How comfortable are your cycling tracks? A new method for objective bicycle vibration measurement

Bíl, Michal; Andrášik, Richard; Kubeček, Jan

doi:10.1016/j.trc.2015.05.007

Cited by 78 publications

(59 citation statements)

References 23 publications

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“…Future work includes the expansion of the risk and discomfort estimation with exposure and vibration measures [17,4], the study and comparison of several other cities [9], the influence of other traffic in cycling safety as well as the design of traffic simulation models for the participatory multi-objective optimization of traffic flows [16,1,12].…”

Section: Discussionmentioning

confidence: 99%

On cycling risk and discomfort: urban safety mapping and bike route recommendations

2019

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Bike usage in Smart Cities becomes paramount for sustainable urban development. Cycling provides tremendous opportunities for a more healthy lifestyle, lower energy consumption and carbon emissions as well as reduction of traffic jams. While the number of cyclists increase along with the expansion of bike sharing initiatives and infrastructures, the number of bike accidents rises drastically threatening to jeopardize the bike urban movement. This paper studies cycling risk and discomfort using a diverse spectrum of data sources about geolocated bike accidents and their severity. Empirical continuous spatial risk estimations are calculated via kernel density contours that map safety in a case study of Zurich city. The role of weather, time, accident type and severity are illustrated. Given the predominance of self-caused accidents, an open-source software artifact for personalized route recommendations is introduced. The software is also used to collect open baseline route data that are compared with alternative ones that minimize risk or discomfort. These contributions can provide invaluable insights for urban planners to improve infrastructure. They can also improve the risk awareness of existing cyclists' as well as support new cyclists, such as tourists, to safely explore a new urban environment by bike.

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Section: Discussionmentioning

confidence: 99%

On cycling risk and discomfort: urban safety mapping and bike route recommendations

2019

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“…This section discusses two distinctive elements-traditional pavement distress that is caused by asphalt fatigue or a quality disorder, and on-purpose devices that are applied for safety such as speed humps. Poor surface pavement quality leads to bicycles using the pavement to vibrate, which strongly influences the users' perceptions of a given cycle track, general cycling comfort and the choice of route [115]. However, there has been little attention paid to cycling infrastructures and pavement quality [29].…”

Section: Pavement Conditionsmentioning

confidence: 99%

“…Thigpen et al [119] conducted a study in the US and found that the surface macrotexture and roughness of a given bike path can strongly affect cyclists' comfort. Bíl et al [115] proposed a dynamic comfort index in order to evaluate the vibration that occurred due to issues with the surface of the pavement's properties. They applied this method to an entire road network within the center of Olomouc in the Czech Republic.…”

Section: Pavement Conditionsmentioning

confidence: 99%

Expanding the Scope of the Bicycle Level-of-Service Concept: A Review of the Literature

et al. 2020

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Research into the bicycle level-of-service (BLOS) has been extensively conducted over the last three decades. This research has mostly focused on user perceptions of comfort to provide guidance for decision-makers and planners. Segments and nodes were studied first, followed by a network evaluation. Besides these investigations, several variables have also been utilized to depict the users’ perspectives within the BLOS field, along with other cycling research domains that simultaneously scrutinized the users’ preferences. This review investigates the variables and indices employed in the BLOS area in relation to the field of bicycle flow and comfort research. Despite general agreement among existing BLOS variables and the adopted indices, several important research gaps remain to be filled. First, BLOS indices are often categorized based on transport components, while scarce attention has been paid to BLOS studies in trip-end facilities such as bicycle parking facilities. The importance of these facilities has been highlighted instead within research related to comfort. Second, the advantages of separated bike facilities have been proven in many studies; however, scarce research has addressed the challenges associated with them (e.g., the heterogeneity within those facilities due to the presence of electric bikes and electric scooters). This issue is clearly noticeable within the research regarding flow studies. Furthermore, network evaluation (in comparison to segment and node indices) has been studied to a lesser extent, whereas issues such as connectivity can be evaluated mainly through a holistic approach to the system. This study takes one step toward demonstrating the importance of the integration of similar research domains in the BLOS field to eliminate the aforementioned shortcomings.

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“…As it is a quite costly process, cyclists' route choices have often been surveyed in order to obtain reliable data which would favor the cyclists' needs and demands. Among the demands, comfort seems to be highly desired when choosing a path [2].…”

Section: Introductionmentioning

confidence: 99%

“…Different road surfaces affect cyclists' perception of comfort differently, whereas smoother surfaces are generally preferred yielding optimal comfortable features for riding and thereby requiring lower energy output. Oppositely, rougher road types that are less comfortable and harder to ride have shown to discourage certain cyclists from riding upon such surfaces [2,5,6].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Road Surface Quality during Cycling Using Smartphone Accelerometer Data

Litzenberger

Christensen

Hofstätter

et al. 2018

The 12th Conference of the International Sports Engineering Association

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Many cyclists use online-maps for planning their routes, however, only little information is known about the road surface of different cycling paths, farm or public roads. Cyclists prefer road surfaces fitting the type of bike they are using for a specific ride (e.g., time trial, road, MTB, cyclocross, gravel bike). Often riders upload their ride data including GPS, heart rate (HR) or power (P) on platforms like Strava or Garmin Connect. In this research we tried to evaluate whether it is possible to (1) evaluate the road surface quality using a 3D accelerometer mounted on the bicycle's fork (f = 500 Hz) and whether (2) results of similar quality can be achieved using the accelerometer of a smartphone (f = 100 Hz) placed in the cyclist's pocket. For data acquisition a cyclist rode on a cyclocross bicycle on three different road surfaces (cobblestones, gravel and tarmac) with three different speeds (10, 20 and 30 km/h) and three different tire pressures (3, 4 and 5 bar). Data of both measuring systems were analyzed using machine learning algorithms. Results showed that road surfaces could be predicted with more than 99% accuracy with the accelerometer and with more than 97% with the smartphone-data.

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How comfortable are your cycling tracks? A new method for objective bicycle vibration measurement

Cited by 78 publications

References 23 publications

On cycling risk and discomfort: urban safety mapping and bike route recommendations

On cycling risk and discomfort: urban safety mapping and bike route recommendations

Expanding the Scope of the Bicycle Level-of-Service Concept: A Review of the Literature

Prediction of Road Surface Quality during Cycling Using Smartphone Accelerometer Data

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