A decision support tool for vehicle infrastructure integration : understanding information effects and advancing data fusion algorithms for traffic management applications.

685138207PDFTech ReportTravel timeMathematical modelsAnalysisProbe vehiclesIndianaNEXTRANS Center (U.S.)Peeta, SrinivasDu, LiliKim, Yong HoonPurdue University.United States. Dept. of Transportation. Research and Innovative Technology AdministrationNTL-REFERENCES AND DIRECTORIES-StatisticsNTL-PLANNING AND POLICY-PLANNING AND POLICYBTS Data DirectoryThis research seeks to explore vehicle-to-vehicle information networks to understand the interplaybetween the information communicated and traffic conditions on the network. A longer-term goal is todevelop a decision support tool for processing and storage of large amount of real-time (probe) data foradvancing the state of the art in Vehicle Infrastructure Integration (VII). The fundamental concept in VIIis that the (probe) vehicles serve as data collectors and anonymously transmit traffic information totransportation agencies to facilitate proactive strategies for traffic management and safety. The projectdevelops new data fusion algorithms for travel time estimation and online stochastic routing whichprovides a clear representation of the benefit of information exchange between vehicles in VANETs.A Vehicular Ad Hoc Network (VANET) is composed of smart vehicles in which advanced wirelesscommunication equipment are installed so that inter-vehicular communications are enabled. As a newlyemerging paradigm of the Advanced Traveler Information Systems (ATIS), the VANET has receivedsignificant interest recently. There are many challenging research topics in this promising area, whichcan be grouped into two major categories. The first category includes the issues regarding theperformance of the communication networks; for example, the network connectivity, thecommunication capacity, the broadcasting protocol, and so on. The second category comprises issuesabout traffic networks such as traffic data or information fusion, and online routing. This study focuseson building the information fusion framework to predict the short-term link travel time distribution withthe real-time travel-time information provided by a VANET