Commercial remote sensing & spatial information (CRS & SI) technologies program for reliable transportation systems planning : volume 1 - comparative evaluation of link-level travel time from different technologies and sources.

PDFTech ReportRITARS-12-H-UNCC-1Remote sensingGeographic information systemsGlobal Positioning SystemTravel timeTransportation planningData collectionTechnological innovationsBluetooth technologyUnited StatesUnited States. Dept. of Transportation. Office of the Assistant Secretary for Research and TechnologyPulugurtha, Srinivas S.Pinnamaneni, Rahul C.Duddu, Venkata R.Reza, R.M. ZahidUniversity of North Carolina at Charlotte. Dept. of Civil and Environmental EngineeringUS Transportation CollectionAccurate travel time information is required to efficiently plan and effectively manage transportation network. Technologies andprivate data sources such as INRIX, TomTom and HERE offer the potential to continuously collect travel time data and use it forlong-term transportation planning as well as real-time traffic condition monitoring. However, their ability to accurately collecttravel time data is still unclear. The first phase of this study focused on capturing and estimating link/section level travel times onarterial streets and freeways using manual floating car method, Global Positioning System (GPS) floating car method, Bluetoothdetectors, and INRIX. A comparison between travel times collected manually and using various technologies / sources (GPS,Bluetooth detectors and INRIX) was performed for each travel time run. Results showed that both Bluetooth detectors andINRIX yield promising estimates for freeways. However, travel time data captured for arterial streets using Bluetooth detectorsare less accurate and not dependable when compared to other technologies. Moreover, data from Bluetooth detectors capturedusing the vendor\u2019s software showed a significant number of outliers. Therefore, the second phase focused on filtering rawsample of Bluetooth detectors data, estimating travel time, and then comparing with manual travel time data to recommendfiltering and data capturing criteria. The effect of spacing between the Bluetooth detectors and signal cabinet controller location(in which Bluetooth detector was placed) on the percent difference in travel time was examined. The role of on-network andtemporal characteristics on difference in travel time from GPS, Bluetooth detectors and INRIX (when compared to ground truth)was also examine