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Lan Wu MS Thesis.pdf (2.07 MB)

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IMPROVED VEHICLE LENGTH MEASUREMENT AND CLASSIFICATION FROM FREEWAY DUAL-LOOP DETECTORS IN CONGESTED TRAFFIC

Wu, Lan
http://rave.ohiolink.edu/etdc/view?acc_num=osu1387558066

Abstract Details

2014, Master of Science, Ohio State University, Civil Engineering.
Classified vehicle counts are a critical measure for forecasting the health of the roadway infrastructure and for planning future improvements to the transportation network. Balancing the cost of data collection with the fidelity of the measurements, length-based vehicle classification is one of the most common techniques used to collect classified vehicle counts. Typically the length-based vehicle classification process uses a pair of detectors to measure effective vehicle length. The calculation is simple and seems well defined. In particular, most conventional calculations assume that acceleration can be ignored. Unfortunately, at low speeds this assumption is invalid and performance degrades in congestion. As a result of this fact, many operating agencies are reluctant to deploy classification stations on roadways where traffic is frequently congested. This thesis will first demonstrate that small changes in the calculations used in conventional practice can lead to large differences in performance during challenging conditions. This work considers seven different variations of vehicle length calculation, two of which perform much better than the others in congested freeway conditions down to 15 mph- both under theoretical vehicle motions and empirical data analysis. Then, to further improve performance, we evaluate the feasible range of true vehicle lengths that could underlie a given combination of measured length, measured speed, and unobserved acceleration at dual-loop detectors. From this analysis we find that there are small uncertainty zones between length classes where the particular class is ambiguous. For the vehicles falling into the uncertainty zones we assign them to two or more classes- representing all of the feasible true length classes that could have yielded the measured speed and length. The rest of the length-speed plane can be unambiguously assigned to a single class. Finally, using empirical data these advances are shown to perform better than the current state of the practice, though we find that even the conventional method did surprisingly well in stop-and-go traffic for vehicle length calculation.
Benjamin Coifman (Advisor)
Mard McCord (Committee Member)
Philip Viton (Committee Member)
101 p.
Civil Engineering
Dual-loop detector; Speed and length measurement; Length-based vehicle classification; Freeway traffic; Congested traffic

Recommended Citations

Citations

  • Wu, L. (2014). IMPROVED VEHICLE LENGTH MEASUREMENT AND CLASSIFICATION FROM FREEWAY DUAL-LOOP DETECTORS IN CONGESTED TRAFFIC [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1387558066

    APA Style (7th edition)

  • Wu, Lan. IMPROVED VEHICLE LENGTH MEASUREMENT AND CLASSIFICATION FROM FREEWAY DUAL-LOOP DETECTORS IN CONGESTED TRAFFIC. 2014. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1387558066.

    MLA Style (8th edition)

  • Wu, Lan. "IMPROVED VEHICLE LENGTH MEASUREMENT AND CLASSIFICATION FROM FREEWAY DUAL-LOOP DETECTORS IN CONGESTED TRAFFIC." Master's thesis, Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1387558066

    Chicago Manual of Style (17th edition)

osu1387558066
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This open access ETD is published by The Ohio State University and OhioLINK.