A context-aware traffic congestion estimation framework to overcome missing sensory data in Bangkok

To ensure the availability and continuity of reported traffic information despite the uncertainty of sensor data, an approach that estimates traffic congestion when sensory data is not available is required. In this thesis, we conduct research into this issue through the lens of a design science research methodology. We propose an artefact, the Context-Aware Traffic Congestion Estimation Framework to Overcome Missing Sensory Data (the CATE framework), to address the above issues. Most existing methods estimate traffic congestion using sensors. In contrast, the CATE framework utilizes available external context information to infer the traffic situation. The framework contains several inference models that represent different situations based on the available context. When sensory traffic data is missing, an appropriate model is selected during run time to infer the traffic congestion degree. The models were developed using machine learning algorithms during our research based on traffic data collected in Bangkok. To further improve the initial artefact of the CATE framework, further test was carried out in the form of survey. The survey collected Bangkok road users' perceptions of the factors that affect traffic in Bangkok. We used the results of these questions to create recommendations for the development of TIS and traffic report services. Through the conceptualization and evaluation of our CATE framework, this thesis makes theoretical and practical contributions to the Intelligent Transportation System (ITS) domain. Through the survey based on the perceptions of Bangkok road users and subsequent statistical analysis, the thesis also makes contributions to the development of traffic information system (TIS) reporting systems.

• Record URL:
  http://arrow.monash.edu.au/hdl/1959.1/1219240
• Record URL:
  http://arrow.monash.edu.au/vital/access/manager/Index
• Supplemental Notes:
  • PhD thesis
• Authors:
  • Raphiphan, P
• Publication Date: 2015-6

Language

• English

Media Info

• Pagination: 282p

Subject/Index Terms

• TRT Terms: Data collection; Highway traffic control; Intelligent transportation systems; Mathematical models; Sensors; Traffic congestion; Traffic flow; Traveler information and communication systems
• Geographic Terms: Bangkok (Thailand); Thailand
• ATRI Terms: Data collection; Intelligent transport systems (ITS); Modelling; Sensor; Traffic congestion; Traffic flow; Traffic management; Travel information
• ITRD Terms: 632: Congestion (traffic); 8735: Intelligent transport system; 1755: Road user
• Subject Areas: Operations and Traffic Management; I71: Traffic Theory;

Filing Info

• Accession Number: 01586874
• Record Type: Publication
• Source Agency: ARRB
• Files: ITRD, ATRI
• Created Date: Jan 14 2016 11:34AM