Cycling Routes Research Articles

Assessing the COVID-19 outbreak effects on active mobility of men in comparison with women

ABSTRACT This study aims to evaluate the effects of the COVID-19 pandemic on active mobility of men and women of Shiraz, Iran, and examine the relationship between perceived built environment factors and men’s and women’s active travel before and during the outbreak. The data were obtained during the pandemic from 747 men and 518 women living in Shiraz. Data collection was conducted using a questionnaire-based survey. The multivariate regression was utilized for determining the effective factors on active travel. The results indicate that the amount of time men spend walking and cycling before and during the outbreak is more than that of women. Meanwhile, the amount of time men and women spend cycling has increased during the pandemic, which can indicate the resiliency of bikes in the crisis. A built environment with mixed, diverse, dense and accessible land uses, as well as safe and secure cycling and walking routes have major effects on citizens’ active mobility in this crisis. Also, for women who have a low rate of bicycle ownership, improving bike-sharing infrastructure is essential. Therefore, it is suggested that urban planners and policymakers take action to make the environment more people-friendly to maintain citizens’ mobility, especially women, during the pandemic.

What aspects of traffic intensity most influence cycling mode choice? A study of commuting in Surrey, UK

Motorized traffic discourages cycling, but the relative influence of different aspects of traffic intensity on commuter cycling rates is under examined. This paper investigates these influences. It employs census data that describes the origins, destinations and mode choices of commuters traveling 2–5 km in Surrey, UK (n = 172,665) and derives the shortest cycling route available for each commuter. Observed and modeled transport data are used to characterize traffic on these routes. The relationship between route-level traffic characteristics and the probability a commuter chooses to cycle is then examined using logit models for all commuters, males (42%) and females (58%). Two models consider the following aspects of traffic intensity both along the cycling route and crossing (intersecting) the route at junctions: speed, volume and the proportion of heavy goods vehicles. The models also consider the influence of separated cycle paths, hilliness and distance. Above-median traffic speeds (>29 km/h) along a commuting route is shown to have the greatest negative influence on cycling propensity, followed by above-median traffic volumes (>273 veh/h) and above-median speeds (in combination) crossing the commuting route. Cycle paths have a positive influence on cycling propensity, whereas the proportion of heavy goods vehicles does not show a significant relationship. The results imply that careful management of traffic at the route scale or the provision of separated cycle paths could encourage cycling on key commuting corridors. The relative influence of different characteristics could also identify the optimal locations for intervention. Findings support 30 km/h (20 mph) speed limits as a mechanism for encouraging cycling.

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.

Using Neural Networks for Bicycle Route Planning

This paper presents the usage of artificial neural networks (NNs) in bicycle route planning. This research aimed to check the possibility of NNs to transfer human expertise in bicycle route design by training the NN on an already established set of bicycle routes and then using the trained NN to design the routes on the novel area. We created two NNs capable of choosing the best route among the given road network by training them on two different areas. The bicycle routes produced by NNs were the same at best and had 75% overlap at the worst compared to those produced by human experts. Furthermore, the mean square error for all of our NN models varied from 0.015 and 0.081. We compared this new approach to the traditional multicriteria GIS (geographic information system) analysis (MA) that requires the human expert to define the bicycle route selection criteria. The benefit of using NN over the MA was that the NN directly transfers the human expertise to a model. In contrast, the MA needs the expert to select multiple criteria and adjust their weights carefully.

Difference in User Satisfaction Factor and Construction of Satisfaction Model of Driving Environment for Cycling Route

Difference in User Satisfaction Factor and Construction of Satisfaction Model of Driving Environment for Cycling Route

A route analysis of metro-bikeshare users using smart card data

Few studies have analyzed individuals’ travel route characteristics in the integrated metro and bikeshare network. Taking Nanjing, China, as a case study, this paper analyzes the combined travel route of metro-bikeshare users based on three-week metro- and shared bike smart card data. The smart card data provides both boarding/borrowing and alighting/returning location and time, which makes it possible to trace each combined mode user’s actual metro routes. By assuming that the bike routes are the shortest paths between a specific OD pair from smart card records, we extract the combined metro-bikeshare travel routes of each user by using a metro route reconstruction method. The results show that over 60% of the metro-bikeshare users, most of whom are youth adults (18–35 years old), only occasionally use this mode. Further, the spatial and temporal characteristics of the combined metro-bikeshare travel routes are analyzed visually across different age groups. We find that most of the combined metro-bikeshare routes concentrated on Metro Line 2 with different cycling access/egress routes; however, the routes mostly travelled by different age groups are significantly different. Young adults are mainly distributed in suburban and exurban areas. Adults are more likely to be metro-bikeshare commuters, with travel routes usually passing through the central area of the city. Besides, the routes mostly travelled by the elderly are longer than those by other groups, and highly coincide with the routes mostly travelled by adults during the rush hours. Finally, relevant policy implementations are proposed in conjunction with metro-bikeshare users’ travel route characteristics.

