Bicycle Facilities Research Articles

Students’ perceptions on bicycle facilities in campus. A case study at Universiti Tun Hussein Onn Malaysia, Johor

Increasing dependence on the private vehicles and motorised transport in the university campus have resulted in a growing traffic congestion and more demand for parking, air pollution and thus, contribute to high energy consumption. It is very necessary to encourage the use of active transportation such as cycling in campus among university students as higher education has been seen as a role model to outside community and has its own impact to community, socially and economically. The objective of this study is to identify students’ perceived current bicycle facilities in campus areas. The questionnaire in a Google Form were distributed through a social media platform (e.g. Facebook and WhatsApp) in order to avoid social interaction during pandemic COVID-19. A total of 328 respondents among postgraduate students in Universiti Tun Hussein Onn Malaysia (UTHM) was chosen to answer the questionnaire. Furthermore, data was analysed using Descriptive Analysis and Importance-Performance Analysis (IPA). The Statistical Packages of Social Sciences (SPSS) software version 26 was used to do the statistical analysis of the sample data. Results show that students perceived some of the bicycle facilities in campus that have a high level of importance value for students, are having a low-level performance, such as improper cycling paths and poor lighting at night.

The maximal covering bicycle network design problem

Considering the lack of adequate cycling infrastructure networks in many cities, decision makers must face the challenge of designing connected bicycle facility networks to ensure safe and comfortable access to urban opportunities for cyclists and the usability of infrastructure. This paper addresses the maximal covering bicycle network design problem (MCBNDP). MCBNDP involves making investment decisions to build a cycling network that is aimed at maximizing the coverage of cyclists, while maintaining a minimum total network cost at its minimum. The derived network is subject to a budget limit and accounts for the entire connectivity and directness as fundamental bicycle network design criteria. Cyclists who are located at a given origin are considered covered by the network if a connected path of dedicated cycling infrastructure links them to their desired destination, within a maximum travel distance. We propose a mixed-integer linear programming (MILP) formulation, including a two-phase solution approach to solving the MCBNDP. In addition, using a commercial solver, our MILP formulation allows exact solutions to be obtained for large-scale instances with reasonable computing times for these types of problems. This MILP formulation is employed to solve a real instance that is applied to a wide territory of analysis in Medellin city (Colombia). The findings of this paper will contribute to existing literature and support urban policymakers to better spatially allocate the resources and, consequently, maximize the impact of their investments on connected cycling infrastructure networks. Our findings indicate that access to opportunities for cyclists can be easily favored by making small improvements to the existing infrastructure to guarantee safe, direct, and comfortable cycling infrastructure. Because we specify a maximum travel distance rather than a shortest path limitation, our problem ensures that cyclists may have several possibilities for their routes, which may go along the shortest path or any other alternative, however, without exceeding the maximum travel distance. In this direction, our findings confirm that prioritizing coverage, while accounting for full network connectivity, will benefit more cyclists because of the flexible configuration of the new network, which also may ensure its usability.

Cyclist Safety and Comfort of Bicycle Facilities in the Bintaro Jaya During Covid-19 Pandemic Using Bicycle Level of Service

Limited cycling facilities are one of the problems that often occur in urban areas in Indonesia, especially Bintaro Jaya, an area that cyclists often traverse during the COVID-19 period as it is today. The lack of service level of bicycle facilities on Jl. Boulevard Bintaro Jaya often causes bicycle users to feel less safe and comfortable during cycling. This study was conducted to know the service of bicycle facilities in Bintaro, especially on jl. Boulevard Bintaro Jaya. The most affecting factor of the service level of bicycle facilities in Bintaro is the high volume of traffic. One of the first steps to knowing the level of service of bicycle facilities is to analyze using the bicycle level of service (BLOS) method. In addition, a questionnaire will be conducted to determine the perception of bicycle facility users in Bintaro. Observations on traffic characteristics are carried out on weekdays and weekends, which are then to obtain BLOS data. Analysis was performed that BLOS values above 3.5 which mean the bike is not feasible for cyclists. The results concluded that the bicycle facilities in Bintaro Jaya are still not by the safety and comfort factors according to the BLOS method. To improve the safety and comfort of cyclists, the application of traffic calm such as speed hum is needed to reduce the impact of high traffic volume and high speed, repainting of markings and adding bicycle parking facilities.

