The influence of pedestrian crossings features on driving behavior and road safety

Abstract

The paper deals with the identification of variables and models that can explain why a certain Severity Level (SL) may be expected in the event of a certain type of crash at a specific point of an urban road network. Two official crash records, a weather database, a traffic data source, and information on the characteristics of the investigated urban road segments of Turin (Italy) for the seven years from 2006 to 2012 were used. Examination of the full database of 47,592 crash events, including property damage only crashes, reveals 9,785 injury crashes occurring along road segments only. Of these, 1,621 were found to be associated with a dataset of traffic flows aggregated in 5 minutes for the 35 minutes across each crash event, and to weather data recorded by the official weather station of Turin. Two different approaches, a back-propagation neural network model and a generalized linear mixed model were used. Results show the impact of flow and other variables on the SL that may characterize a crash; differences in the significant variables and performance of the two modelling approaches are also commented on in the manuscript.of the research studies have been focused on the likelihood of a crash without considering the crash outcome severity.

The safety and conspicuity of pedestrian crossing at roundabouts: The effect of median refuge island and zebra markings

“…The drivers' attention focused on the roadway with a decrease of distraction caused by the surrounding road environment. According to Bichicchi et al (2017), zebra markings and median refuge island were the best perceived elements by all drivers, with a median fixation duration respectively of 700 ms, followed by ''Yield here to pedestrians" vertical sign (300 ms).…”

Assessment pedestrian crossing safety using vehicle-pedestrian interaction data through two different approaches: Fixed videography (FV) vs In-Motion Videography (IMV)

“…Literature review Investigation of pedestrian behavioral parameters as well as traffic characteristics of pedestrian crossings plays an important role in identifying effective factors in pedestrian accidents. The effects of environmental and traffic characteristics, as well as other road users' behaviors have led to the complexity of the analysis of pedestrian crossing behaviors (Bichicchi et al, 2017;Etehad et al, 2015;Khattak & Tung, 2015;Ram & Chand, 2016;Sheykhfard & Haghighi, 2019;Wang et al, 2018). So far, numerous studies have evalutated pedestrian safety using various methods.…”

A Decision Support System for the Safety Evaluation of Urban Pedestrian Crossings

“…It has been also observed that increased intensity of road lighting decreases the number of accidents with pedestrian of 59%. Similarly, increased intensity of roadway lightning and installation of flashing warning signs acts with a reduction of pedestrian crashes of 57% in nighttime and a significant decrease in daytime, about 21%(Zgeer et al, (2006);Nassar et al, (2011);Scott et al, (2012);Bassani et al, (2012);Niaki et al, (2014);Bichicchi et al, (2017);Gibbons at al., (2015);Wei et al, (2016); Bullough et al, (2017 Bullough et al, ( ), (2021;Wang et al, (2018);Gbologah et al, (2019);Bhagavathula et al, (2019Bhagavathula et al, ( ), (2020;Costa et al, (2017), (…”