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Exam of the Relationship of Traffic Flow, Density and Speed with RADAR Data

Ren, Hui
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535382803620171

Abstract Details

2018, PhD, University of Cincinnati, Engineering and Applied Science: Civil Engineering.
Over the past 80 years, a wide range of traffic flow studies have been developed. Bruce D. Greenshields can be considered as the father of traffic flow theory. He gave the first description of highway traffic flow on the macroscopic level by a combination of observed relationship and predictive tools presenting the relationships between traffic parameters including traffic flow, speed and density. Greenshields proposed that speed and density have an inverse linear relationship. Where density increases, traffic speed decreases. He also concluded density and flow have a continuous parabolic curve. To address the data collection limitations of loop detector and camera based methodologies, a portable radar-based sensor system was developed to automatically extract lane boundaries and vehicle trajectories at various locations. Compared to cameras, shadows, sun glare, fog and vibration do not have impact on ESR results. The Delphi ESR 2.5 can directly measure the range, azimuth and speed information for each target, easing trajectory construction. Thus, the space mean speed of all vehicles and the vehicle density in the detection area can be observed. However, ESR applications, such as vehicle trajectory extraction and traffic information extraction, have only been proposed for the lightest traffic and simplest conditions. In this research, a methodology for automated vehicle trajectory extraction is proposed. Methodologies of traffic information extraction like traffic flow, space mean speed, density, vehicle trajectory, and vehicle travel path are proposed. Based on the traffic information, the traffic fundamental diagrams for various cases including different lanes and various aggregation time are proposed. Based on case study results, the error of extracted volume and manually count volume is less than 20% for most of the aggregation time intervals. Traffic volumes are overestimated because of the multiple returns points of trucks. Traffic status can be divided into four regions: free flow, interactive flow, output constrained flow, and jammed flow. Space mean speed is only lightly influenced by density in the free flow region where speed limits control. With increasing density, vehicles interact with each other reducing the space mean speed as faster vehicles are slowed with fewer opportunities to pass slower vehicles. The third region proposed is the output constrained flow regime where the space mean speed is determined by the available space for vehicles to advance. Finally, the jammed region occurs when vehicles are stopped by queued traffic. Space mean speed and density can be described as a linear relationship in both the free flow and interactive regimes. The traffic flow and density have a polynomial relationship for both free flow and interactive regimes. Based on the regression equations for each lane at different locations, the general form of Greenshields’ models relating traffic flow, density and space mean speed: q=kv can be supported. The speed-density relationship in this study differs from Greenshields’ in significant and non-linear ways. Greenshields’ fundamental diagrams did not identify different regions identified in this work.
Jonathan Corey, Ph.D. (Committee Chair)
Sivaraman Balachandran, Ph.D. (Committee Member)
Andrew Rohne, M.ENG. (Committee Member)
Heng Wei, Ph.D. (Committee Member)
170 p.
Civil Engineering
Fundamental Diagram; ESR Data; Vehicle Travel Path; Vehicle Trajectory

Recommended Citations

Citations

  • Ren, H. (2018). Exam of the Relationship of Traffic Flow, Density and Speed with RADAR Data [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535382803620171

    APA Style (7th edition)

  • Ren, Hui. Exam of the Relationship of Traffic Flow, Density and Speed with RADAR Data. 2018. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535382803620171.

    MLA Style (8th edition)

  • Ren, Hui. "Exam of the Relationship of Traffic Flow, Density and Speed with RADAR Data." Doctoral dissertation, University of Cincinnati, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535382803620171

    Chicago Manual of Style (17th edition)

ucin1535382803620171
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This open access ETD is published by University of Cincinnati and OhioLINK.