Voice-assisted digital maps have become mainstream navigation aids for pedestrian navigation. Although these maps are widely studied and applied, it is still unclear how they affect human behavior ...and spatial knowledge acquisition. In this study, we recruited thirty-three college students to carry out an outdoor wayfinding experiment. We compared the effects of voice-assisted digital maps with those of digital maps without voice instructions and paper maps by using eye tracking, sketch maps, questionnaires and interviews. The results show that, compared to the other map types, voice-assisted digital maps can help users reach their destinations more quickly and pay more attention to moving objects, thereby increasing the comfort levels of participants. However, the efficiency of voice-assisted maps on route memory tasks does not rival that of paper maps. Overall, the use of voice-assisted digital maps saves time but may reduce pedestrians' spatial knowledge acquisition. The results of this study reveal the influence of voice on pedestrian wayfinding and deepen the scientific understanding of the multimedia navigation mode in shaping human spatial ability.
Active school travel (AST) is influenced by multiple factors including built and social environments, households and individual variables. A holistic theory such as Mitra's Behavioural Model of ...School Transportation (BMST) is vital to comprehensively understand these complex interrelationships. This study aimed to assess direct and indirect associations between children's AST and environmental, household and child factors based on the BMST using structural equation modelling (SEM).
Data were drawn from Neighbourhoods for Active Kids (NfAK), a cross-sectional study of 1102 children aged 8-13 years (school years 5-8) and their parents from nine intermediate and 10 primary schools in Auckland, New Zealand between February 2015 and December 2016. Data were collected using an online participatory mapping survey (softGIS) with children, a computer-assisted telephone interviewing survey (CATI) with parents, and ArcGIS for built environment attributes. Based on the BMST a conceptual model of children's school travel behaviour was specified for SEM analyses ('hypothesised SEM'), and model modification was made to improve the model ('modified SEM'). SEM analyses using Mplus were performed to test the hypothesised/modified SEM and to assess direct and indirect relationships among variables.
The overall fit of the modified SEM was acceptable (N = 542; Root mean square error of approximation = 0.04, Comparative fit index = 0.94, Tucker-Lewis index = 0.92). AST was positively associated with child independent mobility, child-perceived neighbourhood safety, and parent-perceived importance of social interaction and neighbourhood social environment. Distance to school, and parental perceptions of convenience and concerns about traffic safety were negatively associated with AST. Parental fears of stranger danger were indirectly related to AST through those of traffic safety. Distance to school and child independent mobility mediated relationships between AST and child school year and sex.
Increasing children's AST requires action on multiple fronts including communities that support independent mobility by providing child friendly social and built environments, safety from traffic, and policies that promote local schools and safe vehicle-free zones around school.
Operational global-scale hydrological forecasting systems are used
to help manage hydrological extremes such as floods and droughts. The vast
amounts of raw data that underpin forecast systems and ...the ability to
generate information on forecast skill have, until now, not been publicly
available. As part of the Global Flood Awareness System (GloFAS; https://www.globalfloods.eu/, last access: 3 December 2022) service evolution, in this paper daily ensemble river discharge reforecasts and real-time forecast datasets are made free and openly available through the Copernicus Climate Change Service (C3S) Climate Data Store (CDS). They include real-time forecast data starting on 1 January 2020 updated operationally every day and a 20-year set of reforecasts and associated metadata. This paper describes the model components and configuration used to generate the real-time river discharge forecasts and the reforecasts. An evaluation of ensemble forecast skill using the continuous ranked probability skill score (CRPSS) was also undertaken for river points around the globe. Results show that GloFAS is skilful in over 93 % of catchments in the short (1 to 3 d) and medium range (5 to 15 d) against a persistence benchmark forecast and skilful in over 80 % of catchments out to the extended range (16 to 30 d) against a climatological benchmark forecast. However, the strength of skill varies considerably by location with GloFAS found to have no or negative skill at longer lead times in broad hydroclimatic regions in tropical Africa, western coast of South America, and catchments dominated by snow and ice in high northern latitudes. Forecast skill is summarised as a new headline skill score available as a new layer on the GloFAS forecast Web Map Viewer to aid user interpretation and understanding of forecast quality.
