Interest has grown in using traffic conflicts for studying safety from a broader perspective than relying only on collision data. Traffic conflict analysis is typically performed through the calculation of traditional conflict severity measures such as time-to-collision and postencroachment time. These measures rely on road users getting within specific temporal and spatial proximity from each other and therefore assume that proximity is the surrogate for severity. However, this assumption may not be valid in some driving environments where close interactions between road users are common and sudden evasive actions are frequently used to avoid collisions. It is suggested that evasive action–based conflict indicators can assess the analysis in some less-organized traffic environments. This study focused on the severity evaluation of pedestrian conflicts. Pedestrian evasive actions were reflected mainly in variations of spatiotemporal gait parameters (step frequency and step length). The objective was to compare the use of time proximity and evasive action–based conflict indicators in evaluating the severity of pedestrian conflicts in different traffic environments. Video data from intersections in five major cities—Shanghai, China; New Delhi, India; New York City; Doha, Qatar; and Vancouver, British Columbia, Canada—were analyzed with automated computer vision techniques to extract pedestrian-involved conflicts and calculate conflict indicators. Results show that evasive action–based indicators were more effective in identifying and measuring the severity of pedestrian conflicts than time proximity measures in traffic environments such as Shanghai and New Delhi. However, evasive action measures did not show the same potential in Vancouver and Doha, where time proximity measures were more effective.


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    Titel :

    Comparison of Time-Proximity and Evasive Action Conflict Measures: Case Studies from Five Cities


    Weitere Titelangaben:

    Transportation Research Record


    Beteiligte:
    Tageldin, Ahmed (Autor:in) / Sayed, Tarek (Autor:in) / Shaaban, Khaled (Autor:in)


    Erscheinungsdatum :

    2017-01-01




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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