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Indoor evacuation efficiency heavily relies on the connectivity status of navigation networks. During disastrous situations, the spreading of hazards (e.g., fires, plumes) significantly influences indoor navigation networks’ status. Nevertheless, current research concentrates on utilizing classical statistical methods to analyze this status and lacks the flexibility to evaluate the increasingly disastrous scope’s influence. We propose an evaluation method combining 3D spatial geometric distance and topology for emergency evacuations to address this issue. Within this method, we offer a set of indices to describe the nodes’ status and the entire network under emergencies. These indices can help emergency responders quickly identify vulnerable nodes and areas in the network, facilitating the generation of evacuation plans and improving evacuation efficiency. We apply this method to analyze the fire evacuation efficiency and resilience of two experiment buildings’ indoor networks. Experimental results show a strong influence on the network’s spatial connectivity on the evacuation efficiency under disaster situations.
Lei Niu; Zhiyong Wang; Yiquan Song; Yi Li. An Evaluation Model for Analyzing Robustness and Spatial Closeness of 3D Indoor Evacuation Networks. ISPRS International Journal of Geo-Information 2021, 10, 331 .
AMA StyleLei Niu, Zhiyong Wang, Yiquan Song, Yi Li. An Evaluation Model for Analyzing Robustness and Spatial Closeness of 3D Indoor Evacuation Networks. ISPRS International Journal of Geo-Information. 2021; 10 (5):331.
Chicago/Turabian StyleLei Niu; Zhiyong Wang; Yiquan Song; Yi Li. 2021. "An Evaluation Model for Analyzing Robustness and Spatial Closeness of 3D Indoor Evacuation Networks." ISPRS International Journal of Geo-Information 10, no. 5: 331.
Background Walking is a good and simple way to increase people's energy expenditure, but there is limited evidence whether the neighborhood environment correlates differently with recreational and transportation walking. AimTo investigate how recreational walking and transportation walking are associated with the natural and built environmental characteristics of the living environment in the Netherlands, and examine the differences in their associations between weekdays and weekends. Method and data We extracted the total duration of daily walking (in minutes per person) for recreation and transportation of adults aged 18 years and above from the Dutch National Travel Survey 2015–2017 (N = 65,785) and analyzed it as an outcome variable. Objective measures of the natural (i.e., normalized difference vegetation index (NDVI), blue space and meteorological conditions) and built environment (i.e., crossing density, land-use mix, and residential building density) around respondents' home addresses were determined for buffers with 300, 600, and 1000 m radii using a geographic information system. To assess associations between recreational and transportation walking and the environmental exposures separately, we fitted Tobit regression models to the walking data, adjusted for multiple confounders. ResultsOn weekdays, people living in areas with less NDVI, higher land-use mix, and higher crossing density were more likely to engage in transportation walking. Recreational walking was negatively associated with NDVI, blue space, crossing density, precipitation and daily average temperature. At weekends, land-use mix supports both recreational and transportation walking. A negative association appeared for NDVI and transportation walking. Daily average rainfall and temperature were inversely correlated with recreational walking. Sensitivity tests indicated that some associations depend on the buffer size. ConclusionsOur findings suggest that the built and natural environments are differently associated with people's recreational and transportation walking. We also found differences in the walking-environment associations between weekdays and weekends. Place-based policies to design walking-friendly neighborhoods may have different implications for different types of walking.
Zhiyong Wang; Dick Ettema; Marco Helbich. Objective environmental exposures correlate differently with recreational and transportation walking: A cross-sectional national study in the Netherlands. Environmental Research 2020, 194, 110591 .
AMA StyleZhiyong Wang, Dick Ettema, Marco Helbich. Objective environmental exposures correlate differently with recreational and transportation walking: A cross-sectional national study in the Netherlands. Environmental Research. 2020; 194 ():110591.