Road traffic congestion continues to manifest and propagate in cities around the world. The recent technological advancements in intelligent traveler information have a strong influence on the route ...choice behavior of drivers by enabling them to be more flexible in selecting their routes. Measuring traffic congestion in a city, understanding its spatial dispersion, and investigating whether the congestion patterns are stable (temporally, such as on a day-to-day basis) are critical to developing effective traffic management strategies. In this study, with the help of Google Maps API, we gather traffic speed data of 29 cities across the world over a 40-day period. We present generalized congestion and network stability metrics to compare congestion levels between these cities. We find that (a) traffic congestion is related to macroeconomic characteristics such as per capita income and population density of these cities, (b) congestion patterns are mostly stable on a day-to-day basis, and (c) the rate of spatial dispersion of congestion is smaller in congested cities, i.e. the spatial heterogeneity is less sensitive to increase in delays. This study compares the traffic conditions across global cities on a common datum using crowdsourced data which is becoming readily available for research purposes. This information can potentially assist practitioners to tailor macroscopic network congestion and reliability management policies. The comparison of different cities can also lead to benchmarking and standardization of the policies that have been used to date.
Evolving individual, contextual, organizational, interactional and sociocultural factors have complicated efforts to shape the professional identity formation (PIF) of medical students or how they ...feel, act and think as professionals. However, an almost exclusive reliance on online learning during the COVID-19 pandemic offers a unique opportunity to study the elemental structures that shape PIF and the environmental factors nurturing it. We propose two independent Systematic Evidence-Based Approach guided systematic scoping reviews (SSR in SEBA)s to map accounts of online learning environment and netiquette that structure online programs. The data accrued was analysed using the clinically evidenced Krishna-Pisupati Model of Professional Identity Formation (KPM) to study the evolving concepts of professional identity. The results of each SSR in SEBA were evaluated separately with the themes and categories identified in the Split Approach combined to create richer and deeper 'themes/categories' using the Jigsaw Perspective. The 'themes/categories' from each review were combined using the Funnelling Process to create domains that guide the discussion. The 'themes/categories' identified from the 141 included full-text articles in the SSR in SEBA of online programs were the content and effects of online programs. The themes/categories identified from the 26 included articles in the SSR in SEBA of netiquette were guidelines, contributing factors, and implications. The Funnelling Process identified online programs (encapsulating the content, approach, structures and the support mechanisms); their effects; and PIF development that framed the domains guiding the discussion. This SSR in SEBA identifies the fundamental elements behind developing PIF including a structured program within a nurturing environment confined with netiquette-guided boundaries akin to a Community of Practice and the elemental aspect of a socialisation process within online programs. These findings ought to be applicable beyond online training and guide the design, support and assessment of efforts to nurture PIF.
This study aims to confirm the usefulness of adaptation of proactive braking intervention systems to the risk level of the driving environment for improving the reactive factors of acceptability. ...First, we develop prototypes of adaptive proactive braking intervention systems around non-signalized intersections on community roads. Then, to confirm the effectiveness of adaptation, we conduct user tests, in which 45 elderly drivers participate, on public roads. From comparisons between constant setting and adaptive setting, we confirm that the adaptive setting improves the reactive factors of acceptability, such as reduction in the feeling of impatience and strangeness.
Twitter location inference methods are developed with the purpose of increasing the percentage of geotagged tweets by inferring locations on a non-geotagged dataset. For validation of proposed ...approaches, these location inference methods are developed on a fully geotagged dataset on which the attached Global Navigation Satellite System coordinates are used as ground truth data. Whilst a substantial number of location inference methods have been developed to date, questions arise pertaining the generalizability of the developed location inference models on a non-geotagged dataset. This paper proposes a high precision location inference method for inferring tweets' point of origin based on location mentions within the tweet text. We investigate the influence of data selection by comparing the model performance on two datasets. For the first dataset, we use a proportionate sample of tweet sources of a geotagged dataset. For the second dataset, we use a modelled distribution of tweet sources following a non-geotagged dataset. Our results showed that the distribution of tweet sources influences the performance of location inference models. Using the first dataset we outweighed state-of-the-art location extraction models by inferring 61.9%, 86.1% and 92.1% of the extracted locations within 1 km, 10 km and 50 km radius values, respectively. However, using the second dataset our precision values dropped to 45.3%, 73.1% and 81.0% for the same radius values.
