A Kriging based spatiotemporal approach for traffic volume data imputation.

ABSTRACT: Along with the rapid development of Intelligent Transportation Systems, traffic data collection technologies have progressed fast. The emergence of innovative data collection technologies such as remote traffic microwave sensor, Bluetooth sensor, GPS-based floating car method, and automated license plate recognition, has significantly increased the variety and volume of traffic data. Despite the development of these technologies, the missing data issue is still a problem that poses great challenge for data based applications such as traffic forecasting, real-time incident detection, dynamic route guidance, and massive evacuation optimization. A thorough literature review suggests most current imputation models either focus on the temporal nature of the traffic data and fail to consider the

SUBMITTER: Yang H 

PROVIDER: S-EPMC5903649 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature