Between 2005 and 2007 there were 9071 traffic accidents involving bicycles within London and this paper demonstrates the utility of Geographic Information Systems as a tool for analysing and visualising these occurrences. Through linkage of these spatial locations to a street network dataset it was possible to create a variety of intelligence about the types of street infrastructure where accidents predominantly occur. Additionally, a network routing algorithm was adapted to account for the frequency of accidents within a series of proposed journeys. This pilot routing application compared the quickest route with an accident avoidance weighted route between a series of origins and destinations. The results demonstrated that the routes avoiding areas of high accident volume did not increase journey length significantly; however they did provide a “safer” route based on empirical evidence over the volume of accident locations. 1. Introduction Cycling has grown in popularity as a method of travel in London over the past ten years, with Transport for London (TFL) estimating that around 2% of all journeys are now being made by bicycle which is a rise of 0.8% since the year 2000 [1]. Although in percentage terms this is small when compared to all other modes of available travel, this does however equate to 545,000 individual daily bicycle journeys [2]. The choice of whether to cycle or not is complex, and there is a plethora of literature that identifies numerous influencing factors associated with this decision making process. The literature on this area is comprehensively reviewed elsewhere, and as such will not be repeated here [3]. This paper concerns the spatial analysis of data detailing the locations of all cycling accidents in London between 2005 and 2007. These data define an accident as those cycling incidences involving a personal injury, occurring on a public highway and consequently being reported to the police. During the 2005–2007 time period there were a total of 9071 such accidents in London, with accidents rising from 2977 in 2005 to 3058 in 2007 (~2.7% increase). Of those accidents occurring in 2007, 461 resulted in the road user being killed or seriously injured [4]. The aim of this study is to create a series of maps which represent the spatial concentration of accidents occurring within the London street network and to further use this information to inform a pilot automated service that provides cycle routing options which avoid areas of recorded high accident volumes. There is much previous international literature related to cycling
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