Bicycle Type Research Articles

Sustainable Transportation Characteristics Diary—Example of Older (50+) Cyclists

Cycling is a sustainable and healthy form of transportation that is gradually becoming the primary means of transportation over shorter distances in many countries. This paper describes the dataset used to determine the cycling characteristics of seniors in the USA and Canada. For these purposes, a specially created questionnaire was used in a survey conducted from August 2021 to July 2022. The questionnaire contained sections related to the general socio-demographic characteristics of the respondents, general characteristics of cycling (type of bicycle, cycle time, mileage, etc.), and specific characteristics of cycling (riding in night conditions, termination of cycling, motivating and demotivating factors for cycling, etc.). The total sample consisted of 5096 respondents (50+ years old). This database is particularly significant because it represents the first set of publicly available data related to the cycling characteristics of older adults. The database can be used by various researchers dealing with this topic, but also by the decision-makers who want to design a sustainable and accessible cycling infrastructure, respecting the requirements of this category of users. Finally, this dataset can serve as an adequate basis in the process of determining the specificities and understanding the needs of older cyclists in traffic.

Fracture patterns in bicycle accidents: A descriptive national cohort study of fractures sustained in bicycle accidents in the Swedish Fracture Register 2015–2022

IntroductionBicycle accidents account for the majority of traffic-related accidents in Sweden. Despite the widespread everyday use of bicycles, little is known about the fracture panorama resulting from bicycle accidents. This study analysed the fracture patterns of bicycle accidents in Sweden in regard to fracture type, sex, age, and type of bicycle. Material and methodsWe retrieved data from the Swedish Fracture Register on all fractures caused by bicycle accidents between 2015 and 2022. The study population was comprised of both children and adults who had sustained one or more fractures in a bicycle accident as registered in the Swedish Fracture Register. ResultsWe included 33,384 fractures (25,960 in adults and 7424 in children) in 30,815 patients, with a dominance of fractures in men. The mean age at fracture was 41.6 years (SD 23). The majority of fractures (62.7 %, n = 20,932) were sustained via a low energy mechanism. Overall, the most commonly fractured body parts were the forearm (35.2 %, n = 11,747), the hand (15.6 %, n = 5,196) and the clavicle (13.7 %, n = 4,558). In children, fractures of the forearm (56.8 %, n = 4,215) clearly dominated, followed by the hand (11.7 %, n = 868), and the humerus (11.0 %, n = 816). In adults, the top 3 fracture locations were the forearm (29.0 %, n = 7,532), the hand (16.7 %, n = 4,328), and the clavicle (15.7 %, n = 4,086). Mountain bikes and road bikes showed a fracture panorama that was very similar with a predominance of fractures to the clavicle. Fractures were more common during the warm season. ConclusionThe main finding is that bicyclists predominantly sustained fractures of the upper limb via low energy mechanisms. The fracture panorama differed by age, sex, and type of bicycle.

80 Improving policy and practice for cyclists with a disability in The Netherlands

Abstract Purpose Cycling is known to have great health benefits and to contribute to the autonomy and independence in mobility of people with a disability. However, Dutch streets and cycling lanes are not designed for adapted bicycles, and other traffic users often do not know how to react to cyclists with an adapted bicycle. Furthermore, there is a lack of cycling policy that accounts for disabled cyclists. This raises the following questions: - Why, when, and where do people with a disability cycle? - What challenges do cyclists with a disability experience when cycling? - How can these challenges be addressed, according to people with a disability themselves and professionals in the field? This study will help to gain insight into the practice of cycling among Dutch adults with a disability, in order to better understand their challenges and needs. A better understanding of these challenges and needs is necessary to make cycling more accessible. We also aim to raise awareness amongst designers and policy officials of the great diversity within cyclists’ needs and the types of bicycles used. We ultimately hope to contribute to greater cycling participation among people with a disability. Methods We conducted ten interviews with Dutch adults with different disabilities who shared their experiences of cycling in their neighborhood environment and beyond. The interview transcripts were coded and analyzed based on main themes we identified: characteristics of general cycling behavior, motivation(s) to cycle, challenges in cycling and possibilities to improve the cycling experience. We discussed these results for improvement in a workshop with professionals in spatial and traffic design. Results We will present the experiences of cyclists with a disability, the challenges they face and suggestions for improvements. Conclusions With this study, we hope to contribute to a better understanding of the needs and experiences of cyclists with a disability. Applying these insights will help policy officers and other professionals in the field in making their policies and designs more effective and improve road designs for cyclists with a disability. Funding This research project is funded by the Dutch Ministry of Health, Welfare and Sport (VWS).