Analysis and Design of a Route Recommendation System and Bicycle Rental Fees at Tourist Destinations with Genetic Algorithms

The tourism sector is one of the country's most significant sources of income, especially in Indonesia. This is inseparable from many visitors or foreign tourists who come to Indonesia. Bandung is a tourist destination that is famous for its natural beauty and traditional culture, one example is in Desa Alamendah which has several tourist destinations, namely agro-tourism, nature tourism, and cultural tourism. However, access that can be passed from every tourist spot in Desa Alamendah can only be given on foot or by bicycle. Responding to this matter, bicycle facilities as a means of rotation are needed to access tourist attractions in Desa Alamendah. Based on these problems, this study aims to create a recommendation system for tourist attractions and bicycle rentals using an application in Desa Alamendah, Bandung. Using the Genetic Algorithm, an algorithm that can solve multi-objective problems can be applied to a tourist spot recommendation system in Desa Alamendah. In this system, the Genetic Algorithm is also used to determine fares based on the total distance traveled, so that bicycle rentals are more efficient. The study combines Google Maps as an appropriate route selection based on the recommendation of tourist destination points that tourists can visit using Genetic Algorithms, so that bicycle rentals are more efficient. This is study combines Google Maps as an appropriate route selection based on the recommendation of tourist destination points that tourists can visit using Genetic Algorithms. So that bicycle rentals are more efficient. The study combines Google Maps as an appropriate route selection based on the recommendation of tourist destination points that tourists can visit using Genetic Algorithms. Based on the results of tests that have been carried out in the process of forming tourist attractions recommendations with a Genetic Algorithm that using mutation probability 1.0 and Crossover Probability 0.6, can produce a Mobile Application with a Genetic Algorithm as a tourist spot recommendation system in Desa Alamendah. In addition, it also can provide recommendations, namely displaying tourist points, route using Google Maps. The rental fee is based on the total distance traveled.

Impact of road features on shared e-scooter trip volume: A study based on multiple membership multilevel model

E-scooter sharing systems have been widely adopted by cities around the world. Previous studies analyzed community-level factors influencing e-scooter usage. Few studies examined the effect of road features on e-scooter trip volume (ETV) of the road segment, which can reveal the road features that riders prefer. This study explores this topic by analyzing the ETV of 29,544 road segments in Calgary, Canada, while controlling for community-level factors. Because some segments are the boundaries of multiple communities, the multiple membership multilevel model is adopted to tackle this boundary problem. The results show that segments with sidewalks, dedicated bicycle facilities, lower speed limit, more street lights and trees have higher ETV. ETV is also higher in communities with high income, high percentage of commercial and residential area. Quantifying the effect of road features on ETV could help government agencies determine where e-scooters should be ridden and design road facility improvement plans for e-scooter users.

How does hourly variation in exposure to cyclists and motorised vehicles affect cyclist safety? A case study from a Dutch cycling capital

Cycling is promoted as a sustainable and healthy mode of transport, which results in an increase in bicycle use in urban areas. Increasing bicycle use comes with growing concerns about cyclist safety. This study examines how the temporal variation in the network-wide exposure to cyclists and motorised vehicles affects bicycle crash frequency. Network-wide hourly volumes of cyclists and motorised vehicles were estimated and regression models were used to identify the effect of the exposure to traffic on bicycle crashes in the city of Utrecht, a Dutch cycling capital. The results show that increasing exposure to motorised vehicles, and to a lesser extent, exposure to cyclists, increases the number of bicycle crashes on 50 km/h roads. For 30 km/h roads, no statistically significant relationship between the exposure to cyclists and bicycle crashes was found. Moreover, it was shown that cyclist crash numbers on 30 km/h roads are less sensitive to an increase in the exposure to motorised vehicles compared to cyclist crash numbers on 50 km/h roads. Furthermore, the exposure to motorised vehicles is a stronger factor affecting the increase in bicycle crashes on roads with bicycle lanes or mixed traffic conditions than on roads with separated bicycle facilities. To conclude, this study shows that road safety for cyclists needs further improvements, as cycling in cities keeps increasing.

