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Ye Y, Zhong C, Suel E. Unpacking the perceived cycling safety of road environment using street view imagery and cycle accident data. ACCIDENT; ANALYSIS AND PREVENTION 2024; 205:107677. [PMID: 38924963 DOI: 10.1016/j.aap.2024.107677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 04/22/2024] [Accepted: 06/10/2024] [Indexed: 06/28/2024]
Abstract
Cycling, as a routine mode of travel, offers significant benefits in promoting health, eliminating emissions, and alleviating traffic congestion. Many cities, including London, have introduced various policies and measures to promote 'active travel' in view of its manifold advantages. Nevertheless, the reality is not as desirable as expected. Existing studies suggest that cyclists' perceptions of cycling safety significantly hinder the broader adoption of cycling. Our study investigates the perceived cycling safety and unpacks the association between the cycling safety level and the road environment, taking London as a case study. First, we proposed novel cycling safety level indicators that incorporate both collision and injury risks, based on which a tri-tiered cycling safety level prediction spanning the entirety of London's road network has been generated with good accuracy. Second, we assessed the road environment by harnessing imagery features of street view reflecting the cyclist's perception of space and combined it with road features of cycle accident sites. Finally, associations between road environment features and cycling safety levels have been explained using SHAP values, leading to tailored policy recommendations. Our research has identified several key factors that contribute to a risky environment for cycling. Among these, the "second road effects," which refers to roads intersecting with the road where the accident occurred, is the most critical to cycling safety levels. This would also support and further contribute to the literature on road safety. Other results related to road greenery, speed limits, etc, are also discussed in detail. In summary, our study offers insights into urban design and transport planning, emphasising the perceived cycling safety of road environment.
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Affiliation(s)
- Ying Ye
- Centre for Advanced Spatial Analysis, University College London, London WC1E 6BT, UK
| | - Chen Zhong
- Centre for Advanced Spatial Analysis, University College London, London WC1E 6BT, UK.
| | - Esra Suel
- Centre for Advanced Spatial Analysis, University College London, London WC1E 6BT, UK
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Arcaute E, Ramasco JJ. Recent advances in urban system science: Models and data. PLoS One 2022; 17:e0272863. [PMID: 35976953 PMCID: PMC9384974 DOI: 10.1371/journal.pone.0272863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Cities are characterized by the presence of a dense population with a high potential for interactions between individuals of diverse backgrounds. They appear in parallel to the Neolithic revolution a few millennia ago. The advantages brought in terms of agglomeration for economy, innovation, social and cultural advancements have kept them as a major landmark in recent human history. There are many different aspects to study in urban systems from a scientific point of view, one can concentrate in demography and population evolution, mobility, economic output, land use and urban planning, home accessibility and real estate market, energy and water consumption, waste processing, health, education, integration of minorities, just to name a few. In the last decade, the introduction of communication and information technologies have enormously facilitated the collection of datasets on these and other questions, making possible a more quantitative approach to city science. All these topics have been addressed in many works in the literature, and we do not intend to offer here a systematic review. Instead, we will only provide a brief taste of some of these above-mentioned aspects, which could serve as an introduction to the collection ‘Cities as Complex Systems’. Such a non-systematic view will lead us to leave outside many relevant papers, and for this we must apologise.
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Affiliation(s)
- Elsa Arcaute
- Centre for Advanced Spatial Analysis, University College London, London, United Kingdom
- * E-mail: (EA); (JJR)
| | - José J. Ramasco
- Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB), Campus UIB, Palma de Mallorca, Spain
- * E-mail: (EA); (JJR)
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Xue J, Jiang N, Liang S, Pang Q, Yabe T, Ukkusuri SV, Ma J. Quantifying the spatial homogeneity of urban road networks via graph neural networks. NAT MACH INTELL 2022. [DOI: 10.1038/s42256-022-00462-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Huynh HN. Spatial point pattern and urban morphology: Perspectives from entropy, complexity, and networks. Phys Rev E 2019; 100:022320. [PMID: 31574778 DOI: 10.1103/physreve.100.022320] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Indexed: 11/07/2022]
Abstract
Spatial organization of physical form of an urban system, or city, both manifests and influences the way its social form functions. Mathematical quantification of the spatial pattern of a city is, therefore, important for understanding various aspects of the system. In this work, a framework to characterize the spatial pattern of urban locations based on the idea of entropy maximization is proposed. Three spatial length scales in the system with discerning interpretations in terms of the spatial arrangement of the locations are calculated. Using these length scales, two quantities are introduced to quantify the system's spatial pattern, namely, mass decoherence and space decoherence, whose combination enables the comparison of different cities in the world. The comparison reveals different types of urban morphology that could be attributed to the cities' geographical background and development status.