Detection dataset of electric bicycles for lift control

Electric bicycle datasets for lift control have played a crucial role in the development of electric bicycle lift entry detection algorithms. However, existing datasets often encounter issues, including a small dataset size, a high false detection rate, and the absence of a publicly available benchmark dataset. This paper addresses these challenges by constructing a new electric bicycle detection dataset for lift control based on the research demands of the electric bicycle detection task for lift control. XHNet_EB, a car scene image dataset covering various types of electric bicycles, was constructed based on images taken by a camera from above. Segmented annotation was employed, framing the front and rear of the electric bicycle independently. This approach effectively addressed the problems of many irrelevant features and a high false detection rate caused by the use of whole-electric-bicycle annotations in mainstream datasets. AP_50, AP_75, the mAP, and the number of false detections in the images were used for quantitative analysis of the dataset. The experimental results indicated that the object detection accuracy of the XHNet_EB dataset was excellent. Quantitative analysis and evaluation of the number of false detections in images were conducted using four mainstream lightweight detection model algorithms. The results demonstrated that segmented annotation reduced the false detection rate more effectively than entire electric bicycle annotation. This study identified drawbacks in existing datasets. The dataset proposed in this paper overcomes the shortcomings of existing commercial data and solves problems such as the high false detection rate caused by the inclusion of many irrelevant features caused by the “whole-electric-bicycle annotation” method, which could help with the development of electric bicycle detection applications in lifts.

Speed and lateral distance behavior on highly frequented bicycle facilities in Germany

Due to increasing bicycle traffic demands in Germany, more and more bicycle facilities are designed with widths beyond the standard values given in the existing design guidelines. To date, only few findings are available regarding the traffic flow at bicycle facilities with high volumes, especially when comparing different facility types and percentages of specific bicycle types. For this, the driving behavior of cyclists at high traffic volumes was analyzed, considering different bicycle types. Traffic flow was examined on segments of bicycle facilities with different geometric characteristics, including facility type, gradient, and width. The speed and lateral distance behavior of cyclists was analyzed by using radar and video measurements. It was found that the speed and lateral distance behavior in bicycle traffic is particularly influenced by the gradient and the composition of bicycle types. Furthermore, the results show that the number of bicyclists in the cross section, the width of the facility, the type of interaction (meeting, passing or riding next to each other at the same speed) as well as the type of the constructional boundary influence the lateral distance behavior. In general, it could be observed that bicyclists make use of the available width of the bicycle facility and choose larger distances in case of passing or meeting. Furthermore, it was observed that a minimum lateral wheel distance of 0.80 m is maintained during passing both in one- and two-directional traffic. This minimum lateral distance is already included in the current German design guidelines.

Are We Back to Normal? A Bike Sharing Systems Mobility Analysis in the Post-COVID-19 Era

In recent years, numerous cities around the world have adopted bike sharing systems (BSSs). The increasing popularity of these transportation means is directly related to their eco-friendly and health advantages. Several factors affect how citizens make use of BSS, for instance, the size and configuration of a city, where docking stations are located, the associated prices, and others. Moreover, these systems have different usage patterns that vary according to the month, day, or hour but remain constant when compared yearly. However, the onset of the COVID-19 pandemic modified mobility behaviors as various governments around the world implemented mobility restrictions to avoid the spread of the virus. The objective of this investigation is to determine if the usage patterns of BSSs have changed permanently or if we have recovered pre-pandemic levels and usage patterns. Given the special characteristics of each BSS, this study focuses on Barcelona’s BSS, called Bicing. To understand the impact of other BSSs, the further analysis of each system’s unique characteristics is necessary. The study employs bike usage information from the public open data service maintained by Barcelona City Hall, namely, the Open Data BCN website, from January 2019 to December 2023, and it covers mechanical and electrical bikes with more than 4 million records per month. The results show that usage patterns were similar before and after the pandemic; the usage increased in 2021 and 2022 and stabilized in 2023, registering a rise of 17.5% in Bicing usage from 2021 to 2023. However, bike type preferences have changed for reasons unrelated to the pandemic restrictions. The main limitation of this investigation is the lack of continuity in the data due to a change in the company that provides the service in Barcelona. For future research, data from other transportation means can be used to analyze all communication behavior in this city. Additionally, if data are available, a study by gender and age can be performed and used to improve the system for certain groups.

