Abstract
Non-motorized transportation modes, especially cycling and walking, offer numerous benefits, including improvements in the livability of cities, healthy physical activity, efficient urban transportation systems, less traffic congestion, less noise pollution, clean air, less impact on climate change and decreases in the incidence of diseases related to vehicular emissions. Considering the substantial number of short-distance trips, the time consumed in traffic jams, the higher costs for parking vehicles and restrictions in central business districts, many commuters have found that non-motorized modes of transportation serve as viable and economical transport alternatives. Thus, local governments should encourage and stimulate non-motorized modes of transportation. In return, governments must provide safe conditions for these forms of transportation, and motorized vehicle users must respect and coexist with pedestrians and cyclists, which are the most vulnerable users of the transportation system. Although current trends in sustainable transport aim to encourage and stimulate non-motorized modes of transportation that are socially more efficient than motorized transportation, few to no safety policies have been implemented regarding vulnerable road users (VRU), mainly in large urban centers. Due to the spatial nature of the data used in transport-related studies, geospatial technologies provide a powerful analytical method for studying VRU safety frameworks through the use of spatial analysis. In this article, spatial analysis is used to determine the locations of regions that are characterized by a concentration of traffic accidents (black zones) involving VRU (injuries and casualties) in São Paulo, Brazil (developing country), and Rome, Italy (developed country). The black zones are investigated to obtain spatial patterns that can cause multiple accidents. A method based on kernel density estimation (KDE) is used to compare the two cities and show economic, social, cultural, demographic and geographic differences and/or similarities and how these factors are linked to the locations of VRU traffic accidents. Multivariate regression analyses (ordinary least squares (OLS) models and spatial regression models) are performed to investigate spatial correlations, to understand the dynamics of VRU road accidents in São Paulo and Rome and to detect factors (variables) that contribute to the occurrences of these events, such as the presence of trip generator hubs (TGH), the number of generated urban trips and demographic data. The adopted methodology presents satisfactory results for identifying and delimiting black spots and establishing a link between VRU traffic accident rates and TGH (hospitals, universities and retail shopping centers) and demographic and transport-related data.
Highlights
One key element of modern transportation systems is safety
This literature review mainly discusses three aspects related to the spatial characterization of hot spots involving vulnerable road users (VRU), traffic accident research, accidents involving VRU and the spatial analysis of these accidents
The objectives of kernel density estimation (KDE) analysis were to identify: (1) the spatial locations of black spots; (2) the attributes of each accident inside the black spot zones (address, road type, accident type, vehicle(s) involved and date/time); (3) the attributes of the region delimited by the black spots; and (4) the number and spatial locations of the entities considered in this study as trip generator hubs (TGH) inside the black spot zones
Summary
One key element of modern transportation systems is safety. The goal of safety is to minimize the number of accidents and to reduce the severity of injuries for all users, including motorists, passengers of particular vehicles, public transport commuters, cyclist and pedestrians [1,2].Traffic accidents result in the second highest cost of transportation. The goal of safety is to minimize the number of accidents and to reduce the severity of injuries for all users, including motorists, passengers of particular vehicles, public transport commuters, cyclist and pedestrians [1,2]. Middle-income countries, which are becoming motorized rapidly, are the hardest hit by traffic accidents, with approximately 70% of traffic-related deaths occurring in these countries [16,17]. This tragic scenario indicates that traffic accidents are a serious public health and welfare concern and can be considered as a global epidemic [12]. In Brazil, 4% of the individuals that died from traffic accidents were cyclists and 23% were pedestrians in 2010 [18]
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