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- W577115087 abstract "Studies have shown that crash fatalities involving bicyclists and pedestrians have often been attributed to inadequate visibility conditions on roads, particularly at nighttime with street lights as the mostly available light source. Outdoor visibility varies with the time-of-the day and often due to altering weather conditions, such as sunny, cloudy or rainy. Therefore, from what authors have found from exhaustive references and literature reviews, street visibility issues, albeit important, have never been addressed in research in any of the earlier or existing path finding paradigms. This paper presents a street visibility-based path finding methodology to help in the decision making of bicyclists and pedestrians in choosing safe paths. In this paper, street’s visibility is measured by its ‘level of lux’ using LuxMeter, a free iPhone app. Subsequently, a multi-objective shortest path algorithm is developed that identifies the best path (the non-inferior path) from among p-highest level of lux paths considering travel time. An example application of the proposed methodology is demonstrated on the bicycle and pedestrian street network system obtained from the City of College Station, Texas. It is observed that the best path(s) found during daytime, cloudy and nighttime conditions for the two modes are sensitive to the travel time and visibility conditions on the streets. This research contributes to the state-of-the-art practice for all safety studies that would address visibility as an important issue for bicyclists and pedestrians. Further, the street visibility-based path finding methodology developed in this paper can be integrated with modern-day route planning tools (such as GPS) for an improved route guidance system for bicyclists and pedestrians within an Intelligent Transportation Systems (ITS) framework." @default.
- W577115087 created "2016-06-24" @default.
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- W577115087 date "2015-01-01" @default.
- W577115087 modified "2023-09-24" @default.
- W577115087 title "Street Visibility-Dependent Path Finding for Pedestrians and Bicyclists in Urban Areas" @default.
- W577115087 hasPublicationYear "2015" @default.
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