Using Global Positioning System Big Data to Define a Bikeshare User Typology and Model On-/Off-Road Bicycle Facility Preferences

Bikeshare programs have grown exponentially over the last decade and have been found to be influential in increasing the nonmotorized mode share. With shared microbility programs proving to be a key component of modern urban environments and in first- and last-mile connections to transit, there is a need to better understand users and their facility preferences. This study utilizes 3 years’ worth of data from a campus bikeshare program in Auburn, AL, that includes over 100,000 trips and almost 9,000 users to develop a bikeshare user typology. Whereas past research developing cyclist groupings has been based on self-reported cyclist comfort and confidence levels, this study utilized actual ridership data from the bikeshare program to create new typologies specific to bikeshare. Using a K-means cluster analysis, this study proposes four bikeshare user types: unsupported users, aspirational users, flexible users, and purposeful users. These users have varying travel motivations, needs, and patterns. Their choice between an on-road and off-road facility option was analyzed at nine specific locations displaying different roadway and physical conditions. A binary logistic regression analysis was performed to determine which variables are influential in a bikeshare user’s choice between riding on an on-road or off-road facility. The modeling results found two typology memberships were a significant predictor of bicycle facility preference, keeping all other factors constant. Specifically, flexible and purposeful users had stronger preferences for off-road bicycle facilities. Additionally, the physical conditions were found to be significant with users choosing off-road options away from motor vehicle traffic as the roadway environment becomes more intimidating.

Exploring Unobserved Heterogeneity in Cyclists’ Occupying Motorized Vehicle Lane Behaviors at Different Bike Facility Configurations

Cyclists occupying motorized vehicle lanes disrupt road traffic order and increase collisions. Exploring the contributing factors could help develop countermeasures to regulate such behaviors. The purpose of this study is to explore the intrinsic features influencing the behavior of cyclists in occupying motorized vehicle lanes at different bicycle facilities. We investigated a total of 34,631 cycling behavior samples in the urban area of Pingdingshan, China. A Bayesian random parameter logit model was used to account for the unobserved heterogeneous effects. The experimental results of all bike facilities demonstrate that the bike type, dividing strip type, bike lane width, temporary on-street parking, and whether it is a working day significantly affect cyclists’ occupying motorized vehicle lane behaviors. Factors associated with unobserved heterogeneity are age, barriers dividing strip, vehicle lane numbers, bike volume, vehicle volume, and daily recording time intervals. Comparing the estimated model of five type bike lane facilities across different dividing strips, we find that cyclists have a significantly different occupying probability and the heterogeneity factors of the various bike facilities also have their focus. When the non-motorized road conditions become more open, the cyclist behavior becomes more random and the heterogeneity factors become broader.

The speed and configuration of cyclist social groups: A field study

Group behaviour is common among bicycle users and can have an impact on traffic dynamics in natural or emergency situations. As our observation shows, 35% of cyclists in traffic ride in pairs or groups. This paper aims to explore how cyclist group members interact and organize in bicycle flow. A field study was conducted, 166 groups of cyclists were selected as the observation objects, and their tracks were obtained through the multi-object tracking algorithm (MOT). The average speed, spatial arrangement and similarity between group members were calculated and analysed. The results show that group size has a significant negative effect on average group speed as cyclist members of the same group tend to maintain similar speeds as they ride forward. The 2-person and 3-person riding groups have relatively “time stable” geometrical structures (4 patterns for pairs and 5 patterns for triads). They are generated not only from traffic rules but also from the local interaction between group members. The dissimilarity value of movement among them tends to increase with increasing group size due to weaker coordination in larger groups. These findings have implications for bicycle traffic modelling and safe bicycle facility design.