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Affiliation(s)
- Hoai Nguyen Huynh
- Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore
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Mitochondrial network complexity emerges from fission/fusion dynamics. Sci Rep 2018; 8:363. [PMID: 29321534 PMCID: PMC5762699 DOI: 10.1038/s41598-017-18351-5] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2016] [Accepted: 12/06/2017] [Indexed: 12/03/2022] Open
Abstract
Mitochondrial networks exhibit a variety of complex behaviors, including coordinated cell-wide oscillations of energy states as well as a phase transition (depolarization) in response to oxidative stress. Since functional and structural properties are often interwinded, here we characterized the structure of mitochondrial networks in mouse embryonic fibroblasts using network tools and percolation theory. Subsequently we perturbed the system either by promoting the fusion of mitochondrial segments or by inducing mitochondrial fission. Quantitative analysis of mitochondrial clusters revealed that structural parameters of healthy mitochondria laid in between the extremes of highly fragmented and completely fusioned networks. We confirmed our results by contrasting our empirical findings with the predictions of a recently described computational model of mitochondrial network emergence based on fission-fusion kinetics. Altogether these results offer not only an objective methodology to parametrize the complexity of this organelle but also support the idea that mitochondrial networks behave as critical systems and undergo structural phase transitions.
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Makarov VV, Hramov AE, Kirsanov DV, Maksimenko VA, Goremyko MV, Ivanov AV, Yashkov IA, Boccaletti S. Interplay between geo-population factors and hierarchy of cities in multilayer urban networks. Sci Rep 2017; 7:17246. [PMID: 29222518 PMCID: PMC5722944 DOI: 10.1038/s41598-017-17576-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2017] [Accepted: 11/28/2017] [Indexed: 11/29/2022] Open
Abstract
Only taking into consideration the interplay between processes occurring at different levels of a country can provide the complete social and geopolitical plot of its urban system. We study the interaction of the administrative structure and the geographical connectivity between cities with the help of a multiplex network approach. We found that a spatially-distributed geo-network imposes its own ranking to the hierarchical administrative network, while the latter redistributes the shortest paths between nodes in the geographical layer. Using both real demographic data of population censuses of the Republic of Kazakhstan and theoretical models, we show that in a country-scale urban network and for each specific city, the geographical neighbouring with highly populated areas is more important than its political setting. Furthermore, the structure of political subordination is instead crucial for the wealth of transportation network and communication between populated regions of the country.
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Affiliation(s)
- Vladimir V Makarov
- REC 'Artificial Intelligence Systems and Neurotechnologies', Yuri Gagarin State Technical University of Saratov, Polytechnicheskaja str 77, Saratov, 410054, Russia
- Institute of Energy and Transport Systems, Yurij Gagarin State Technical University of Saratov, Polytechnicheskaja str 77, Saratov, 410054, Russia
| | - Alexander E Hramov
- REC 'Artificial Intelligence Systems and Neurotechnologies', Yuri Gagarin State Technical University of Saratov, Polytechnicheskaja str 77, Saratov, 410054, Russia.
- Department of Automation, Control and Mechatronics, Yurij Gagarin State Technical University of Saratov, Polytechnicheskaja str 77, Saratov, 410054, Russia.
| | - Daniil V Kirsanov
- REC 'Artificial Intelligence Systems and Neurotechnologies', Yuri Gagarin State Technical University of Saratov, Polytechnicheskaja str 77, Saratov, 410054, Russia
- Department of Automation, Control and Mechatronics, Yurij Gagarin State Technical University of Saratov, Polytechnicheskaja str 77, Saratov, 410054, Russia
| | - Vladimir A Maksimenko
- REC 'Artificial Intelligence Systems and Neurotechnologies', Yuri Gagarin State Technical University of Saratov, Polytechnicheskaja str 77, Saratov, 410054, Russia
- Department of Automation, Control and Mechatronics, Yurij Gagarin State Technical University of Saratov, Polytechnicheskaja str 77, Saratov, 410054, Russia
| | - Mikhail V Goremyko
- REC 'Artificial Intelligence Systems and Neurotechnologies', Yuri Gagarin State Technical University of Saratov, Polytechnicheskaja str 77, Saratov, 410054, Russia
| | - Alexey V Ivanov
- Institute of Urban Studies, Architecture and Construction, Yurij Gagarin State Technical University of Saratov, Polytechnicheskaja str 77, Saratov, 410054, Russia
| | - Ivan A Yashkov
- Institute of Urban Studies, Architecture and Construction, Yurij Gagarin State Technical University of Saratov, Polytechnicheskaja str 77, Saratov, 410054, Russia
| | - Stefano Boccaletti
- CNR-Institute of Complex Systems, Via Madonna del Piano 10, 50019, Sesto Fiorentino, Florence, Italy
- The Italian Embassy in Israel, 25 Hamered Street, 68125, Tel Aviv, Israel
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