A pedestrian network construction algorithm based on multiple GPS traces

Kasemsuppakorn, Piyawan; Karimi, Hassan A.

doi:10.1016/j.trc.2012.09.007

Cited by 66 publications

(42 citation statements)

References 24 publications

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“…We compared between two alternatives for the geo-location sub-system. Kasemsuppakorn and Karimi [26] suggest an algorithm for creating a pedestrian network that comes only from GPS data from users' mobile phones. We implemented their algorithm in order to compare it to the Google fused location provider.…”

Section: Geo-location and Cartographymentioning

confidence: 99%

“…For this purpose, we implemented several algorithms in the server for the correction of paths that were uploaded by users. The first filtering rejects the points that had very small accuracy, as it is suggested by Kasemsuppakorn and Karimi [26]. Next, the smoothing of the path is performed according to the algorithm of Douglas and Peucker [27].…”

Section: Geo-location and Cartographymentioning

confidence: 99%

See 1 more Smart Citation

Citizen science for pedestrian cartography: collection and moderation of walkable routes in cities through mobile gamification

Kapenekakis

Chorianopoulos

2017

Hum. Cent. Comput. Inf. Sci.

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Digital geographical maps can be regarded as a user interface for understanding and navigating the city. Nevertheless, contemporary digital maps over-emphasize the needs of motor vehicles. Pedestrian routes have only been considered as an add-on option in existing digital maps and the respective data collection has not been performed in the field. In this article, we present a mobile application that employs gamification as a means to engage users to collect pragmatic data about walkable routes, which are then processed with the goal of creating a new kind of pedestrian-friendly cartography. Besides the technical infrastructure for collecting and filtering the route traces, the main challenge in user-generated walkable routes is the identification of malicious data, which should be rejected, as well as the rewarding of constructive behavior through peer-review. For this purpose, the mobile application employs a point system in order to identify and discourage the submission of bad routes. A longitudinal (2-months) field study of the mobile application confirmed that gamification facilitates effective data collection for producing pedestrian cartography even with few users and demonstrated that gamification infuses a shared responsibly about the quality of data collection. The visualization of the pedestrian-generated data on a map required a partially manual process, thus, further research should explore the gamification of the data visualization part, too.

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Section: Geo-location and Cartographymentioning

confidence: 99%

Section: Geo-location and Cartographymentioning

confidence: 99%

Citizen science for pedestrian cartography: collection and moderation of walkable routes in cities through mobile gamification

Kapenekakis

Chorianopoulos

2017

Hum. Cent. Comput. Inf. Sci.

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“…Cao and Krumm [23] used physical attraction simulations to convert raw GPS traces to a routable road network, and Fathi and Krumm [24] introduced an approach based on with finding road intersections rather than defining the road geometry. Piyawan Kasemsuppakorn et al [25] developed a pedestrian path extraction technique to generate pedestrian path segments, but the method was more susceptible to the multi-path problem than data acquired from driving. J. Biagioni et al [26] designed a hybrid process to automatically infer road maps from large collections of trajectories, which was tolerant to disparities in coverage and noise.…”

Section: Road Map Generation With Trajectoriesmentioning

confidence: 99%

Updating Road Networks by Local Renewal from GPS Trajectories

Xiang

Gong

2016

IJGI

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Abstract:The long production cycle and huge cost of collecting road network data often leave the data lagging behind the latest real conditions. However, this situation is rapidly changing as the positioning techniques ubiquitously used in mobile devices are gradually being implemented in road network research and applications. Currently, the predominant approaches infer road networks from mobile location information (e.g., GPS trajectory data) directly using various extracting algorithms, which leads to expensive consumption of computational resources in the case of large-scale areas. For this reason, we propose an alternative that renews road networks with a novel spiral strategy, including a hidden Markov model (HMM) for detecting potential problems in existing road network data and a method to update the data, on the local scale, by generating new road segments from trajectory data. The proposed approach reduces computation costs on roads with completed or updated information by updating problem road segments in the minimum range of the road network. We evaluated the performance of our proposals using GPS traces collected from taxies and OpenStreetMap (OSM) road networks covering urban areas of Wuhan City.

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“…Moreover, pedestrian route networks have also been designed from self-reported GPS traces of walkers [40]. GPS data of this type have not only been used for mapping purposes, but also to detect the behavior of different road users [41] and to infer travel modes [42].…”

Section: Introductionmentioning

confidence: 99%

Mapping Rural Road Networks from Global Positioning System (GPS) Trajectories of Motorcycle Taxis in Sigomre Area, Siaya County, Kenya

Oloo

2018

IJGI

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Effective transport infrastructure is an essential component of economic integration, accessibility to vital social services and a means of mitigation in times of emergency. Rural areas in Africa are largely characterized by poor transport infrastructure. This poor state of rural road networks contributes to the vulnerability of communities in developing countries by hampering access to vital social services and opportunities. In addition, maps of road networks are incomplete, and not up-to-date. Lack of accurate maps of village-level road networks hinders determination of access to social services and timely response to emergencies in remote locations. In some countries in sub-Saharan Africa, communities in rural areas and some in urban areas have devised an alternative mode of public transport system that is reliant on motorcycle taxis. This new mode of transport has improved local mobility and has created a vibrant economy that depends on the motorcycle taxi business. The taxi system also offers an opportunity for understanding local-level mobility and the characterization of the underlying transport infrastructure. By capturing the spatial and temporal characteristics of the taxis, we could design detailed maps of rural infrastructure and reveal the human mobility patterns that are associated with the motorcycle taxi system. In this study, we tracked motorcycle taxis in a rural area in Kenya by tagging volunteer riders with Global Positioning System (GPS) data loggers. A semi-automatic method was applied on the resulting trajectories to map rural-level road networks. The results showed that GPS trajectories from motorcycle taxis could potentially improve the maps of rural roads and augment other mapping initiatives like OpenStreetMap.

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A pedestrian network construction algorithm based on multiple GPS traces

Cited by 66 publications

References 24 publications

Citizen science for pedestrian cartography: collection and moderation of walkable routes in cities through mobile gamification

Citizen science for pedestrian cartography: collection and moderation of walkable routes in cities through mobile gamification

Updating Road Networks by Local Renewal from GPS Trajectories

Mapping Rural Road Networks from Global Positioning System (GPS) Trajectories of Motorcycle Taxis in Sigomre Area, Siaya County, Kenya

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