Preferences for roundabout attributes among US bicyclists: A discrete choice experiment

As roundabouts become increasingly common, there is very limited research about bicycle safety at roundabouts and, specifically, a lack of information about preferences for roundabouts among people bicycling. To address this gap, we conducted a discrete choice experiment involving an online survey of 613 US adult bicyclists to understand stated preferences for roundabouts with different design and operational characteristics: central island size, number of circulating lanes, bicycle facility type, motor vehicle volumes, and approach speed limit. For each respondent, the experiment included six (from among 18) choices between two roundabouts with different attributes, represented using text and simulated images. We analyzed these data using panel mixed multinomial logit models with random and systematic preference heterogeneity due to respondent characteristics. Overall, US bicyclists seem to prefer roundabouts with: smaller central islands, fewer travel lanes, lower traffic volumes, lower speed limits, and separated bicycle lanes; although, shared lane bicycle markings and signs were also preferred over bicycle ramps to the sidewalk or no bicycle facilities. Additionally, there were significant variations in preferences for bicycle facilities at roundabouts. Women, infrequent cyclists, and “interested but concerned” cyclists had stronger preferences for separated bicycle lanes, but “strong and fearless” and/or “enthused and confident” cyclists had significantly weaker preferences for these more protected facilities. This research offers insights into bicycling preferences that may help to create roundabouts that are safer and more attractive for people bicycling of all ages and abilities.

What makes bicyclists comfortable? Insights from a visual preference survey of casual and prospective bicyclists

• Comfort in different bicycling environments measured using a visual preference survey. • Bike infrastructure and low traffic speeds generate higher comfort ratings. • People without a predisposition to bicycle are unlikely to feel comfortable with even the best-designed on-road facilities. • Planning for a “design person” and setting a minimum infrastructure standard could increase comfort for all. Understanding what environments are comfortable (and perceived as safe) for bicyclists is essential for increasing bicycling, particularly for non-experienced riders. Surveys probing people’s qualitative perceptions about bicycling environments can inform bicycle planning in important ways. In this study we use survey data from an on-line video experiment to analyze bicycling comfort and its relationship with person-level and road-level variables. We use an existing survey of students, faculty, and staff at UC Davis (n = 3089) who rated video clips of bicycling facilities in different environments based on their perceived comfort as a part of the annual UC Davis Campus Travel Survey (CTS). The video clips come from a variety of urban and semi-rural roads around the San Francisco Bay Area where bicycling rates vary. Our results indicate considerable effects of socio-demographics and attitudes on absolute video ratings, but we find relative agreement about which videos are most comfortable and uncomfortable across our sample population segments. Presence of bike infrastructure and low speed roads are especially important in generating higher comfort ratings. However, our results suggest that even the best designed on-road bike facilities (according to attributes in our data) are unlikely to provide a comfortable bicycling environment for those without a predisposition to bicycle. Nonetheless, our results provide guidance for improving roads with on-street bike facilities where protected or separated facilities may not be suitable. We discuss these results in the context of design standards for bicycling and methods for prioritizing bike infrastructure investments.

Taking another look at cycling demand modeling: A comparison between two cities in Canada and New Zealand

Cities around the world are investing in their cycle network as a way to reduce traffic congestions and improve population health. For effective infrastructure investment decision-making, it is critical to understand the factors affecting cycling demand. This study investigates the combined effects of spatial and temporal factors on the demand of cycling in Auckland, New Zealand and Kelowna, Canada. A latent segmentation-based negative binomial (LSNB) model is developed utilizing daily cycling counts over a year from Auckland and Kelowna. The LSNB model captures unobserved heterogeneity based on the temporal attributes, and land use and neighborhood characteristics of the cycling facilities. The models confirm the influence of weather, bicycle facility type, built environment, traffic, land use, and accessibility attributes. The model results suggest that higher temperature, lower rainfall, increased length of shared paths, lower AADT, and closer distance to bus stop are likely to increase cycling demand in Auckland. The model also confirms heterogeneity. For example, road-connectivity index and bike index vary across the urban and suburban areas of Auckland. For Kelowna, higher temperature, lower rainfall, lower snowfall, and closer distance to water bodies are likely to increase cycling demand. In the case of heterogeneity, the effects of road-connectivity index, bike index, and AADT varies over the urban and suburban areas of Kelowna. Analysis suggests that increasing bike index is one of the critical factors to increase cycling demand in the suburban areas of Auckland and Kelowna.