The influence of individual physical capabilities for cycling adoption: Understanding its influence and mode-shift potentials

We show the importance of individual physical capabilities for cycling in Switzerland, as well as introducing a routing-tool that integrates these capabilities into the estimation of cycling demand potentials. A binary logit model to predict daily cycling was estimated, using data from the Swiss Health Survey. It is found that the frequency of physical exercise explains most of the variability of the choice to cycle or not. Since previous work in the literature has shown a clear link between exercise frequency and physical strength, one valid, although so far not directly observable hypothesis is that more physical power leads to faster speeds and higher competitiveness of cycling against other modes. The higher power output of E-Bikes and S-Pedelecs further increase cycling potentials in this context. We therefore use data from the Swiss Health Survey to impute cycling potentials for individuals who participated in the Swiss Mobility Microcensus and evaluate mode-shifts potentials to bikes based on travel times of public transport and car trips. Because our router makes use of an elevation-aware physical model, which takes into account bike and cyclist characteristics, such as input power and weight, we also model pedelecs and speed-pedelecs and show how such bike types increase the mode-shift potentials towards bicycles.

Mesoscopic model of cycling trip energy expenditure based on operating modes

Cyclist physical exertion is largely ignored in quantitative travel analysis, partly due to a lack of appropriate tools. Microscopic models of second-by-second energy expenditure based on equations of motion are data intensive and cannot be applied to hypothetical routes (such as needed for route choice modelling). Macroscopic models of aggregate energy expenditure based on a fixed assumed energy intensity are insensitive to traveller, trip, and contextual factors that are relevant for behavioural research and policy analysis (such as bicycle type or trip purpose). Building on concepts from motor vehicle emissions analysis, this paper proposes a mesoscopic approach to model cycling trip energy expenditure based on the distribution of travel time across discrete states of motion (“operating modes”) for different classes of traveller and trip (“model segments”). We aim to answer two key questions for model implementation: 1) which variables most effectively classify trips into model segments and 2) what operating mode definition most consistently characterizes cycling energy expenditure within model segments? We also evaluate the precision of the mesoscopic model relative to cycling energy estimates from microscopic and macroscopic models. Applied to a dataset of naturalistic cycling trips in Vancouver, Canada, the proposed mesoscopic model with six model segments based on 3 segmenting variables (rider gender, electric-assist bicycle, and high or low speed tier) explains up to 28 % of the variance in trip-level energy estimates from the microscopic model (within around 35 W of the microscopic estimates, on average). Further research to develop cycling trip energy models for general application is discussed.

Bicycling for Rehabilitation of Persons With Parkinson Disease: A Scoping Review.

Exercise is beneficial for persons with Parkinson disease (PwPD). The overarching purpose of this scoping review was to provide guidance to clinicians and scientists regarding current evidence for bicycling exercise for PwPD. A scoping review was conducted to examine the heterogeneous literature on stationary bicycling for PwPD to reduce motor symptoms and body function structure impairments, improve activities and motor performance, and reduce disease severity. The Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines were followed. PubMed, CINAHL, and PEDro were searched from inception to January 23, 2023. Articles reporting original data on relevant outcome measures were included. Search results were screened and articles were extracted. Data were analyzed quantitatively with percentages of significant and clinically meaningful findings and qualitatively to extract themes. Bicycling was categorized using bicycle types (assisted, nonassisted) and training modes (speed, aerobic, force). A high percentage of the 34 studies showed statistical significance for reducing motor symptoms (83%), body function structure impairments (78%), disease severity (82%), and improving activities (gait 72%, balance 60%). Clinically meaningful findings were achieved in 71% of the studies for reduction in disease severity and in 50% for improving gait. The literature on bicycling for PwPD has evolved from speed to aerobic studies. The terminology describing types of bicycling was simplified. Of all the outcomes reported, reduction of disease severity achieved the highest frequency of clinical meaningful improvements. Bicycling was comparable with other forms of aerobic training for walking speed and endurance. Opportunities for translation to practice and research are presented.

