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A Study on Prediction of Traffic Volume Using Road Management Big Data
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 Title & Authors
A Study on Prediction of Traffic Volume Using Road Management Big Data
Sung, Hongki; Chong, Kyusoo;
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 Abstract
In reflection of road expansion and increasing use rates, interest has blossomed in predicting driving environment. In addition, a gigantic scale of big data is applied to almost every area around the world. Recently, technology development is being promoted in the area of road traffic particularly for traffic information service and analysis system in utilization of big data. This study examines actual cases of road management systems and road information analysis technologies, home and abroad. Based on the result, the limitations of existing technologies and road management systems are analyzed. In this study, a development direction and expected effort of the prediction of road information are presented. This study also examines regression analysis about relationship between guide name and traffic volume. According to the development of driving environment prediction platform, it will be possible to serve more reliable road information and also it will make safe and smart road infrastructures.
 Keywords
Road Information;Driving Environment;Prediction;Road Management System;
 Language
English
 Cited by
 References
1.
Choi, W.S., Nah, H.S., Seo, M.B., Jeong, S.Y., and Lim, J.T. (2010), Asset management information in the social infrastructure, Journal of the Korea Contents Association, Vol. 10, No. 11, pp. 68-79. (in Korean with English abstract)

2.
Chun, S.H., Kwon, S.K., Lim, H.S., Nam, D.S., and Lee, Y.I. (2011), Analysis of spatial influential zone for road sign using the variable radius buffer model, Journal of the Korean Society of Transportation, Vol. 29, No. 2, pp. 71- 80. (in Korean)

3.
Kim, D.M., Jeong., Y.M, and Min, S.Y. (2012), A study on building the platform and development of algorithm for collecting real-time traffic data, The Korean Institute of Information and Communication Sciences Conference, KIICE, 26 May, Seoul, Korea, pp. 535-538. (in Korean with English abstract)

4.
Kim, H.T. (2014), Utilization of space big data - focused on the metropolitan public transport system analysis, The Korean Geographlcal Society Conference, 30 June, Seoul, Korea, pp. 284-285. (in Korean)

5.
Kim, S.H., Shin, H.S., and Son, S.H. (2014), A study on large-scale traffic information modeling using R, Journal of KIISE : Computer Systems and Theory, Vol. 41, No. 4, pp. 151-157. (in Korean with English abstract)

6.
Kwon, S.K., Chun, S.H., Lim, H.S., Nam, D.S., and Lee, Y.I. (2009), Development of the roadsign naming program, Journal of the Korean Society of Transportation, Vol. 60, pp. 3895-390. (in Korean)

7.
Lee, J. (2013), Develop a road disaster prevention network in Korea through the analysis of system in Japan, Journal of the Korean Society of Road Engineers, Vol. 15, No. 4, pp. 5-8. (in Korean)

8.
Lim, J.T., Kim, K.H., Kim, J.K., and Oh, H.K. (2014), Design and implementation of a realtime optimal traffic route guidance system through big data analysis, The Korea Contents Society Conference, 20 November, Seoul, Korea, pp. 297-298. (in Korean)

9.
Osima, H., Matsita, T., Matsura, T., and Kim, M,C. (2007), Economic and policy trends in the japanese construction industry, Research Institute of Construction and Economy, Japan, http://www.rice.or.jp (last date accessed: 6 November 2015)

10.
Park, H.S., Park, T.H., and Ha, T.J. (2006), A study on B/C analysis of improvement projects of high accident locations in highway (about safety facilities), Korean Society of Civil Engineerings Conference, 12 October, Gwangju, Korea, pp. 3939-3942. (in Korean)

11.
Shin, H.C. (2006), An introductory study for developing asset management system of road facilities, ISBN 978-89-5503-225-3 93530, KOTI, Sejong, Korea, pp. 18-60. (in Korean with English abstract)