Analyzing bicycle level of service using virtual reality and deep learning technologies

Bicycle Level of Service (BLOS) provides an essential tool for evaluating the operations of low-carbon bicycle facilities and prioritizing investment in new bicycle facilities under various constraints. This study aimed at developing a LOS method for assessing bicycle facilities in the metropolitan areas of China. Using this method, we addressed major challenges in obtaining user ratings of bicycle facilities and captured senses of satisfaction of bike users riding on bicycle facilities. Virtual Reality (VR) technique was introduced to obtain data by creating 120 immersive settings or scenarios for participants. A hundred of bicyclists or participants with a wide range of characters were recruited. These participants were asked to express their senses of satisfaction under predefined physical conditions of bike facilities and traffic conditions. Their Satisfaction Rating Scores (SRS) were documented. The statistical relationships between rider’s feelings and bike facilities/traffic conditions were modeled and verified through a symbolic regression (or an effective deep learning) approach. The model is demonstrated to be reliable in predicting SRS of bicyclists with a high correlation coefficient. This study also developed a set of LOS criteria based on the cumulative distribution of satisfaction scores. These LOS criteria are simple to use and effective in assessing operational performance of existing bicycle facilities and providing decision makers with insightful guidance for planning, designing, and operating new active transportation facilities.

School Safe Route in Sumbersari District, Jember Regency

The number of underage accidents in Jember Regency in 2011-2012 increased from 37 to 190 cases. Therefore, bicycle and pedestrian paths were planned through the School Safe Route program that could encourage students to choose to ride a bicycle or walking. The method of this study was the Level of Service analysis (LOS), student and travel characteristics, cross tabs, bicycle lanes, pedestrians, and road equipment facilities. The results showed that the level of road service on each road section varied, including LOS A, B, D and E. The characteristic and common cross tabs analysis results showed that most transportations used by students were motorcycles. Still, there was a relatively large proportion of students’ willingness to change their transportation mode in operational conditions if bicycle and pedestrian path facilities were provided. Cycle path analysis showed that the types of bicycle lanes were planned, specifically type A and C, with a bicycle lane width was 1.44 m for each lane. From the calculation of the minimum effective width of the sidewalk obtained 1.01 m with a crossing facility in the form of a pelican crossing with waiting stalls. Several road equipment facilities were planned, such as traffic signs, road markings and Traffic Signaling Equipment (TSE). Bicycle and pedestrian routes were planned at Tawang Mangu Street, Danau Toba Street, Mastrip Barat Street, Kalimantan Street, Jawa Street, Karimata Street, M.T. Haryono Street, Letjen S. Parman Street, Letjen Panjaitan Street and Letjen Suprapto Street.

Biking where Black: Connecting transportation planning and infrastructure to disproportionate policing

This study asks whether deficiencies in transportation are associated with disproportionate policing in Chicago using the case of cycling. I examine how the number of bicycle citations issued per street segment are influenced by the availability of bicycle facilities and street characteristics, controlling for crash incidence, police presence, and neighborhood characteristics. Tickets were issued 8 times more often per capita in majority Black tracts and 3 times more often in majority Latino tracts compared to majority white tracts. More tickets were issued on major streets, but up to 85% fewer were issued when those streets had bike facilities, which were less prevalent in Black and Latino neighborhoods. Tickets were not associated with bicycle injury-crashes and inversely associated with vehicle injury-crashes. Infrastructure inequities compound the effects of racially-biased policing in the context of transportation safety strategies. Remedies include the removal of traffic enforcement from safe systems strategies and equitable investment in cycling.

Analysis of Bicycle-Motor Vehicle Crashes in San Antonio, Texas.

Bicycling is inexpensive, environmentally friendly, and healthful; however, bicyclist safety is a rising concern. This study investigates bicycle crash-related key variables that might substantially differ in terms of the party at fault and bicycle facility presence. Employing 5 year (2014–2018) data from the Texas Crash Record and Information System database, the effect of these variables on bicyclist injury severity was assessed for San Antonio, Texas, using bivariate analysis and binary logistic regression. Severe injury risk based on the party at fault and bicycle facility presence varied significantly for different crash-related variables. The strongest predictors of severe bicycle injury include bicyclist age and ethnicity, lighting condition, road class, time of occurrence, and period of week. Driver inattention and disregard of stop sign/light were the primary contributing factors to bicycle-vehicle crashes. Crash density heatmap and hotspot analyses were used to identify high-risk locations. The downtown area experienced the highest crash density, while severity hotspots were located at intersections outside of the downtown area. This study recommends the introduction of more dedicated/protected bicycle lanes, separation of bicycle lanes from the roadway, mandatory helmet use ordinance, reduction in speed limit, prioritization of resources at high-risk locations, and implementation of bike-activated signal detection at signalized intersections.