Review of the Impacts of Human Factors on Cycling: Perceptions, Workload, and Behavior

Cycling remains a popular mode of transportation, yet cyclists are vulnerable road users that face numerous safety challenges. Although human factors research typically focuses on motor vehicle drivers, studies addressing active transportation users, like cyclists, are scarce. The unique aspects of cycling, such as physical effort, exposure to the environment, and disconnected infrastructure, can affect cyclists’ mental perception, workload, and behavior, which are argued to influence their safety on the road. Therefore, this scoping literature review identified factors influencing cyclists’ workload and explored different measures used to quantify mental workload. The findings highlighted age, infrastructure, portable devices, and type of bike as factors that could affect workload levels. However, research on cyclists’ workload from their perspective is limited. This paper summarizes three types of workload measure: subjective, performance, and physiological. These have been used to quantify workload in relation to cyclists and in other settings. We reflect on their benefits and challenges were they to be used to quantify cyclists’ workload. Our discussion emphasizes the need for future research to take a comprehensive approach that considers multiple factors simultaneously to gain a more holistic understanding of their collective impact on cyclists’ mental workload. Moreover, we emphasize the importance of supplementing subjective workload measures with psychophysiological ones for better accuracy and reliability. The review revealed a lack of data and guidelines specific to cycling infrastructure, contributing to cyclists’ vulnerability, and underscored the need for previous findings to be translated into actionable recommendations to improve cyclist safety.

Development of Two Wheel Drive Electric Bikes for Extreme Road and A Long-Range Capabilities

This paper aims to develop the electric bicycle by using a two-wheel drive that has a long range of use. This development is motivated by many extreme roads and the absence of a charging station except in the user’s own house. A folding bicycle type bicycle for adults with 16-inch wheels was used in this study. The two-wheel drive can be adjusted using the driving motor to be more flexible and adapt to road conditions, although the motor power used is small, 350-Watt 24 Volt for one wheel. The battery capacity used is quite large for the range quite far away, which is 24 volts 80 Amps, and the charging time is about 2 hours. The placement of the battery has calculated the center of gravity and balance of the bike. Results show that this electric bicycle can be used for slippery road conditions and slopes of not more than 1A maximum speed of the bicycle can reach up to 30 km/hour, on flat road conditions. Likewise, the bicycle’s range for a full charge is around 220-260 km, with an average speed of 15-16 km/hour. Two drives can be implemented independently, adjusting the running conditions by moving the drive motor selection button. For extreme conditions, it is recommended to use two electric motors.

Spatial dimension of accidents involving pedelecs 25 and conventional bicycles

The pedelec 25 (pedal electric cycle) has established itself as a popular mode of transport, with sales rising. Unfortunately, this has also led to an increase in the number of accidents. Analyses of pedelec accidents have been carried out, but most studies are based on technical variables. Neither spatial, geographical factors, for example the terrain, nor socio-geographical aspects, such as whether an accident occurred in a tourist region, have been much addressed. However, geographical exposure can vary significantly. Therefore, we assume that spatial differences contribute to regional variations in numbers of accidents and resulting injuries associated with both bicycle types (pedelecs 25 and conventional). Thus, the aim of this paper is to determine geographical factors that influence severe accidents and to evaluate this influence. We have identified relevant geographical factors and proven their influence on two types of severity: risk of severe bicycle accidents per region (RS) and probability of severe injuries in case of accident (AS). Spatial analyses indicate that for both bicycle types, severity of accident increases in rural, mountainous or tourist regions. Regression analyses of RS provided further evidence: compactness of settlement structure (thus urbanity/rurality), share of tourists, altitude differences (only pedelecs), rate of registered motor vehicles and share of elderly population (only pedelecs) influence the risk of severe bicycle accidents per region. The influence of geographical variables tended to be greater for pedelecs. Regression analyses of AS reveal that geographical factors also have an influence on the probability of severe injuries in case of an accident.

