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TrafficPulse: a mobile GISystem for transportation

Authors:

Steve H. L. Liang,

Young-Ji ByonAuthors Info & Claims

MobiGIS '12: Proceedings of the First ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems

Pages 9 - 16

https://doi.org/10.1145/2442810.2442813

Published: 06 November 2012 Publication History

Abstract

Today municipalities around the world spend millions of dollars to understand the dynamics of their transportation infrastructure. Traditional approaches for traffic data collection rely on a fixed sensor infrastructure (e.g., inductive loop detectors), and because these sensors are expensive to deploy and maintain, the traffic data coverage is limited to main highways and major intersections. This limited information hinders municipalities to achieve efficient traffic management and control. To address this problem, we develop TrafficPulse, a mobile GISystem platform for transportation applications. For the client front-end, we develop the TrafficPulse mobile application that collects traffic data by integrating participatory sensing, opportunistic sensing, and offline data collection module. For the server back-end, we develop Geopot cloud, a cloud-based geo-location data service for mobile applications. In order to demonstrate the potential benefit of this system, we also develop a carpooling recommendation system to analyze user-shared content and provide a recommendation service to TrafficPulse users. In this paper, we describe our system architecture and experiences, allowing our paper to be used as a reference for other developers who want to develop their own transportation applications.

References

[1]

Google maps for android. http://www.google.com/mobile/products/maps.html#p=default.

[2]

Microsoft, bing maps tile system. http://msdn.microsoft.com/en-us/library/bb259689.aspx.

[3]

Openstreetmap. http://www.openstreetmap.org/.

[4]

Social media: the right tool in right hands. http://bit.ly/fWCjgy.

[5]

Stats: Google maps the most popular mobile app in the uk, with 6.4m users. http://bit.ly/OeFtjb.

[6]

Ushahidi. http://ushahidi.com/.

[7]

Waze. http://www.waze.com/.

[8]

M. Bell. The real time estimation of origin-destination flows in the presence of platoon dispersion. Transportation Research Part B, 25:115--125, 1991.

[9]

L. Bergroth, H. Hakonen, and T. Raita. A survey of longest common subsequence algorithms. In Proceedings of the 7th International Symposium on String Processing Information Retrieval, SPIRE'00, pages 39--48, A Corunña, Spain, 2000.

Digital Library

[10]

C. Bonnington. Global smartphone adoption approaches 30 percent. http://www.wired.com/gadgetlab/2011/11/smartphones-feature-phones/.

[11]

J. Cryans, A. April, and A. Abran. Criteria to compare cloud computing with current database technology. In Proceedings of the International Conferences on Software Process and Product Measurement, pages 114--126, Munich, Germany, 2008.

Digital Library

[12]

S. Deterding, M. Sicart, L. Nacke, K. O'Hara, and D. Dixon. Gamification. using game-design elements in non-gaming contexts. In Proceedings of the 2011 Annual Conference Extended Abstracts on Human Factors in Computing Systems, CHIEA'11, pages 2425--2428, 2011.

Digital Library

[13]

D. Douglas and T. Peucker. Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. The Canadian Cartographer, 10(2):112--122, 1973.

[14]

R. O. Duda, P. E. Hart, and D. G. Stork. Pattern classification. New York: Wiley Interscience, 2nd edition, 2000.

Digital Library

[15]

M. Goodchild. Citizens as sensors: the world of volunteered geography. GeoJournal, 69(4):211--221, 2007.

[16]

J. Grira, Y. Bédard, and S. Roche. Spatial data uncertainty in the vgi world: going from consumer to producer. Geomatica, 64:61--71, 2010.

[17]

B. Hull, V. Bychkovsky, Y. Zhang, K. Chen, K. Goraczko, A. Miu, E. Shih, H. Balakrishnan, and S. Madden. Cartel: a distributed mobile sensor computing system. In Proceedings of the 4th International Conference on Embedded Networked Sensor Systems, pages 125--138, 2006.

Digital Library

[18]

S. Kaisar. Smartphone traffic characteristics and context dependencies. Master's thesis, University of Saskatchewan, 2012.

[19]

D. W. Lee and S. H. L. Liang. Crowd-sourced carpool recommendation based on simple and efficient trajectory grouping. In The 4th International Workshop on Computational Transportation Science, IWCTS 2011, pages 12--17, Chicago, USA, 2011.

Digital Library

[20]

D. W. Lee and S. H. L. Liang. Geopot: a cloud-based geolocation data service for mobile applications. International Journal of Geographical Information Science, 25(8):1283--1301, 2011.

Digital Library

[21]

P. Mohan, V. N. Padmanabhan, and R. Ramjee. Nericell: rich monitoring of road and traffic conditions using mobile smartphones. In Proceedings of the 6th ACM conference on Embedded network sensor systems, pages 323--336, 2008.

Digital Library

[22]

C. Parker, A. May, and V. Mitchell. Relevance of volunteered geographic information in a real world context. In Proceedings of GIS Research UK 19th Annual Conference, Portsmouth, UK, 2011.

[23]

X. Qian, L. Di, D. Li, P. Li, L. Shi, and L. Cai. Data cleaning approaches in web2.0 vgi application. In Proceedings of the 17th International Conference on Geomatics, pages 12--14, Fairfax, USA, 2009.

[24]

S. L. Shaw. Geographic information systems for transportation: From a static past to a dynamic future. Annuals of GIS, 16(3):129--140, 2010.

[25]

J. Supernak. Transportation modeling: Lessons from the past and tasks for the future. Transportation, 12:79--90, 1983.

[26]

R. F. Teal. Carpooling: Who, how and why. Transportation Research Part A: General, 21(3):203--214, 1987.

[27]

H. J. V. Zuylen and L. G. Willumsen. The most likely trip matrix estimated from traffic counts. Transportation Research Part B: Methodological, 14(3):281--293, 1980.

Cited By

Ahmed A(2021)A privacy‐preserving mobile location‐based advertising system for small businessesEngineering Reports10.1002/eng2.124163:11Online publication date: 4-May-2021
https://doi.org/10.1002/eng2.12416
Moamen AJamali N(2020)Opportunistic Sharing of Continuous Mobile Sensing Data for Energy and Power ConservationIEEE Transactions on Services Computing10.1109/TSC.2017.270568513:3(503-514)Online publication date: 1-May-2020
https://doi.org/10.1109/TSC.2017.2705685
Khoi NCasteleyn S(2018)Analyzing Spatial and Temporal User Behavior in Participatory SensingISPRS International Journal of Geo-Information10.3390/ijgi70903447:9(344)Online publication date: 23-Aug-2018
https://doi.org/10.3390/ijgi7090344
Show More Cited By

Index Terms

TrafficPulse: a mobile GISystem for transportation
1. Computer systems organization
  1. Embedded and cyber-physical systems
  2. Real-time systems

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cover image ACM Conferences

MobiGIS '12: Proceedings of the First ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems

November 2012

112 pages

ISBN:9781450316996

DOI:10.1145/2442810

Conference Chair:
Chi-Yin Chow
City University of Hong Kong, Hong Kong

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2012

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SIGSPATIAL'12

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SIGSPATIAL

SIGSPATIAL'12: SIGSPATIAL 2012 International Conference on Advances in Geographic Information Systems

November 6, 2012

California, Redondo Beach

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Cited By

Ahmed A(2021)A privacy‐preserving mobile location‐based advertising system for small businessesEngineering Reports10.1002/eng2.124163:11Online publication date: 4-May-2021
https://doi.org/10.1002/eng2.12416
Moamen AJamali N(2020)Opportunistic Sharing of Continuous Mobile Sensing Data for Energy and Power ConservationIEEE Transactions on Services Computing10.1109/TSC.2017.270568513:3(503-514)Online publication date: 1-May-2020
https://doi.org/10.1109/TSC.2017.2705685
Khoi NCasteleyn S(2018)Analyzing Spatial and Temporal User Behavior in Participatory SensingISPRS International Journal of Geo-Information10.3390/ijgi70903447:9(344)Online publication date: 23-Aug-2018
https://doi.org/10.3390/ijgi7090344
Petrovska NStevanovic AFurht BPetrovska NStevanovic AFurht B(2016)Background and Related WorkInnovative Web Applications for Analyzing Traffic Operations10.1007/978-3-319-33319-9_2(3-21)Online publication date: 18-Jun-2016
https://doi.org/10.1007/978-3-319-33319-9_2
Moamen AJamali N(2015)Share SensProceedings of the 2015 IEEE International Conference on Mobile Services10.1109/MobServ.2015.22(89-96)Online publication date: 27-Jun-2015
https://dl.acm.org/doi/10.1109/MobServ.2015.22
Petrovska NStevanovic A(2015)Traffic Congestion Analysis Visualisation ToolProceedings of the 2015 IEEE 18th International Conference on Intelligent Transportation Systems10.1109/ITSC.2015.243(1489-1494)Online publication date: 15-Sep-2015
https://dl.acm.org/doi/10.1109/ITSC.2015.243
Torres JPomares A(2015)Participant selection in CrowdSensing environments2015 10th Computing Colombian Conference (10CCC)10.1109/ColumbianCC.2015.7333453(408-415)Online publication date: Sep-2015
https://doi.org/10.1109/ColumbianCC.2015.7333453
Moamen AJamali N(2015)CSSWare: A Middleware for Scalable Mobile Crowd-Sourced ServicesMobile Computing, Applications, and Services10.1007/978-3-319-29003-4_11(181-199)Online publication date: 2015
https://doi.org/10.1007/978-3-319-29003-4_11
Bakillah MLauer JLiang SZipf AArsanjani JMobasheri ALoos LKarimi H(2014)Exploiting Big VGI to Improve Routing and Navigation ServicesBig Data10.1201/b16524-10(177-192)Online publication date: 22-Jan-2014
https://doi.org/10.1201/b16524-10
Harding MFinney JDavies NRouncefield MHannon JMattern FSantini SCanny JLangheinrich MRekimoto J(2013)Experiences with a social travel information systemProceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing10.1145/2493432.2493475(173-182)Online publication date: 8-Sep-2013
https://dl.acm.org/doi/10.1145/2493432.2493475

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