This study focuses on the recently emerged Internet of Vehicles (IoV) concept to provide an integrated agricultural vehicle/machinery tracking system through two leading low power wide area network ...(LPWAN) technologies, namely LoRa and NB-IoT. The main aim is to investigate the theoretical coverage limits by considering the urban, suburban, and rural environments. Two vehicle tracking units (VTUs) have been designed for LoRa and NB-IoT connectivity technologies that can be used as reference hardware in coverage analysis. On this basis, the closed-form explicit analytical expressions of the maximum transmission range have been derived using the Hata path loss model. Besides, the computer simulation results have been validated via the maps from XIRIO online radio planning tool. In light of the obtained findings, several evaluations have been made to enhance the LPWAN-based agricultural vehicle tracking feasibility in smart farms.
In the era of smartphones, route-planning and navigation is supported by freely and globally available web mapping services, such as OpenStreetMap or Google Maps. These services provide digital maps, ...as well as route planning functions that visually highlight the suggested route in the map. Additionally, such digital maps contain landmark pictograms, i.e. representations of salient objects in the environment. These landmark representations are, amongst other reference points, relevant for orientation, route memory, and the formation of a cognitive map of the environment. The amount of visible landmarks in maps used for navigation and route planning depends on the width of the displayed margin areas around the route. The amount of further reference points is based on the visual complexity of the map. This raises the question how factors like the distance of landmark representations to the route and visual map complexity determine the relevance of specific landmarks for memorizing a route. In order to answer this question, two experiments that investigated the relation between eye fixation patterns on landmark representations, landmark positions, route memory and visual map complexity were carried out. The results indicate that the attentional processing of landmark representations gradually decreases with an increasing distance to the route, decision points and potential decision points. Furthermore, this relation was found to be affected by the visual complexity of the map. In maps with low visual complexity, landmark representations further away from the route are fixated. However, route memory was not found to be affected by visual complexity of the map. We argue that map users might require a certain amount of reference points to form spatial relations as a foundation for a mental representation of space. As maps with low visual complexity offer less reference points, people need to scan a wider area. Therefore, visual complexity of the area displayed in a map should be considered in navigation-oriented map design by increasing displayed margins around the route in maps with a low visual complexity. In order to verify our assumption that the amount of reference points not only affects visual attention processes, but also the formation of a mental representation of space, additional research is required.
The Simultaneous Localization and Mapping (SLAM) technique has achieved astonishing progress over the last few decades and has generated considerable interest in the autonomous driving community. ...With its conceptual roots in navigation and mapping, SLAM outperforms some traditional positioning and localization techniques since it can support more reliable and robust localization, planning, and controlling to meet some key criteria for autonomous driving. In this study the authors first give an overview of the different SLAM implementation approaches and then discuss the applications of SLAM for autonomous driving with respect to different driving scenarios, vehicle system components and the characteristics of the SLAM approaches. The authors then discuss some challenging issues and current solutions when applying SLAM for autonomous driving. Some quantitative quality analysis means to evaluate the characteristics and performance of SLAM systems and to monitor the risk in SLAM estimation are reviewed. In addition, this study describes a real-world road test to demonstrate a multi-sensor-based modernized SLAM procedure for autonomous driving. The numerical results show that a high-precision 3D point cloud map can be generated by the SLAM procedure with the integration of Lidar and GNSS/INS. Online four–five cm accuracy localization solution can be achieved based on this pre-generated map and online Lidar scan matching with a tightly fused inertial system.
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