Abstract
Abstract. In contrast to cars, route choices for cycling are barely influenced by the respective traffic situation, but to a large extent by the routes’ comfort. Especially in urban settings with several alternatives, segments with many or long stops at traffic lights and badly maintained roads are avoided due to a low comfort and cyclists vary from the shortest route. This fact is only indirectly considered in common navigation applications.This work aims to integrate surface roughness measurements collected from diverse bicycles to a joint scale via a least-squares adjustment. Data was collected using smartphones, which were mounted to bike hand bars and measured positions and vertical accelerations on user’s trips. As this way sensed roughness also depends on the bike setting and type, the resulting values would be different for different users. Thus, this paper presents a novel approach to harmonize observations from differing sensitive setups. The basic concept idea of bundle block adjustment is adapted to calibrate a basic scale model and in parallel adjust the observations of surface roughness to a common scale.This way a crowd-sourced roughness map can be generated. Such a map can be used to enrich bike focused routing services and thus encourage cycling in daily live. In addition, it can also be used to derive hints for infrastructure servicing.
Highlights
AND RELATED WORKDue to the wide availability on smartphones, navigation applications are no longer used only for driving in unknown surroundings, and for everyday rides by bicycle
In contrast to the car where route choice is mainly influenced by estimated travel time, cyclists rather look for comfortable routes
To avoid situations with low comfort like gradients, many or long stops at traffic lights and badly maintained roads, cyclists vary from the shortest route ((McCarthy et al, 2016),)
Summary
Due to the wide availability on smartphones, navigation applications are no longer used only for driving in unknown surroundings, and for everyday rides by bicycle. There is already a routing service, Komoot (komoot GmbH, 2021), based on OSM surface tags, but this requires a prior manual labeling of the paths by volunteers (Bike Citizens Mobile Solutions GmbH, 2021) from Austria offers a navigation app for cyclists similar to Komoot, and promotes the recording and uploading of the trajectory traveled during use This is analyzed in comparison to the shortest routes to adapt future recommendations. The focus of the development, data recording and analysis was placed on capturing the way surface conditions Published works such as (Bıl et al, 2015), (Dawkins et al, 2011) and (Wage et al, 2020) have shown that vertical acceleration measurements on bicycles (and other vehicles) can provide information about the roughness (or smoothness) of the ground. As a solution to this problem, we present an approach for adjusting data collected from diverse cyclists relatively to each other and into a joint roughness level
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