Exploring the factors affecting bike sharing usage in developing countries: a case study on Chandigarh, India

ABSTRACT Bike-sharing is one of the world’s fastest-growing new modes of transportation, with new schemes appearing on a regular basis. This paper examines the usage trends in a bike-sharing scheme operating in Chandigarh since 2020. While many studies have been conducted on how bike-sharing schemes are changing mobility in cities worldwide, particularly in developed countries, few have examined the dynamics of these schemes in cities in developing countries like India. One of the reasons for looking at a city like Chandigarh is to see if medium and smaller cities in developing countries benefit from bikesharing schemes and if bike-sharing schemes can play a prominent role in these cities. The study conducted an exploratory analysis using app data to examine the impact of factors such as temporal, weather, travel characteristics, and bike type (conventional or E-bike) on bike share usage in the city. Some of the research findings on the impact of various factors on bicycle ride durations (short, medium, and long) can assist other cities in developing countries in planning new bike station networks. Furthermore, analysing mode selection (conventional and E-bike) in bike share provides insights into user preferences and how various influencing factors influence their mode choice behaviour in similar cities.

Research on Vibration Comfort of Non-Motorized Lane Riding Based on Three-Axis Acceleration

To enhance cycling comfort, a critical investigation of vibration effects in non-motorized bicycle riding is essential, focusing on road characteristics and traffic features. The analysis of how these elements influence cycling vibrations identified 13 key factors. This study utilized non-motorized bicycle lanes in Wuhan City for empirical research. Three-axis accelerometers were attached to riders’ torsos to measure vibration comfort levels. The observed road segments ranged from slightly to relatively uncomfortable. This study employed the random forest algorithm and logistic regression to analyze the influencing factors further. Six factors emerged as significant in affecting cycling comfort: the existence of dedicated non-motorized bicycle lanes, the lack of a physical barrier between non-motorized and motorized traffic, cycling speed, road surface irregularities, parking areas within non-motorized lanes, and bicycle type. This research offers valuable insights into non-motorized bicycle lane usage and contributes to the development of urban non-motorized bicycle infrastructure, supporting sustainable urban transportation.

Simulation Model for the Formation of Distributive Routes in a Dynamic Urban Environment

The share of small shipments in the total volume of cargo transportation has increased significantly. However, irrational routes are formed, customers’ requirements for timely delivery of goods are ignored, and vehicles of irrational carrying capacity are used on distribution routes, which significantly increases logistics costs and the cost of goods. The limitations and problems of existing solutions were analysed. Theoretic methods are not applicable to the Vehicle Routing Problem with more than 17 customers due to computational complexity. The heuristic methods that were examined focus on creating the shortest routes but do not consider customer priority, route restrictions, or potential service strategies. Therefore, a metaheuristic Genetic algorithm was chosen for route formation tasks. The research is aimed at developing a simulation model, which is based on the use of a genetic algorithm, to create optimal delivery routes for small shipments to customers within a city. The study includes modelling the route formation using a genetic algorithm for various types of cargo bicycles and trucks in a dynamic urban environment. As a result of simulation modelling, distribution routes were formed and operational parameters were optimized on cargo delivery routes in the city for various types of vehicles with different carrying capacities.

A station location design problem in a bike-sharing system with both conventional and electric shared bikes considering bike users’ roaming delay costs

Bike-sharing systems (BSSs) have emerged in many cities worldwide. One key issue regarding the strategic design of BSSs is the deployment of bike stations. Innovations in technology have enabled new types of bikes, such as shared e-bikes, to work alongside conventional shared bikes. However, existing studies on bike station location design mainly focus on single bike type, and there is a lack of a theoretical model to determine the optimal bike station locations for a BSS where both conventional shared bikes and e-bikes are considered. This study investigates the station location design problem in a BSS with conventional shared bikes and e-bikes. The design problem is formulated as a bi-level optimization problem. The upper-level problem is to determine the optimal station locations with the objective of maximizing social welfare, and the lower-level problem is a multi-period multi-modal network equilibrium problem with pick-up and drop-off constraints. The upper-level problem is solved using the Genetic Algorithm, while the rolling horizon method is used to decompose the lower-level problem into multiple period-specific subproblems. Each subproblem is solved via a block Gauss-Seidel decomposition approach coupled with the revised simplex method and column generation. Numerical examples are given to demonstrate the properties of the problem, illustrate the performance of the solution algorithm, and offer key insights into the planning of BSSs.

