The number of both recreational and utilitarian bicycle trips often drops significantly during the winter months. This is especially the case in the Nordic countries [1, 6, 15, 40] and some parts of Northern America with harsh winters [3, 21, 42, 46]. Fournier et al. [22] found that in areas with harsh winters (in the northern hemisphere), the seasonal bicycle usage can be estimated with a sinusoidal model peaking on July 1 and being at the minimum on January 1. The most prominent “barriers” to winter cycling have been identified to be cold temperatures, increased precipitation, darkness and inclement road conditions [6, 8, 26, 36, 48].
There is a widespread political desire to increase bicycle usage throughout the year because it can relieve the pressure on overcrowded metros and buses [49]. More cycling also leads to benefits in terms of public health, travel-time reliability, cost-effectiveness, reduced congestion and pandemic resilience [7, 20, 30, 33, 52]. Due to the acknowledged benefits, several governments have set official goals for increased cycling. The current Norwegian National Transport Plan (2018–2029) states that walking and cycling should cover 40–60% of all passenger traffic increases in urban areas [39]. Finland’s new energy and climate strategy include an official national goal to increase the number of trips made by bicycle or foot to 30% by 2030 [29]. Sweden published a national strategy dedicated to more and safer cycling and invested 100 million SEK in promoting cycling in a 2016–2017 initiative [47]. Malone [34] analyzed cycling policies that have been deployed in several European cities in a report produced for EU city planners, decision-makers and citizens. The report underlines that a successful cycling policy can only be achieved by an organization with knowledge and cycling data. Malone indicates that municipalities should build this knowledge by developing relationships with engineering firms, schools, cycling associations and consultants.
The goal of deploying cycling policies is to increase cycling by inducing changes in the factors determining people’s cycling habits, i.e., cycling determinants. Previous research has documented these factors thoroughly. Pucher and Buehler [44] summarize the majority of academic research on how to increase cycling in cities and make it safer for all society segments. Heinen et al. [28] present a comprehensive review of the academic literature on the dominant factors affecting people’s decision to cycle or not. To summarize, the cycling determinants can be divided into four main categories, namely the natural environment (weather and topography), the built environment (infrastructure and land-use mix), temporal factors (calendar-events and time of day), and other (individual and cultural) factors. An et al. [4], Butterworth and Pojani [9], Schneider [45], Willis et al. [56] have later written complementary overviews on this topic.
To increase cycling, one can induce changes in the cycling determinants to either recruit new cyclists or increase current cyclists’ cycling frequency. To recruit new cyclists, there is often a need to reduce cultural or personal barriers such as a negative attitude towards cycling or work and family commitments. Occasional cyclists are often reluctant to increase their cycling frequency due to flexibility and practical matters, for example, if they need to transport cargo during the day [23]. Moreover, to encourage summer cyclists to cycle more during the winter, proper winter maintenance, especially snow removal, is essential [6, 37, 50, 51]. However, to evaluate the cost-benefit of improved winter maintenance, there is still a need for more knowledge about the actual effect of improved winter maintenance [55].
The purpose of winter maintenance is to improve the road surface conditions. During the winter, snow and ice on the roads often reduce skid resistance and steerability and increase cycling resistance and unevenness. Quantifiable surface quality measurements are important to evaluate the effect of winter maintenance performances on infrastructure winter resilience [57]. Friction measurements have been used to quantify the skid resistance, and an adequate friction level is essential for cycling safety [37, 38].
Another quantifiable measure of the surface conditions is rolling resistance. The rolling resistance increase with increasing loose snow depths and unevenness [13, 19, 32, 54]. The rolling resistance is also highly dependent on the bicycle properties, i.e., tire rubber properties, inflation pressure and contact area [12, 24]. Previous research has found a nearly linear relationship between wheel load, i.e., the average contact pressure times the contact area between the wheel and the road surface, and rolling resistance force [5, 11, 24, 25]. The coefficient of rolling resistance, Crr, has therefore been established to compare rolling resistances for different wheel loads:
$$ {C}_{rr}=\frac{F_r}{F_N} $$
where Fr is the rolling resistance force and FN is the wheel load.
Fenre and Klein-Paste [18] developed a new method for estimating bicycle rolling resistance on cycleways by measuring propulsive and resistive forces on a moving bicycle. This method considers pedaling power, air drag forces, inertial forces, and gravity forces. The method is suitable for rolling resistance measurements at variable speeds, variable weather conditions, and any road gradient. This method was utilized to investigate how bicycle rolling resistance is affected by typical winter conditions on cycleways. These investigations found a strong correlation between the rolling resistance level and snow type, loose snow depth, and unevenness [19]. Moreover, there seems to be knowledge gap about how the rolling resistance level correlates to people’s willingness to cycle. This knowledge can help determine how various winter maintenance actions affect the urban infrastructure resilience during wintertime.
In this study, we used an online survey to collect data about people’s willingness to cycle on various winter cycling conditions shown in photos. We compared the cycling willingness results to rolling resistance measurements of the same conditions collected in a previous study [19] and investigated how people’s stated willingness to cycle is affected by the rolling resistance level.