A System for Generating Customized Pleasant Pedestrian Routes Based on OpenStreetMap Data

Novack, Tessio; Wang, Zhiyong; Zipf, Alexander

doi:10.3390/s18113794

Cited by 55 publications

(28 citation statements)

References 45 publications

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“…To do this, the eligible preferences are the number of green areas, number of social places, noise of the streets and total length of the journey. Later, routes are calculated thanks to an algorithm based on weights and OMS [ 16 ]. This application does not consider the hours of the day when the query occurs, which could modify the routes to avoid dark places at night or very crowded places during the day.…”

Section: Introductionmentioning

confidence: 99%

Walking Secure: Safe Routing Planning Algorithm and Pedestrian’s Crossing Intention Detector Based on Fuzzy Logic App

Domínguez

Sanguino

2021

Sensors

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Improving road safety through artificial intelligence is now crucial to achieving more secure smart cities. With this objective, a mobile app based on the integration of the smartphone sensors and a fuzzy logic strategy to determine the pedestrian’s crossing intention around crosswalks is presented. The app developed also allows the calculation, tracing and guidance of safe routes thanks to an optimization algorithm that includes pedestrian areas on the paths generated over the whole city through a cloud database (i.e., zebra crossings, pedestrian streets and walkways). The experimentation carried out consisted in testing the fuzzy logic strategy with a total of 31 volunteers crossing and walking around a crosswalk. For that, the fuzzy logic approach was subjected to a total of 3120 samples generated by the volunteers. It has been proven that a smartphone can be successfully used as a crossing intention detector system with an accuracy of 98.63%, obtaining a true positive rate of 98.27% and a specificity of 99.39% according to a receiver operating characteristic analysis. Finally, a total of 30 routes were calculated by the proposed algorithm and compared with Google Maps considering the values of time, distance and safety along the routes. As a result, the routes generated by the proposed algorithm were safer than the routes obtained with Google Maps, achieving an increase in the use of safe pedestrian areas of at least 183%.

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Section: Introductionmentioning

confidence: 99%

Walking Secure: Safe Routing Planning Algorithm and Pedestrian’s Crossing Intention Detector Based on Fuzzy Logic App

Domínguez

Sanguino

2021

Sensors

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“…Besides, it may lead to an increase in the number of people appreciating these artworks beyond participants of street-art walking tours and users of related web and smart-phone applications. More concretely, a higher completeness of features representing graffiti artworks in open geo-datasets, like OSM, for example, might benefit applications for the generation of aesthetically pleasant pedestrian routes, such as the ones proposed by Quercia et al [46], Kachkaev et al [47] and, more recently, Novack et al [48]. However, automatizing the detection of graffiti artworks requires, besides access to the appropriate datasets, overcoming different technical challenges.…”

Section: Summary and Discussionmentioning

confidence: 99%

Towards Detecting Building Facades with Graffiti Artwork Based on Street View Images

Novack

Vorbeck

Lorei³

et al. 2020

IJGI

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As a recognized type of art, graffiti is a cultural asset and an important aspect of a city’s aesthetics. As such, graffiti is associated with social and commercial vibrancy and is known to attract tourists. However, positional uncertainty and incompleteness are current issues of open geo-datasets containing graffiti data. In this paper, we present an approach towards detecting building facades with graffiti artwork based on the automatic interpretation of images from Google Street View (GSV). It starts with the identification of geo-tagged photos of graffiti artwork posted on the photo sharing media Flickr. GSV images are then extracted from the surroundings of these photos and interpreted by a customized, i.e., transfer learned, convolutional neural network. The compass heading of the GSV images classified as containing graffiti artwork and the possible positions of their acquisition are considered for scoring building facades according to their potential of containing the artwork observable in the GSV images. More than 36,000 GSV images and 5000 facades from buildings represented in OpenStreetMap were processed and evaluated. Precision and recall rates were computed for different facade score thresholds. False-positive errors are caused mostly by advertisements and scribblings on the building facades as well as by movable objects containing graffiti artwork and obstructing the facades. However, considering higher scores as threshold for detecting facades containing graffiti leads to the perfect precision rate. Our approach can be applied for identifying previously unmapped graffiti artwork and for assisting map contributors interested in the topic. Furthermore, researchers interested on the spatial correlations between graffiti artwork and socio-economic factors can profit from our open-access code and results.

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“…However, we were not able to find the final version of this smartphone app on the Google Play Store. Likewise, Novack, et al [28] proposed a framework based on the OSM data to incorporate greenness, sociability, and quietness in a customized routing mapping system. This system allows users to find a route through the desired level of greenness, sociability, and quietness.…”

Section: Apps Categoriesmentioning

confidence: 99%

Allowing Users to Benefit from Tree Shading: Using a Smartphone App to Allow Adaptive Route Planning during Extreme Heat

Deilami

Rudner

Butt

et al. 2020

Forests

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This paper presents the outcomes from a joint research project that aims to develop a smartphone application/online platform to model the most thermally comfortable active transport route to a planned destination using heat information and tree shading (Shadeway). Here, we provide a summary of our systematic review of academic literature and applications from the Google Play and Apple App Store, to identify current knowledge about personal adaptation strategies when navigating travel in cities during high temperatures. The review identifies that there is a lack of attention regarding the use of smartphone applications to address urban thermal comfort for active transport by government and private industry. We then present the initial results of original research from three community focus groups and an online survey that elicited participants’ opinions about Shadeways in the City of Greater Bendigo (CoGB), Australia. The results clearly show the need for better management of Shadeways in CoGB. For example, 52.3% of the routes traveled by participants suffer from either no or poor levels of shading, and 53 of the shaded areas were located along routes that also experience heavy traffic, which can have an adverse effect on perceptions and actual safety. It is expected that this study will contribute to improve understanding of the methods used to identify adaptation strategies to increasingly extreme temperatures.

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A System for Generating Customized Pleasant Pedestrian Routes Based on OpenStreetMap Data

Cited by 55 publications

References 45 publications

Walking Secure: Safe Routing Planning Algorithm and Pedestrian’s Crossing Intention Detector Based on Fuzzy Logic App

Walking Secure: Safe Routing Planning Algorithm and Pedestrian’s Crossing Intention Detector Based on Fuzzy Logic App

Towards Detecting Building Facades with Graffiti Artwork Based on Street View Images

Allowing Users to Benefit from Tree Shading: Using a Smartphone App to Allow Adaptive Route Planning during Extreme Heat

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