The use of self-monitoring solutions amongst cyclists: An online survey and empirical study

Self-monitoring has been shown to be one of the most efficient behaviour change techniques to promote physical activity. However, there has been no research on the exact nature and impact of using various self-monitoring solutions (e.g. cycle computer, cadence monitor, smartphone’ physical activity apps) amongst cyclists. Initially, an online survey was conducted with 227 adults who did or did not use self-monitoring solutions with their cycling. We found that the most important features for cyclists who use self-monitoring are: time it takes to travel, cycling speed, and distance covered. In contrast, cyclists who do not use self-monitoring perceived features related to location (e.g. directions with maps) as the most important ones. In a subsequent study we included self-monitoring solutions as a part of mixed-design, small-scale, longitudinal intervention aimed at changing transportation patterns. We found that self-monitoring is mainly suitable for performance oriented cyclists rather then recreational cyclists. We discuss the implications of those results for designing interventions to promote cycling.     

Categorizing bicycling environments using GPS-based public bicycle speed data

A promising alternative transportation mode to address growing transportation and environmental issues is bicycle transportation, which is human-powered and emission-free. To increase the use of bicycles, it is fundamental to provide bicycle-friendly environments. The scientific assessment of a bicyclist’s perception of roadway environment, safety and comfort is of great interest. This study developed a methodology for categorizing bicycling environments defined by the bicyclist’s perceived level of safety and comfort. Second-by-second bicycle speed data were collected using global positioning systems (GPS) on public bicycles. A set of features representing the level of bicycling environments was extracted from the GPS-based bicycle speed and acceleration data. These data were used as inputs for the proposed categorization algorithm. A support vector machine (SVM), which is a well-known heuristic classifier, was adopted in this study. A promising rate of 81.6% for correct classification demonstrated the technical feasibility of the proposed algorithm. In addition, a framework for bicycle traffic monitoring based on data and outcomes derived from this study was discussed, which is a novel feature for traffic surveillance and monitoring.     

Characterising group-cycling journeys using interactive graphics

The group-cycling behaviours of over 16,000 members of the London Cycle Hire Scheme (LCHS), a large public bikeshare system, are identified and analysed. Group journeys are defined as trips made by two or more cyclists together in space and time. Detailed insights into group-cycling behaviour are generated using specifically designed visualization software. We find that in many respects group-cycle journeys fit an expected pattern of discretionary activity: group journeys are more likely at weekends, late evenings and lunchtimes; they generally take place within more pleasant parts of the city; and between individuals apparently known to each other. A separate set of group activity is found, however, that coincides with commuting peaks and that appears to be imposed onto LCHS users by the scheme’s design. Studying the characteristics of individuals making group journeys, we identify a group of less experienced LCHS cyclists that appear to make more spatially extensive journeys than they would do normally while cycling with others; and that female cyclists are more likely to make late evening journeys when cycling in groups. For 20% of group cyclists, the first journey ever made through the LCHS was a group journey; this is particularly surprising since just 9% of all group cyclists’ journeys are group journeys. Moreover, we find that women are very significantly (p < 0.001) overrepresented amongst these ‘first time group cyclists’. Studying the bikeshare cyclists, or bike share ‘friends’, that individuals make ‘first time group journeys’ with, we find a significantly high incidence (p < 0.001) of group journeys being made with friends of the opposite gender, and for a very large proportion (55%) of members these first ever journeys are made with a friend that shares the same postcode. A substantial insight, then, is that group cycling appears to be a means through which early LCHS usage is initiated.     

Safety-oriented bicycling and traffic accident involvement

Many U.S. bicyclists are killed or injured in traffic accidents annually. Based on analysis of available research and published reports on traffic accidents, it was theorized that adherence to six safety-oriented on-road bicycling practices will reduce involvement in traffic accidents. This study investigated whether adherence to these safety-oriented bicycling practices is associated with reduced involvement in traffic accidents. U.S. adult bicycle riders responded to an anonymous on-line survey covering bicycling practices, recent traffic accident experiences, and potential confounding variables. Participants were recruited via on-line announcements to bicycling-related organizations. The results suggested that neither vigilance nor cautiousness will protect adult bicycle riders from traffic accident involvement, but predictability might reduce accident risk, particularly for younger adults. Results should be interpreted cautiously due to limitations in the study methodology. Further research of this type is warranted.This paper is a re-formulation of research originally presented as a conference paper and oral presentation at the International Cycling Safety Conference in Bologna, Italy, 3–4 November 2016.     

