To manage the data measured from Honam high-speed railroad(HSR) infrastructure(environmental noise reduction structures, track structures, catenary system), we are trying to establish an integrated database through analysis of the developed infrastructure technologies and standards, construction of prototypes on the fields and evaluation of infrastructure performance according to the increment of train speed. In this paper, integrated monitoring center for management of measured data is suggested.

Needs for a new technologies of infrastructure systems arose, following the development of next generation EMU(Electric Multiple Unit) train with maximum speed over 400km/h. For high-speed operation tests of the new EMU, a high-speed railway infrastructure test-bed was constructed in a 28km long section of the Honam High-speed Railway. Diverse sensors and monitoring system was installed for continuous monitoring of the railway. Due to such effort, further demands and needs of the integrated monitoring system was derived in a more comprehensive and long-term perspective.

Recently, power distributed high-speed train with 430km/h(HEMU-430X) has developed in korea, 2012. However, the development of the train alone can not achieve the speed of high-speed rail system. So it needs the development of infrastructure system. In this paper, the project named “Application & technology development of high-speed rail infrastructure for 400km/h-class” being promoted in december 2010 will be introduced comprehensively.

From the traffic analysis, and model constructions and verifications for speed prediction on the freeway ramp junctions with 70mph speed limit, the following results were obtained : ⅰ) The traffic flow distribution showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy distribution was also shown to be varied by a big difference depending on the time periods. Especially, the occupancy in the morning peak period showed over 100% increase when compared with the 24hours average occupancy, and the occupancy in the afternoon peak period over 25% increase when compared with the same occupancy. ⅲ) The speed distribution was not shown to have a big difference depending on the time periods. Especially, the speed in the morning peak period showed 10mph decrease when compared with the 24hours'average speed, but the speed did not show a big difference in the afternoon peak period. ⅳ) The analyses of variance showed a high explanatory power between the speed predictive models(SPM) constructed and the variables used, especially the upstream speed. ⅴ) The analysis of correlation for verifying the speed predictive models(SPM) constructed on the ramp junctions were shown to have a high correlation between observed data and predicted data. Especially, the correlation coefficients showed over 0.95 excluding the unstable condition on the diverge section. ⅵ) Speed predictive models constructed were shown to have the better results than the HCM models, even if the speed limits on the freeway were different between the HCM models and speed predictive models constructed.