Investigation of the driving characteristics of electric bicycles by means of multibody simulation

Electrically assisted bicycles lead to a change in the driving characteristics compared to conventional bicycles because of the additionally attached masses of motor and battery. In order to describe the resulting interaction of the electric drive components on the driving characteristics, this paper examines simulations of the driving behavior of bicycles with different positions of battery and motor in open- and closed-loop tests. The integration of human driving behavior by control loops allows the evaluation of driving characteristic under more realistic driving conditions compared to the existing studies of the eigenbehavior. The results are analyzed using characteristic values that describe the system behavior in a suitable way. Furthermore, a design of experiments is performed to classify the influence of the presented research results in relation to other system parameters, such as different types of bicycles and different rider postures.

Development of German pedelec (and bicycle) crashes between 2013 and 2021

Introduction: The continuous growth in the use of e-bikes (in Germany mostly pedelecs that support pedaling up to 25 km/h) raises questions about the use of historic crash data for the development of road safety measures. The aim of this study was to address this issue, by conducting a longitudinal analysis of pedelec and bicycle crash data over a period of nine years to identify trends and to clarify whether such trends are specific to pedelecs. Method: We analyzed 95,338 police reported pedelec and bicycle injury crashes from 2013 through 2021. The dataset consisted of crashes from three federal states of Germany: Brandenburg, Hesse and Saxony. Data were analyzed with respect to sex and age distribution, time, location and type of accident, conflict partner, cause of crash and injury severity. Results: Many of the analyzed variables showed a considerable degree of temporal stability, with differences as well as similarities between the two bicycle types staying quite consistent over the years. One notable difference was the mean age of the involved riders, with crashed pedelec riders being significantly older than conventional cyclists. At the same time, however, the mean age of these pedelec riders has decreased by eight years over time. Single vehicle crashes were consistently more common for pedelec riders than for cyclists. Similarly, pedelec rider crashes went with a higher injury severity over all the years. Conclusions and practical applications: While, on a more detailed level, we found differences between the two bicycle types, overall crash characteristics were remarkably similar and consistent over time. Our findings provide no clear argument for road safety measures that are specifically designed to target pedelecs. Instead, the stable crash total, and the increases in ridership of both bicycles and pedelecs, highlight the demand for new, innovative solutions to improve cycling safety in general.

Transforming bicycle market: Assessing cyclists route preferences on different bike types in a choice experiment

Cycling is an environmentally friendly and healthy mode of transport that can be supported by appropriate road infrastructure. Most recently, the bike market is being differentiated and sales of innovative bike types such as cargo bikes and e-bikes are growing rapidly. Even though the importance of these particular vehicles is increasing greatly, little is known about specific route preferences applicable. Hence, we evaluate a graphically assisted online discrete choice experiment. We investigate the route preferences of users of different types of bikes. By applying mixed logit models, we estimate the differences in the valuation of infrastructure characteristics between users of regular bikes, cargo bikes and e-bikes. Results show that users of both, cargo bikes and e-bikes value a high-quality infrastructure even higher than users of regular bikes do. Higher route requirements of users of innovative bike types strengthen the importance of upgrading the infrastructure as these vehicles are becoming increasingly popular.

Rebalancing in bike sharing systems: Application to the Lisbon case study

This work presents a mathematical programming formulation for the static Bike Rebalancing Problem to meet the practical constraints faced by the operators of Bike Sharing Systems. Adaptating a Mixed Integer Linear Programming formulation, it now includes different types of vehicles and bicycles, the autonomy of each vehicle, the duration of its route and the stations that require inspection actions. An intermediate station is introduced to temporarily store bicycles, relaxing the restrictions imposed by the vehicles’ capacity. After incorporating different acceleration procedures, a Branch-and-Cut scheme is run for 30 min to find optimized routes for the reposition vehicle on five real instances of the Lisbon Bike Sharing System. The computed routes resulted in a 30% to 75% decrease in total length, when compared to the real routes. This decrease is mainly attributed to the integration of all the mentioned factors in one global model, encouraging its future implementation.