Effects of e-bikes on bicycle use and mode share

In Norway, as in many countries, a political goal is to increase bicycle use, and the e-bike is promising in this respect. However, concerns have been raised about mode-share effects. It has been argued that if the e-bike’s only function is in cycling becoming cycling with electric assistance, there would be no benefit to either the environment or public health. Little is yet known about the use of the e-bike, or of its potential in reducing motorized travel. In the current study, 66 randomly selected participants were given an e-bike to use for a limited period of time and the results compared with those of a control group (N = 160). E-bike cycling trips increased from 0.9 to 1.4 per day, distance from 4.8 km to 10.3 km and, as a share of all transport, from 28% to 48%, whereas with the control group there was no increase in cycling. The effect of the e-bike increased with time, indicating a learning effect among users, and was greater for female than for male cyclists. There were no differences with age. Overall, the results suggest that the e-bike is indeed practical for everyday travel.     

The factors influencing bicycling in the Bangalore city

Bicycling, in an urban context, have many benefits, compared with motorized transports, like reduced carbon footprint, and lower maintenance, health, social and infrastructural costs. The present paper analyses the various factors contributing to a low percentage of bicycling in the Bangalore city and elicits certain policy aspects to improve the attractiveness of bicycling. The study focuses mainly on the behavioral aspects of commuters pertaining to their childhood and current scenario, and uses a face-to-face questionnaire survey for data collection. These behavioral aspects indicated a commuter’s perception about social expectation, convenience and bicycling infrastructure using a 5-point Likert scale measurement. Information is also collected about factors that might motivate bicycling, and about demographic variables like age, gender, income, etc. The study used a statistical z-test to identify the most influential attitudinal factors and to check whether the various factors are significantly different. The results gave a clear picture about the most dominant attitudinal factors that resulted in the stoppage of bicycling during a commuter’s childhood, and that acted as a deterrent to their bicycle usage in a current scenario. The study determined a need for changing the attitude of people towards cycling by programs that would create a positive image for cycling. There was also a need for segregated cycle lanes and signals at intersections so that people could feel safe while travelling on cycles.     

An exploration of the importance of social influence in the decision to start bicycling in England

The purpose of this paper is to gain a better understanding, through qualitative exploration, of the ways in which social influence affects the decision to start bicycling in England. ‘Social influence’ is defined as the process by which an individual’s thoughts and actions are changed by the thoughts and action of others. Its role was investigated at three levels: the immediate family, household members and significant others (direct social influence); the extended family, friends, peers and colleagues (less direct social influence); and the wider cultural context (indirect social influence). Interviews with 61 individuals living in 12 towns and cities across England were analysed. Half of the interviewees were new regular bicyclists and the other half did not bicycle at all, or only occasionally. Social influence was found to be the dominant factor for a minority of the cases where participants started bicycling regularly. It played a role alongside other factors in other cases. It could take the form of direct influence from family, friends and peers or indirect influence from the social and cultural context. The analysis illustrates the difficulty of capturing social influence which is often hidden and emerges incidentally in the course of the interviews and interacts with other contributing factors. The role of social influence found in this research challenges the rational approach to explaining travel decision making that has traditionally dominated transport studies. The paper suggests that social processes could be harnessed to improve the efficacy of bicycling promotion programs.     

Bikeshare trip generation in New York City

Cities around the world and in the US are implementing bikesharing systems, which allow users to access shared bicycles for short trips, typically in the urban core. Yet few scholars have examined the determinants of bikeshare station usage using a fine-grained approach. We estimate a series of Bayesian regression models of trip generation at stations, examining the effects bicycle infrastructure, population and employment, land use mix, and transit access separately by season of the year, weekday/weekend, and user type (subscriber versus casual). We find that bikeshare stations located near busy subway stations and bicycle infrastructure see greater utilization, and that greater population and employment generally predict greater usage. Our findings are nuanced, however; for instance, those areas with more residential population are associated with more trips by subscribers and on both weekdays and non-working days; however, the effect is much stronger on non-working days. Additional nuances can be found in how various land use variables affect bikeshare usage. We use our models, based on 2014 data, to forecast the trips generated at new stations opened in 2015. Results suggest there is large variation in predictive power, partly caused by variation in weather, but also by other factors that cannot be predicted. This leads us to the conclusion that the nuances we find in our inferential analysis are more useful for transportation planners.