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Automated Vehicle Delay and Travel Time Estimation Techniques for Improved Performance Measures of Urban Network System

Shatnawi, Ibrahem Mahmoud
http://rave.ohiolink.edu/etdc/view?acc_num=akron1446473677

Abstract Details

2015, Doctor of Philosophy, University of Akron, Civil Engineering.
Vehicle delay and travel time are considered the most important measures of effectiveness (MOE) in urban arterial roads. They allow traffic engineers to evaluate the performance of a traffic system component or the effectiveness of the system-wide control strategy. They are often utilized for real-time applications such as adaptive signal control, congestion management, and dynamic traffic assignment. However, obtaining intersection performance data in real-time, including average control delay and travel time, can be very time consuming and labor intensive. Three real-time logics: AVDET, AVTTET, and ANDET are proposed for estimating performance measures of isolated intersections, traffic corridors, and traffic networks. These approaches use the existing traffic detection system to calculate vehicle delay and travel time. By using a real-time traffic detection system as an input for traffic information, the developed algorithms use the obtained information from both the detectors and the signal system of the intersection. By tracking the status of the traffic signal operation and detectors second-by-second, travel time, approach, and intersection delays can be estimated automatically. Results from the proposed algorithms were compared to those from simulation output and different statistical tests were conducted under varying traffic operation conditions. The findings show that the proposed algorithms can yield very stable and reliable results in various traffic and signal control conditions. Future work of field implementation for the proposed algorithms is recommended to investigate the model reliability and effectiveness in real-time traffic conditions. Furthermore, in this dissertation, an analysis has been conducted to obtain the turning movement information in real time from limited data available. By using the MATLAB software, Moore–Penrose pseudoinverse method was adopted to estimate the turning movements. Also, a mathematical model for analyzing the effect of errors in the known variables on the final output of the unknown variables was developed.
Ping Yi (Advisor)
William Schneider (Committee Member)
Zhe Luo (Committee Member)
Sozer Yilmaz (Committee Member)
Ye Jun (Committee Member)
200 p.
Transportation

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Citations

  • Shatnawi, I. M. (2015). Automated Vehicle Delay and Travel Time Estimation Techniques for Improved Performance Measures of Urban Network System [Doctoral dissertation, University of Akron]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=akron1446473677

    APA Style (7th edition)

  • Shatnawi, Ibrahem. Automated Vehicle Delay and Travel Time Estimation Techniques for Improved Performance Measures of Urban Network System. 2015. University of Akron, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=akron1446473677.

    MLA Style (8th edition)

  • Shatnawi, Ibrahem. "Automated Vehicle Delay and Travel Time Estimation Techniques for Improved Performance Measures of Urban Network System." Doctoral dissertation, University of Akron, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=akron1446473677

    Chicago Manual of Style (17th edition)

akron1446473677
330
© 2015, all rights reserved.
This open access ETD is published by University of Akron and OhioLINK.