Chicago/Turabian StyleZhiyong Wang; Dick Ettema; Marco Helbich. 2020. "Objective environmental exposures correlate differently with recreational and transportation walking: A cross-sectional national study in the Netherlands." Environmental Research 194, no. : 110591.
Traffic congestion is a major issue in most big cities, resulting in longer travel time and increased greenhouse gas emission. Various factors can cause traffic congestion, and includes not only traffic events on roads (e.g., car accidents) but also urban events (e.g., football games, concerts, and festivals), where a large number of human activities happen in a certain place and at a certain time. The technology of connected vehicles (CV) has provided a crowd-souring platform enabling communication between vehicles and surrounding information share to be more timely and effective. Taking the advantage of that, in this paper we focus on navigation during urban events, and present an approach to find feasible routes avoiding traffic congestion caused by the different types of events. Using 12-month geo-tagged tweets, we create a human activity network to capture certain types of human activities across cities. Based on that, an event estimation algorithm is developed to find the possible events that would occur in the near future, and to estimate their probabilities. These detected events are represented in the form of obstacle polygons with timestamps, and are used by the routing algorithm to generate congestion avoidance routes. We apply our approach to the road network of Toronto, Ontario, Canada, and the experimental results show the capability of our approach in supporting routing during urban events.
Zhiyong Wang; Wei Huang. A Social Media Based Approach for Route Planning During Urban Events. IEEE Access 2020, 8, 207589 -207598.
AMA StyleZhiyong Wang, Wei Huang. A Social Media Based Approach for Route Planning During Urban Events. IEEE Access. 2020; 8 ():207589-207598.
Chicago/Turabian StyleZhiyong Wang; Wei Huang. 2020. "A Social Media Based Approach for Route Planning During Urban Events." IEEE Access 8, no. : 207589-207598.
Post-disaster recovery involves interdependent processes of physical and psychological rehabilitations. Over the past few years, researchers have explored geotagged social media data to assist the planning, monitoring, and assessment of the post-disaster recovery of tourism destinations, given its advantages over traditional approaches. Nonetheless, recent studies have mostly focused on quantitatively accessing the physical elements of post-disaster recovery (e.g., infrastructure reconstruction and re-influx of tourists). Few studies have explored people's sentiments and perspectives over the process of post-disaster recovery. In this study, a mixed methods approach involving sentiment analysis and Latent Dirichlet allocation (LDA) topic modeling is designed for mining sheer volume of tweets about Lombok and Bali, generated by nonlocal Twitter users after a series of earthquakes in the two places in August 2018. The findings mainly suggest that people have generally become less negative about Lombok and Bali over time, despite fluctuations in their sentiment polarities' central tendencies. In addition, dissatisfactions about the housing reconstruction progress, tourism recovery status, and living conditions in the affected areas of Lombok still existed in 2019; contestations have been found with regard to the huge funds for hosting the 2018 Bali IMF-World Bank meeting after the earthquakes. The overall results of this study have proved that the adopted approach can effectively reveal the variations of people's sentiments and perspectives of general and specific issues regarding post-disaster tourism recovery over time.
Yingwei Yan; Jingfu Chen; Zhiyong Wang. Mining public sentiments and perspectives from geotagged social media data for appraising the post-earthquake recovery of tourism destinations. Applied Geography 2020, 123, 102306 .
AMA StyleYingwei Yan, Jingfu Chen, Zhiyong Wang. Mining public sentiments and perspectives from geotagged social media data for appraising the post-earthquake recovery of tourism destinations. Applied Geography. 2020; 123 ():102306.
Chicago/Turabian StyleYingwei Yan; Jingfu Chen; Zhiyong Wang. 2020. "Mining public sentiments and perspectives from geotagged social media data for appraising the post-earthquake recovery of tourism destinations." Applied Geography 123, no. : 102306.
