IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v18y2026i14p6974-d1986311.html

Curvature-Based Assessment of Left-Turn Trajectories at Urban Intersections Using Video-Extracted Vehicle Paths

Author

Listed:
  • Panagiotis Lemonakis

    (School of Civil Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Apostolos Anagnostopoulos

    (School of Civil Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Fotini Kehagia

    (School of Civil Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Victoria Zorba

    (Rhoe Urban Technologies, Polytechniou St., 54626 Thessaloniki, Greece)

  • Konstantinos Michopoulos

    (Rhoe Urban Technologies, Polytechniou St., 54626 Thessaloniki, Greece)

  • Evangelos Manthos

    (School of Civil Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

Abstract

Urban intersection design generally assumes that drivers follow idealised turning paths defined by circular arcs and, in some cases, transition curves. In practice, however, observed left-turn trajectories often depart from these theoretical paths. This study proposes a curvature-based framework for quantifying such deviations at the movement level by directly comparing observed vehicle paths with theoretical design arcs derived from intersection geometry. Naturalistic traffic data were collected at five urban intersections in Thessaloniki, Greece, using elevated video cameras. Left-turn passenger-vehicle trajectories were extracted, georeferenced, and compared with corresponding theoretical paths. For each trajectory, a best-fit circular arc was estimated, and the deviation between observed and theoretical path geometry was quantified through radius- and curvature-based percentage indicators. These indicators were then aggregated at the intersection and movement level using medians, deciles and the relative shares of flatter-than-theoretical and tighter-than-theoretical trajectories. The results show that deviations from theoretical geometry are strongly movement-specific and that the strongest flattening and tightening patterns were statistically supported by movement-level Wilcoxon signed-rank tests. In some cases, drivers systematically opened the turn relative to the design path, with median curvature deviations reaching about −14% and flatter-than-theoretical shares as high as 94%. In other cases, the opposite pattern was observed, with median curvature deviations exceeding +37% and tighter-than-theoretical shares reaching 100%. Other movements remained close to the theoretical path or displayed substantial internal heterogeneity. Overall, the proposed framework offers a practical and interpretable way to screen left-turn movements for systematic departure from design intent. This is important because it allows the analysis to move from individual path overlays to a movement-level geometric reading that can support consistency checks, intersection review and future integration with speed- and conflict-based safety analyses. These results should nonetheless be regarded as exploratory and descriptive: neither the circle-fitting residuals nor the coordinate-level geometric accuracy of the extracted trajectories were formally validated in the present study, and the reported RDP/CDP values are, therefore, not intended for use as precision-survey quantities or as a stand-alone design basis.

Suggested Citation

  • Panagiotis Lemonakis & Apostolos Anagnostopoulos & Fotini Kehagia & Victoria Zorba & Konstantinos Michopoulos & Evangelos Manthos, 2026. "Curvature-Based Assessment of Left-Turn Trajectories at Urban Intersections Using Video-Extracted Vehicle Paths," Sustainability, MDPI, vol. 18(14), pages 1-32, July.
  • Handle: RePEc:gam:jsusta:v:18:y:2026:i:14:p:6974-:d:1986311
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/18/14/6974/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/18/14/6974/
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:18:y:2026:i:14:p:6974-:d:1986311. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.