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Abstract
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Background
Conflict analysis appears more important for pedestrian and bicyclist safety assessment than crashes alone because willingness to walk and bicycle depends significantly on perceptions of safety. Understanding and identifying the rate of conflicts on a segment of intersection also may provide a better source of data for local decision-makers because crash data due to its infrequent occurrence rate may not identify a location as dangerous until a fatality or injury occurs. Conflicts between vehicles, pedestrians and bicyclists occur at both intersections and street segments. The study seeks to develop a surrogate safety measure using conflict analysis, which considers conflict categories (severity of conflicts) and safety impact.
Methods
The research team identifies conflict characteristics that influence the potential seriousness of the conflict and five conflict types: Pedestrian - Vehicle Bicyclist - Vehicle Pedestrian - Bicyclist Vehicle - Bicyclist (Overtaking) Bicyclist - Pedestrian (Overtaking) The study surveys a panel of 132 experts from national transportation, planning, and public health agencies and advocacy organizations to calibrate the conflict safety and severity for each of these categories. The electronic survey uses a scenario approach to gather their feedback and obtains a response rate of 36% (n=47). The survey uses skip-logic, which allows respondents to self-identify their areas of expertise and directs them to the appropriate survey questions.
Results
The experts evaluate different levels of the conflict characteristics to grade the conflict severity based on the vulnerable road user and place it into one of four categories, A to D, and evaluate the likelihood the crash occurrence safe (no likelihood), moderately safe (low likelihood) or not safe (high likelihood). For pedestrian-vehicle conflicts, two findings stand out. Severity level increases even as the distance between pedestrian and vehicles decreases when emergency evasive actions must be taken. For short distances, irrespective of evasive action type, the survey respondents rated the conflict type as category A and labeled the situation not safe. The survey respondents give more weight to separation distance when rating a conflict situation for crash likelihood. The research team has developed a survey form and an Android app that can be used to collect conflict data in the field.
Conclusions
Coupled with crash data, understanding the conflict patterns and their possible causes can help transportation agencies make strategic decisions about active transportation investments. Moreover, conflict measures can act as a sketch planning level performance measure to understand potential safety issues related to transportation facilities. |