Background Walking is a good and simple way to increase people’s energy expenditure, but there is limited evidence whether the neighborhood environment correlates differently with recreational and transportation walking. Aim To investigate how recreational walking and transportation walking are associated with the natural and built environmental characteristics of the living environment in the Netherlands, and examine the differences in their associations between weekdays and weekends. Method and data We extracted the total duration of daily walking (in minutes per person) for recreation and transport from the Dutch National Travel Survey 2015-2017 (N=66,880) and analyzed it as an outcome variable. Objective measures of the natural (i.e., Normalized Difference Vegetation Index (NDVI) and meteorological conditions) and built environment (i.e., crossing density, land-use mix, and residential building density) around respondents’ home addresses were determined for buffers with 300, 600, and 1,000 m radii using a geographic information system. To assess associations between recreational and transport walking and the environmental exposures separately, we fitted Tobit regression models to the walking data, adjusted for multiple confounders. Results On weekdays, people living in areas with less NDVI, higher land-use mix, higher residential building density, and higher crossing density were more likely to engage in transportation walking. While recreational walking was negatively associated with NDVI, crossing density, precipitation, and daily average temperature, it was positively associated with residential building density. At weekends, land-use mix supports both recreational and transportation walking. A negative association appeared for NDVI and transportation walking. Daily average rainfall and temperature were inversely correlated with recreational walking. Sensitivity tests indicated that some associations depend on the buffer size. Conclusions Our findings suggest that the built and natural environments have different impacts on people’s recreational and transportation walking. We also found differences in the walking–environment associations between weekdays and weekends. Place-based policies to design walking-friendly neighborhoods may have different implications for different types of walking.
Zhiyong Wang; Dick Ettema; Marco Helbich. Objective environmental exposures correlate differently with recreational and transportation walking: A cross-sectional national study in the Netherlands. 2020, 1 .
AMA StyleZhiyong Wang, Dick Ettema, Marco Helbich. Objective environmental exposures correlate differently with recreational and transportation walking: A cross-sectional national study in the Netherlands. . 2020; ():1.
Chicago/Turabian StyleZhiyong Wang; Dick Ettema; Marco Helbich. 2020. "Objective environmental exposures correlate differently with recreational and transportation walking: A cross-sectional national study in the Netherlands." , no. : 1.
Noise pollution is one of the main stressors in urban environments, having negative impacts on people's quality of life and health. For some groups of citizens, such as school children, patients, and elders, there is a need to support them in finding pedestrian routes in noise polluted areas of cities. In this paper, we focus on the estimation of traffic noise, and present an approach to provide quiet routing services, taking into account the estimated noise levels of roads. By combining Volunteered Geographic Information, official socio-economic data, and open-access GPS trajectory data, we develop a set of traffic related variables, and apply machine learning methods to perform traffic volume estimations. Given the estimated traffic information, an existing traffic noise model is then employed to derive the noise polluted areas. For generation of quiet routes, a new routing algorithm is proposed based on the Dijkstra algorithm. It minimizes the exposure of pedestrians to traffic noise pollution while taking into account the route distance constraint. We apply our quiet routing approach to the city of Heidelberg (Germany). The application results demonstrate the efficacy of our algorithms in the generation of quiet routes customized to pedestrian preferences.
Zhiyong Wang; Tessio Novack; Yingwei Yan; Alexander Zipf. Quiet Route Planning for Pedestrians in Traffic Noise Polluted Environments. IEEE Transactions on Intelligent Transportation Systems 2020, 1 -12.
AMA StyleZhiyong Wang, Tessio Novack, Yingwei Yan, Alexander Zipf. Quiet Route Planning for Pedestrians in Traffic Noise Polluted Environments. IEEE Transactions on Intelligent Transportation Systems. 2020; (99):1-12.
Chicago/Turabian StyleZhiyong Wang; Tessio Novack; Yingwei Yan; Alexander Zipf. 2020. "Quiet Route Planning for Pedestrians in Traffic Noise Polluted Environments." IEEE Transactions on Intelligent Transportation Systems , no. 99: 1-12.
