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Title: A SPATIOTEMPORAL APPROACH FOR HIGH RESOLUTION TRAFFIC FLOW IMPUTATION

Along with the rapid development of Intelligent Transportation Systems (ITS), traffic data collection technologies have been evolving dramatically. The emergence of innovative data collection technologies such as Remote Traffic Microwave Sensor (RTMS), Bluetooth sensor, GPS-based Floating Car method, automated license plate recognition (ALPR) (1), etc., creates an explosion of traffic data, which brings transportation engineering into the new era of Big Data. However, despite the advance of technologies, the missing data issue is still inevitable and has posed great challenges for research such as traffic forecasting, real-time incident detection and management, dynamic route guidance, and massive evacuation optimization, because the degree of success of these endeavors depends on the timely availability of relatively complete and reasonably accurate traffic data. A thorough literature review suggests most current imputation models, if not all, focus largely on the temporal nature of the traffic data and fail to consider the fact that traffic stream characteristics at a certain location are closely related to those at neighboring locations and utilize these correlations for data imputation. To this end, this paper presents a Kriging based spatiotemporal data imputation approach that is able to fully utilize the spatiotemporal information underlying in traffic data. Imputation performance of themore » proposed approach was tested using simulated scenarios and achieved stable imputation accuracy. Moreover, the proposed Kriging imputation model is more flexible compared to current models.« less
Authors:
 [1] ;  [2] ;  [2]
  1. University of Tennessee, Knoxville (UTK)
  2. ORNL
Publication Date:
OSTI Identifier:
1261368
DOE Contract Number:
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: Transportaion Research Board (TRB) 95th Annual Meeting, Washington, DC, USA, 20160110, 20160114
Research Org:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
ORNL work for others
Country of Publication:
United States
Language:
English