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A Study on Predictive Traffic Information Using Cloud Route Search
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 Title & Authors
A Study on Predictive Traffic Information Using Cloud Route Search
Jun Hyun, Kim; Kee Wook, Kwon;
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 Abstract
Recent navigation systems provide quick guide services, based on processing real-time traffic information and past traffic information by applying predictable pattern for traffic information. However, the current pattern for traffic information predicts traffic information by processing past information that it presents an inaccuracy problem in particular circumstances(accidents and weather). So, this study presented a more precise predictive traffic information system than historical traffic data first by analyzing route search data which the drivers ask in real time for the quickest way then by grasping traffic congestion levels of the route in which future drivers are supposed to locate. First results of this study, the congested route from Yang Jae to Mapo, the analysis result shows that the accuracy of the weighted value of speed of existing commonly congested road registered an error rate of 3km/h to 18km/h, however, after applying the real predictive traffic information of this study the error rate registered only 1km/h to 5km/h. Second, in terms of quality of route as compared to the existing route which allowed for an earlier arrival to the destination up to a maximum of 9 minutes and an average of up to 3 minutes that the reliability of predictable results has been secured. Third, new method allows for the prediction of congested levels and deduces results of route searches that avoid possibly congested routes and to reflect accurate real-time data in comparison with existing route searches. Therefore, this study enabled not only the predictable gathering of information regarding traffic density through route searches, but it also made real-time quick route searches based on this mechanism that convinced that this new method will contribute to diffusing future traffic flow.
 Keywords
Real-time Route Search;Predictive Traffic Information;Historical Traffic Data;
 Language
Korean
 Cited by
 References
1.
Chol, B., Kang, H., Lee, S., and Han, S. (2009), A study for traffic forecasting using traffic statistic information, The Korean Journal of Applied Statistics, Vol. 22, No. 6, pp. 1177-1190.(in Korean with English abstract) crossref(new window)

2.
Choi, J. and Yang, Y. (2008), An efficient filtering technique of GPS traffic data using historical data, Journal of Korea Spatial Information System Society, Vol. 10, No. 3, pp.55-65.(in Korean with English abstract)

3.
Han, G., Kim, I., and Kim, H.(2003), Effects of predictive transportation information on traffic pattern, Journal of the Korea Institute of Intelligent Transport Systems, Vol. 2003, No.1, pp. 142-147.(in Korean with English abstract)

4.
Hwang, J., Kang, H., and Choi, H. (2012), A method for extracting vehicle speed using aerial images, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 30, No. 1, pp, 11-19.(in Korean with English abstract) crossref(new window)

5.
Kim, D., Jeong, Y., and Min, S. (2012), A study on building the platform and development of algorithm for collecting real-time traffic data, Proceedings of 31th Korea Institute Information and Communication Engineering Congress, 25-26 May, Pusan, Korea, Vol. 31. No. 1, pp. 535-538.

6.
Lee, C. (2003), Route travel time stabilization by real time traffic information improvement, Journal of The Korea Institute of Intelligent Transport Systems, Vol. 2, No. 1, pp. 101-108.(in Korean with English abstract)

7.
Lee, G. (2011), A Study on the Connecting Methods of Traffic Information using OPEN-API, Master’s thesis, Ajou University, Gyeonggi-do, Korea, 56p.(in Korean with English abstract)

8.
Lee, G. and Nam, D. (2012), Open architecture of transportation information dissemination using open API, The Journal of the Institute of Internet, Broadcasting and Communication, Vol. 12, No. 1, pp. 109-114.(in Korean with English abstract)

9.
Oh, M. and Park, S.(2013), A weighted based pre-perform A* algorithm for efficient heuristics computation processing, Journal of Korea Game Society, Vol. 13, No. 6, pp. 43-52. (in Korean with English abstract)

10.
Park, Y., Jeong, Y., and Min S.(2012), A study on development of verification system for real-time traffic data using TPEG data and GPS device, Proceedings of 31th Korea Institute Information and Communication Engineering Congress, 25-26 May, Pusan, Korea, Vol. 31. No. 1, pp. 547-549.(in Korean with English abstract)

11.
Ryu, Y.(2013), Development of a shortest path searching algorithm using minimum expected weights, Journal of the Korea Institute of Intelligent Transport Systems, Vol. 12, No. 5, pp. 36-45.(in Korean with English abstract) crossref(new window)

12.
Wang, J. and Kim, D. (2013), Development of destination arrival time prediction system for bus that applied smart-phone based real-time traffic information, Journal of the Korea Society of Digital Industry and Information Management, Vol. 9, No. 4, pp. 127-134.(in Korean with English abstract)

13.
Yoo, Y. and Jo, M. (2006), The system for predicting the traffic flow with the real-time traffic information, International Journal of Maritime Information and Communication Sciences, Vol. 10, No. 7, pp. 1312-1318.(in Korean with English abstract)