Analysing the influence of attitude and habit on bicycle commuting

New transport trends have emerged in developing countries to promote bicycling due to its individual and societal benefits. Although bicycle infrastructure provision has been one of the most utilised strategies to encourage bicycling, it has had a limited immediate impact on the bicycling modal share. Published research indicates the need to incorporate the psychosocial dimension to understand commuters' transport behaviour and explain why bicycling infrastructure usage is lower than expected. This study highlights the processes behind bicycle mode choice decisions, explicitly incorporating pro-bicycle attitudes and habits, while also considering the influence of socioeconomic, bicycle facilities and bicycling experience variables on shaping that attitude. For this purpose, an online survey was designed and sent to students, faculty members and staff of two Chilean universities to collect ad-hoc data. The modelling used an approach based on an integrated choice and latent variable model. The main findings are: attitude in itself is a relevant construct to explain behaviour; bicycling infrastructure contribute to explain bicycle choice but only indirectly through attitude; socioeconomic characteristics, bicycling familiarity and practical issues have both a direct effect on bicycle choice decision and an indirect one by fostering pro-bicycling attitudes. Additionally, results show that the explicit inclusion of habit reduces the contribution of pro-bicycle attitude in explaining bicycle choice. This might be due to interaction and reinforcement between habit and attitude.

Factors Influencing Bicycle Use in International Islamic University Malaysia (IIUM) Gombak Campus

The use of bicycles on-campus at higher learning institutions including International Islamic University Malaysia (IIUM) is at a very low level. It is imperative to understand what influences bicycle use on-campus. This paper identifies factors that influence bicycle use in IIUM from the opinion of bicyclists. The main data used in this paper were from literature reviews, observational surveys, and field survey questionnaires. Univariate and bivariate analysis techniques were applied to the data to achieve the objectives of this study. The major findings show that good conditions and adequate bicycle facilities are some of the main factors, among others, that encourage students to cycle on-campus. At the end of this paper, few recommendations are suggested to increase bicycle use among the IIUM community on-campus.

Research on Scheduling Based on Spatial and Temporal Distribution Characteristics of Piled Shared Bicycle

With the development of bicycles, the problem of having no piles to park and no cars to use also appears. Because the driving mechanism of bicycle travel is not understood, the operation personnel in charge of redistribution have no way to start. In this paper, from the perspective of subway station and city bus transfer system, starting from the characteristics of road network, combining with the nature of land use, the spatial-temporal characteristics of quantitative analysis is carried out to study the spatial-temporal distribution law of travel behavior. Based on the above factors and the supporting conditions of the bicycle facilities, the common least square model was established. It was found that the number of stations in the traffic district was the most important variable, indicating that the basic supporting facilities had a great impact on the number of bicycle trips. Then, the number of bicycles and piles was deeply studied. Firstly, the stations are classified according to K-means, and defined as low-frequency high flow, high-frequency low flow, low-frequency low flow, and medium-frequency low flow according to the average of clustering results. Then, the redistribution suggestions are put forward respectively for these categories. For outflow clustering with large values of O and D, R can be predicted by BP neural network to provide reference for redistribution and distribution.

Safety-critical events in bicycle lanes in Jongno, Seoul

ABSTRACT Increasing use of cycling is closely associated with bicycle safety on the street. This study investigates safety-critical events (SCEs) on the newly built bicycle lane in a highly populated area. To encourage the low level of bicycle use, Seoul municipal government started its first plan make rooms for a new bike lane on the existing Jongno street, a symbolic boulevard in the metropolitan city center, in 2018. The goal of the study is to evaluate bicycle safety after the installation of that bike lane on Jongno street for road safety. Based on the record data from the city’s traffic camera video, which are open to the public, 141 SCEs are found for 7 days. We could find SCE characteristics and most frequent SCEs in Jongno using descriptive analysis and hierarchical clustering analysis. As a result, six types of SCE clusters were extracted, and each has specific situations and meaningful implications. These findings help understand less-known traffic conflicts in the new practice of bicycle facilities in a car-oriented CBD street that are not yet familiar with bicycle culture.