LoS service. A consensus-based coordinating approach is adopted to coordinate the RISoUAVs navigation to cover all MTs under a good quality of service. Simulation results show the effectiveness of the method. Note to Practitioners—In this paper, we consider a scenario where vehicles need to have high-speed, uninterrupted data links in obstructed, highly dense urban environments. Due to spectrum crunch, the data links are increasingly likely to rely on a high-frequency spectrum, including mmWave with quasi-optic nature, visible light communications, or even laser. However, the obstructed LoS and propagation are critical issues with the 5G and beyond as they rely on the availability of an unobstructed path (e.g., the LoS or a quality reflective path). On the other hand, the RIS performs as a passive reflective element that provides an indirect LoS link, a one-bounce channel, to improve the performance and efficiency of mmWave, and beyond, wireless communication networks. UAVs equipped with RISs are suggested in this paper to be adopted as aerial transponders to reflect signals and facilitate communication in high-density environments. Therefore, the problem of UAV navigation and 3D trajectory planning should be addressed regarding the application, particularly, for providing LoS service for mobile vehicles with arbitrary directions. Autonomous navigation of RISoUAVs for LoS wireless communication is a natural multi-dimensional extension of autonomous navigation with obstacle avoidance where regions in which LoS communication is lost are viewed as obstacles to avoid. However, the environment and valid LoS links can change dynamically due to moving vehicles in the obstructed environment. This makes the navigation design an NP-hard problem that is tackled in this paper by developing an effective navigation program.

Diversity of greenspace design and management impacts pollinator communities in a densely urbanized landscape: the city of Paris, France

The response of insect pollinator communities to increasing urbanization is shaped by landscape and local factors. But what about habitats that are already highly artificial? We investigated the drivers of pollinator diversity in a dense urban matrix, the city of Paris. We monitored insect pollinator communities monthly (March-October) for two consecutive years in 12 green spaces that differed in their management practices, focusing on four insect orders (Hymenoptera, Diptera, Lepidoptera, Coleoptera). Pollinator abundance and species richness were both positively tied to green space size and flowering plant species richness, but negatively linked to surrounding impervious surfaces. In addition, environmental features at both the local and landscape scales influenced the composition and functional diversity of wild bee communities. Indeed, small and large bees responded differently, with the occurrence of large-bodied species being impaired by the proportion of impervious surfaces but strongly enhanced by plant species richness. Also, sites with a majority of spontaneous plant species had more functionally diverse bee communities, with oligolectic species more likely to be found.These results, consistent with the literature, can guide the design and management practices of urban green spaces to promote pollinator diversity and pollination function, even in dense urban environments.

Stakeholder Perspectives on Data-Driven Solutions to Address Cardiovascular Disease and Health Equity in New York City

There is growing recognition of the importance of addressing the social determinants of health in efforts to improve health equity. In dense urban environments such as New York City, disparities in chronic health conditions (e.g., cardiovascular disease) closely mimic inequities in social factors such as income, education, and housing. Although there is a wealth of data on these social factors in New York City, little is known about how to rapidly use available data sources to address health disparities. Semistructured interviews were conducted with key stakeholders (N=11) from across the public health landscape in New York City (health departments, healthcare delivery systems, and community-based organizations) to assess perspectives on how social determinants of health data can be used to address cardiovascular disease and health equity, what data-driven tools would be useful, and challenges to using these data sources and developing tools. A matrix analysis approach was used to analyze the interview data. Stakeholders were optimistic about using social determinants of health data to address health equity by delivering holistic care, connecting people with additional resources, and increasing investments in under-resourced communities. However, interviewees noted challenges related to the quality and timeliness of social determinants of health data, interoperability between data systems, and lack of consistent metrics related to cardiovascular disease and health equity. Future research on this topic should focus on mitigating the barriers to using social determinants of health data, which includes incorporating social determinants of health data from other sectors. There is also a need to assess how data-driven solutions can be implemented within and across communities and organizations.

RIS-aided mmWave beam-forming for two-way communications of multiple pairs

Millimeter-wave (mmWave) communications is a key enabler towards realizing enhanced Mobile Broadband (eMBB) as a key promise of 5G and beyond, due to the abundance of bandwidth available at mmWave bands. An mmWave coverage map consists of blind spots due to shadowing and fading especially in dense urban environments. Beam-forming employing massive MIMO is primarily used to address high attenuation in the mmWave channel. Due to their ability in manipulating the impinging electromagnetic waves in an energy-efficient fashion, Reconfigurable Intelligent Surfaces (RISs) are considered a great match to complement the massive MIMO systems in realizing the beam-forming task and therefore effectively filling in the mmWave coverage gap. In this paper, we propose a novel RIS architecture, namely RIS-UPA where the RIS elements are arranged in a Uniform Planar Array (UPA). We show how RIS-UPA can be used in an RIS-aided MIMO system to fill the coverage gap in mmWave by forming beams of a custom footprint, with optimized main lobe gain, minimum leakage, and fairly sharp edges. Further, we propose a configuration for RIS-UPA that can support multiple two-way communication pairs, simultaneously. We theoretically obtain closed-form low-complexity solutions for our design and validate our theoretical findings by extensive numerical experiments.

Experimental investigation of a multilayer detention roof for stormwater management

This study aimed to evaluate the technical feasibility of a multilayer detention roof, namely a purple roof, in managing urban stormwater. A purple roof is conceptually and technically different from a green roof in that the former includes a low-transmissivity drainage layer and a void layer that can be designed at various depths for the temporary storage and slow release of water. Three types of roofs, i.e., (i) traditional, (ii) green and (iii) purple, were constructed in Western Sydney, Australia. These roofs were investigated and compared in terms of runoff reduction capacity, time to start runoff and time to release the runoff. Data were collected across the period from April 2021 to May 2022. A total of 76 rainfall events were recorded during this period. It was found that the purple roof performed better than other roof systems during all the rainfall events. The purple roof delayed the median start times of runoff by 773, 211 and 86 min for small, medium and large rainfall events, respectively, compared to a traditional roof, and 110, 59 and 14 min, respectively, compared to a green roof. During small rainfall events, the purple roof retained 100% of the water on most occasions. For medium, large, and extremely large events, the median runoff volume reductions by the purple roof were 88%, 34% and 7%, and 55%, 21% and 10% than those of the traditional and green roofs, respectively. In addition to reducing the volume discharged, the purple roof took 242 and 113 min (median values) longer to discharge the stormwater compared to the traditional roof during medium and large events, respectively, and 226 and 66 min (median values) longer than the green roof. In the case of median times for extremely large events, the purple roof took 503 min longer to release stormwater than the traditional roof, and 74 min longer than the green roof. The outcomes from this study proved the technical feasibility of the purple roof technology to slow the release and reduce the volume of stormwater during different-sized rainfall events. Thus, a purple roof can potentially be used to replace the traditional detention basins in a dense urban environment to reduce flood risks.