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Development and Testing of An Application System for Intersection Data Collection and Analysis

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2017, Doctor of Philosophy, University of Akron, Civil Engineering.
Nowadays vehicle turning movement data can be applied in many fields such as adaptive traffic control, dynamic planning and traffic demand analysis. Accurate real-time turning movement data can help traffic control systems generate better signal timing plans and make better operation decisions. However, such data is not easy to collect. In the past several decades, many methods have been developed to collect turning movement data such as manual data collection, modeling methods based on data resources including link volume, partial turning movement data and historical data, methods based on the genetic algorithm, Time and Place System (TAPS) method, vision-based methods and trajectory tracking methods. Each method has its own strengths and limitations, but most of the methods cannot provide real-time data with high accuracy. This study developed and calibrated an automatic vehicle turning movement data collection system which makes use of traffic signal information and detection information. The system has a hardware structure centered around a microcontroller and Raspberry Pi. The National Transportation Communications for ITS Protocol (NTCIP) was applied for signal interpretation and multiple data resources were used for the turning movement identification algorithm. The system was applied in field tests during different times of day at different intersections in the real world. Test results show that this system has high accuracy and strong robustness, and can consistently collect real-time turning movement data without being affected by location, time or weather conditions. The collected turning movement data can potentially be used for traffic planning, operation and forecasting.
Ping Yi (Advisor)
Zhe Luo (Committee Member)
Qindan Huang (Committee Member)
Hamid R. Bahrami (Committee Member)
Richard L. Einsporn (Committee Member)
88 p.

Recommended Citations

Citations

  • Zhang, S. (2017). Development and Testing of An Application System for Intersection Data Collection and Analysis [Doctoral dissertation, University of Akron]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=akron1513262599088906

    APA Style (7th edition)

  • Zhang, Songling. Development and Testing of An Application System for Intersection Data Collection and Analysis. 2017. University of Akron, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=akron1513262599088906.

    MLA Style (8th edition)

  • Zhang, Songling. "Development and Testing of An Application System for Intersection Data Collection and Analysis." Doctoral dissertation, University of Akron, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=akron1513262599088906

    Chicago Manual of Style (17th edition)