Real-time routing with OpenStreetMap data

Luxen, Dennis; Vetter, Christian

doi:10.1145/2093973.2094062

Cited by 324 publications

(205 citation statements)

References 15 publications

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“…Because of this margin of error, some of the coordinates received did not actually correspond to streets and/or roads. To overcome this we used map matching using the Open Source Route Matching project (Project OSRM) implementation of the Graphhopper algorithm [4,9,10]. This allowed us to correlate the tweets and congestion information with the nearest available street for a more accurate and meaningful visual representation.…”

Section: Experimental Setup and Resultsmentioning

confidence: 99%

Towards provisioning of real-time smart city services using clouds

Soomro

Khan

Hasham

2016

Proceedings of the 9th International Conference on Utility and Cloud Computing

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ICT is becoming an enabler for smart city applications by making effective use of various data resources generated daily in an urban environment. Mostly this data is utilised by city authorities for city planning purposes and often citi- zens become indirect beneficiaries of such applications. In this paper we present an algorithm for real-time processing of streaming data from multiple sources. We also present the design and proof of concept of an application that per- forms mining and analysis of open data available through city portals and social networks and generates an informa- tion service in real time for use by city administrations. The prototype utilises streaming data from Twitter and open data from Bristol to demonstrate a hypothetical scenario using Apache Storm. The output is presented in the form of visual maps using OpenStreetMaps as a backend and the prototype highlights various challenges which are discussed in detail

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Section: Experimental Setup and Resultsmentioning

confidence: 99%

Towards provisioning of real-time smart city services using clouds

Soomro

Khan

Hasham

2016

Proceedings of the 9th International Conference on Utility and Cloud Computing

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“…Bing Map [26] is another map service provider, which calculates and display directions and routes on the Map with Direction API module or with Bing Map Rest Services. Several alternatives can also be used for those ridesharing providers who opt for a self-hosted direction provider: a great example is The Open Source Routing Machine [27], which is a high performance routing engine written in C++ designed to run on OpenStreetMap data.…”

Section: The Route Matching Algorithmmentioning

confidence: 99%

Dynamic Carpooling in Urban Areas: Design and Experimentation with a Multi-Objective Route Matching Algorith

et al. 2017

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This paper focuses on dynamic carpooling services in urban areas to address the needs of mobility in real-time by proposing a two-fold contribution: a solution with novel features with respect to the current state-of-the-art, which is named CLACSOON and is available on the market; the analysis of the carpooling services performance in the urban area of the city of Cagliari through emulations. Two new features characterize the proposed solution: partial ridesharing, according to which the riders can walk to reach the driver along his/her route when driving to the destination; the possibility to share the ride when the driver has already started the ride by modeling the mobility to reach the driver destination. To analyze which features of the population bring better performance to changing the characteristics of the users, we also conducted emulations. When compared with current solutions, CLACSOON allows for achieving a decrease in the waiting time of around 55% and an increase in the driver and passenger success rates of around 4% and 10%, respectively. Additionally, the proposed features allowed for having an increase in the reduction of the CO 2 emission by more than 10% with respect to the traditional carpooling service.

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“…The map-matching approach makes use of the Viterbi algorithm for maximizing the product of measurement probabilities and transition probabilities to determine the most likely route. An open source map-matching implementation from the project Open Street Routing Machine (OSRM) is used in this study [21]. Timestamps did not change during map-matching, i.e., ∀ : ∈ , ∈ , , , , , ,…”

Section: Map-matchingmentioning

confidence: 99%