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

Details

• Creators:
  Peeta, Srinivas ; Du, Lili ; Kim, Yong Hoon
• Corporate Creators:
  Purdue University.
• Corporate Contributors:
  United States. Department of Transportation. Research and Innovative Technology Administration
• Subject/TRT Terms:
  Analysis Mathematical Models Probe Vehicles Travel Time (Traffic Engineering)--Mathematical Models Traffic Monitoring--Mathematical Models Travel Time Vehicle-infrastructure Integration
• Resource Type:
  Tech Report
• Geographical Coverage:
  Indiana
• Corporate Publisher:
  NEXTRANS Center (U.S.)
• Abstract:
  This research seeks to explore vehicle-to-vehicle information networks to understand the interplay
  
  between the information communicated and traffic conditions on the network. A longer-term goal is to
  
  develop a decision support tool for processing and storage of large amount of real-time (probe) data for
  
  advancing the state of the art in Vehicle Infrastructure Integration (VII). The fundamental concept in VII
  
  is that the (probe) vehicles serve as data collectors and anonymously transmit traffic information to
  
  transportation agencies to facilitate proactive strategies for traffic management and safety. The project
  
  develops new data fusion algorithms for travel time estimation and online stochastic routing which
  
  provides 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 wireless
  
  communication equipment are installed so that inter-vehicular communications are enabled. As a newly
  
  emerging paradigm of the Advanced Traveler Information Systems (ATIS), the VANET has received
  
  significant interest recently. There are many challenging research topics in this promising area, which
  
  can be grouped into two major categories. The first category includes the issues regarding the
  
  performance of the communication networks; for example, the network connectivity, the
  
  communication capacity, the broadcasting protocol, and so on. The second category comprises issues
  
  about traffic networks such as traffic data or information fusion, and online routing. This study focuses
  
  on building the information fusion framework to predict the short-term link travel time distribution with
  
  the real-time travel-time information provided by a VANET.
  
  
• Format:
  PDF
• Collection(s):
  University Transportation Centers US Transportation Collection
• Main Document Checksum:
  urn:sha-512:85cef9590a79d3cb6e126238886baf73ac3e56d3a8d1760fb860780a02039b8f16480fd81be8113948d2ac655288c92491f4045bd2b60faff7836487c006a067
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/5705/dot_5705_DS1.pdf
• File Type:
  [PDF - 2.34 MB ]