TY - GEN
T1 - Development of a geocoding system for diverse road data
AU - Imai, Ryuichi
AU - Taniguchi, Hisatoshi
AU - Tajima, Satoshi
AU - Hashimoto, Hiroyoshi
AU - Shigetaka, Koichi
PY - 2019/5/15
Y1 - 2019/5/15
N2 - Diverse and massive road traffic data, such as about traffic congestion, disasters, traffic restrictions, travel history and traffic volume, are expressed by different location referencing methods including latitude & longitude, DRM links, milepost, sight frontage names, and addresses. Each of these location referencing methods is suitable for the respective use. In treating some different types of road traffic data under the same environment, however, e.g. in superimposing road traffic data created by different location referencing methods on a map or spatial processing requires conversion of their location referencing methods, which is being an obstructive factor to smooth distribution of road traffic data. In this research, we developed a geocoding algorithm that enables interconversion of location referencing methods including latitude & longitude, digital road map (DRM), VICS, the Road Section Identification Data set (RSIDs), Reference Road Sections, and milepost. And we verified the usefulness by mutually converting actual road traffic data using the system that implements the algorithm.
AB - Diverse and massive road traffic data, such as about traffic congestion, disasters, traffic restrictions, travel history and traffic volume, are expressed by different location referencing methods including latitude & longitude, DRM links, milepost, sight frontage names, and addresses. Each of these location referencing methods is suitable for the respective use. In treating some different types of road traffic data under the same environment, however, e.g. in superimposing road traffic data created by different location referencing methods on a map or spatial processing requires conversion of their location referencing methods, which is being an obstructive factor to smooth distribution of road traffic data. In this research, we developed a geocoding algorithm that enables interconversion of location referencing methods including latitude & longitude, digital road map (DRM), VICS, the Road Section Identification Data set (RSIDs), Reference Road Sections, and milepost. And we verified the usefulness by mutually converting actual road traffic data using the system that implements the algorithm.
UR - http://www.scopus.com/inward/record.url?scp=85067097021&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067097021&partnerID=8YFLogxK
U2 - 10.1109/SCIS-ISIS.2018.00013
DO - 10.1109/SCIS-ISIS.2018.00013
M3 - Conference contribution
AN - SCOPUS:85067097021
T3 - Proceedings - 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2018
SP - 7
EP - 13
BT - Proceedings - 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2018
Y2 - 5 December 2018 through 8 December 2018
ER -