Current indoor mapping approaches can detect accurate geometric information but are incapable of detecting the room type or dismiss this issue. This work investigates the feasibility of inferring the room type by using grammars based on geometric maps. Specifically, we take the research buildings at universities as examples and create a constrained attribute grammar to represent the spatial distribution characteristics of different room types as well as the topological relations among them. Based on the grammar, we propose a bottom-up approach to construct a parse forest and to infer the room type. During this process, Bayesian inference method is used to calculate the initial probability of belonging an enclosed room to a certain type given its geometric properties (e.g., area, length, and width) that are extracted from the geometric map. The approach was tested on 15 maps with 408 rooms. In 84% of cases, room types were defined correctly. It, to a certain degree, proves that grammars can benefit semantic enrichment (in particular, room type tagging).
Xuke Hu; Hongchao Fan; Alexey Noskov; Alexander Zipf; Zhiyong Wang; Jianga Shang. Feasibility of Using Grammars to Infer Room Semantics. Remote Sensing 2019, 11, 1535 .
AMA StyleXuke Hu, Hongchao Fan, Alexey Noskov, Alexander Zipf, Zhiyong Wang, Jianga Shang. Feasibility of Using Grammars to Infer Room Semantics. Remote Sensing. 2019; 11 (13):1535.
Chicago/Turabian StyleXuke Hu; Hongchao Fan; Alexey Noskov; Alexander Zipf; Zhiyong Wang; Jianga Shang. 2019. "Feasibility of Using Grammars to Infer Room Semantics." Remote Sensing 11, no. 13: 1535.
Determining safe and fast routes for first responders is an important issue in a disaster response. Especially when different types of disasters (e.g., toxic plumes, fires, and floods) occur and affect transportation networks simultaneously, special routing strategies (e.g., detour) would be needed to ensure the safety for responders. On the other hand, after disasters happen, a quick response time is required, and the responders should move as fast as possible and even go through certain obstacles to reach the disaster sites to deliver emergency services. In this paper, we study path planning through moving obstacles, taking into account the influence of obstacles on the status of road networks and the speed of rescue vehicles. A set of algorithms is proposed to deal with not only geometries but also the properties of moving obstacles to support route generation. Based on the Dijkstra algorithm, a new routing algorithm is designed and developed, which aims at minimizing the risk while constraining the travel time of routes. We validate our approach with a set of experiments on some navigation cases. The experimental results show the promise of the algorithm in the generation of feasible and safe routes for first responders to pass through moving obstacles.
Zhiyong Wang; Sisi Zlatanova. Safe Route Determination for First Responders in the Presence of Moving Obstacles. IEEE Transactions on Intelligent Transportation Systems 2019, 21, 1044 -1053.
AMA StyleZhiyong Wang, Sisi Zlatanova. Safe Route Determination for First Responders in the Presence of Moving Obstacles. IEEE Transactions on Intelligent Transportation Systems. 2019; 21 (3):1044-1053.
Chicago/Turabian StyleZhiyong Wang; Sisi Zlatanova. 2019. "Safe Route Determination for First Responders in the Presence of Moving Obstacles." IEEE Transactions on Intelligent Transportation Systems 21, no. 3: 1044-1053.
In this work, we present a system that generates customized pedestrian routes entirely based on data from OpenStreetMap (OSM). The system enables users to define to what extent they would like the route to have green areas (e.g., parks, squares, trees), social places (e.g., cafes, restaurants, shops) and quieter streets (i.e., with less road traffic). We present how the greenness, sociability, and quietness factors are defined and extracted from OSM as well as how they are integrated into a routing cost function. We intrinsically evaluate customized routes from one-thousand trips, i.e., origin–destination pairs, and observe that these are, in general, as we intended—slightly longer but significantly more social, greener, and quieter than the respective shortest routes. Based on a survey taken by 156 individuals, we also evaluate the system’s usefulness, usability, controlability, and transparency. The majority of the survey participants agree that the system is useful and easy to use and that it gives them the feeling of being in control regarding the extraction of routes in accordance with their greenness, sociability, and quietness preferences. The survey also provides valuable insights into users requirements and wishes regarding a tool for interactively generating customized pedestrian routes.
Tessio Novack; Zhiyong Wang; Alexander Zipf. A System for Generating Customized Pleasant Pedestrian Routes Based on OpenStreetMap Data. Sensors 2018, 18, 3794 .
AMA StyleTessio Novack, Zhiyong Wang, Alexander Zipf. A System for Generating Customized Pleasant Pedestrian Routes Based on OpenStreetMap Data. Sensors. 2018; 18 (11):3794.
Chicago/Turabian StyleTessio Novack; Zhiyong Wang; Alexander Zipf. 2018. "A System for Generating Customized Pleasant Pedestrian Routes Based on OpenStreetMap Data." Sensors 18, no. 11: 3794.
With a rapidly-growing volume of volunteered geographic information (VGI), there is an increasing trend towards using VGI to provide location-based services. In this study, we investigate using OpenStreetMap data to integrate indoor and outdoor route planning for pedestrians. To support indoor and outdoor route planning, in this paper, we focus on the connections inside buildings and propose a data model, which uses OSM primitives (nodes, ways and relations) and tags to capture horizontal and vertical indoor components, as well as the connection between indoor and outdoor environments. A set of new approaches is developed to support indoor modeling and mapping. Based on the proposed data model, we present a workflow that enables automatic generation of a routing graph and provide an algorithm to calculate integrated indoor-outdoor routes. We applied our data model to a set of test cases. The application results demonstrate the capability of our data model in modeling built environments and its feasibility for the integration of indoor and outdoor navigation.
Zhiyong Wang; Lei Niu. A Data Model for Using OpenStreetMap to Integrate Indoor and Outdoor Route Planning. Sensors 2018, 18, 2100 .
AMA StyleZhiyong Wang, Lei Niu. A Data Model for Using OpenStreetMap to Integrate Indoor and Outdoor Route Planning. Sensors. 2018; 18 (7):2100.
Chicago/Turabian StyleZhiyong Wang; Lei Niu. 2018. "A Data Model for Using OpenStreetMap to Integrate Indoor and Outdoor Route Planning." Sensors 18, no. 7: 2100.
This paper investigates the integration of traffic information (TI) into the routing in the presence of moving obstacles. When traffic accidents occur, the incidents could generate different kinds of hazards (e.g., toxic plumes), which make certain parts of the road network inaccessible. On the other hand, the first responders, who are responsible for management of the traffic incidents, need to be fast and safely guided to the incident place. To support navigation in the traffic network affected by moving obstacles, in this paper, we provide a spatio-temporal data model to structure the information of traffic conditions that is essential for the routing, and present an extended path planning algorithm, named MOAAstar–TI (Moving Obstacle Avoiding A* using Traffic Information), to generate routes avoiding the obstacles. A speed adjustment factor is introduced in the developed routing algorithm, allowing integration of both the information of vehicles and traffic situations to generate routes avoiding the moving obstacles caused by the incidents. We applied our system to a set of navigation scenarios. The application results show the potentials of our system in future application in real life.
Zhiyong Wang; John Steenbruggen; Sisi Zlatanova. Integration of Traffic Information into the Path Planning among Moving Obstacles. ISPRS International Journal of Geo-Information 2017, 6, 86 .
AMA StyleZhiyong Wang, John Steenbruggen, Sisi Zlatanova. Integration of Traffic Information into the Path Planning among Moving Obstacles. ISPRS International Journal of Geo-Information. 2017; 6 (3):86.
Chicago/Turabian StyleZhiyong Wang; John Steenbruggen; Sisi Zlatanova. 2017. "Integration of Traffic Information into the Path Planning among Moving Obstacles." ISPRS International Journal of Geo-Information 6, no. 3: 86.