Considering Space Syntax in Bicycle Traffic Assignment with One or More User Classes

Modeling bicycle traffic assignment requires consideration of the various factors and criteria that could play a role in a cyclist’s route decision-making process. However, existing studies on bicycle route choice analysis tend to overlook the less tangible or measurable aspects of cyclist route decision-making, such as a cyclist’s cognitive understanding of the network and a cyclist’s biking experience. This study explores the applicability of space syntax as a route cognitive attribute in a bicycle traffic assignment model. Since space syntax is a tool that links urban spatial layout to human movement, the results of a space syntax model can be used as a cognitive attribute for modeling bicycle movements with explicit consideration of the cognitive complexities of navigating through the environment. In developing a bicycle traffic assignment model, we considered relevant attributes such as route cognition, distance, and safety and integrated multiple user class analysis to reflect different biking experience levels. Numerical experiments using the Winnipeg network are conducted to demonstrate the applicability of the proposed bicycle traffic assignment model with one or more user classes.

Bicycle Traffic Model for Sustainable Urban Mobility Planning

Modelling tools and transport models are required to assess the impact of measures for the effective planning of cycling routes in cities. This paper presents the methodology for developing a four-stage macroscopic model of bicycle traffic for the city of Gdynia, and its use in planning new bicycle routes, considering a modal shift. The model presented in this paper allows for the evaluation of the influence of the characteristics of the cycling infrastructure, along with the development of the cycling network based on the choice of cycling as an alternative to other modes of transport, by taking into account the modal shift. The model takes into account the influence of the longitudinal gradient, link, and surface type of cycling routes on the distribution and demand for bicycle traffic. The results of our research allow us to assess the impact of planned cycling routes on the reduction in the volume of car traffic, which is crucial for reducing energy consumption and negative environmental impacts. Experiences from the application of the model in Gdynia suggest that the model provides a strong basis to support mobility planning and monitoring processes in cities worldwide. Cities should take into account the methods proposed in this paper when planning the development of their transport systems.

The impacts of COVID-19 on older adults’ active transportation mode usage in Isfahan, Iran

AimsSince active mobility is essential for older adults’ health and well-being, especially in crises, this study aims to investigate and compare factors affecting active mode choice of older adults (AMCOA) in the pre- and post-COVID-19 outbreak and evaluate changes in their active mobility behavior and no research has been conducted this subject. MethodologyThe sample study of this cross-sectional study includes individuals over 60 years old residing in Isfahan, Iran. For interviews based on a structured questionnaire, which was drafted based on reviewing the literature, 453 participants were randomly selected in 15 municipality districts of Isfahan. A binary logistic regression model was used to analyze the data. Result and DiscussionThe results indicate that in the post-outbreak the average walking duration per week decreased from 59 to 29 min; while, the share of this mode has increased from 40% to 65%. Also, the share of bicycles and the average cycling duration per week increased from 9% to 18% and from 9 to 15 min, respectively. Moreover, trip frequency, bicycle ownership, quality of walking and cycling routes, intersections safety, neighborhood security and greenery, traffic calming, CBD accommodation, and public transportation accessibility have positive effects on AMCOA; while, trip distance and vehicle ownership affect negatively. The results reveal that older adults have turned to the bicycle for most of their long trips during the pandemic because it is not subjected to traffic restrictions. Besides, the findings show that increasing bicycle ownership and improving bike-sharing infrastructure make the bicycle a resilient alternative when public transportation and private vehicles are not efficient. ConclusionPolicymakers and urban planners should consider that an elderly-friendly neighborhood with mixed, dense, and accessible land uses and services, as well as safe and secure routes can increase older adults’ active mobility in the crises. AimsSince active mobility is essential for older adults’ health and well-being, especially in crises, this study aims to investigate and compare factors affecting active mode choice of older adults (AMCOA) before and during the first wave of COVID-19 outbreak and evaluate changes in their active mobility behavior and no research has been conducted this subject.

Estimating Bicycle Demand in the Austin, Texas Area: Role of a Bikeability Index

This study contributes to research and practice by demonstrating the use of a composite measure, a bikeability index, to facilitate the use of and improve the performance of direct demand models for bicycle traffic, especially when only limited observation is available. The city of Austin was selected as a case study to develop the model using bicycle volume from 44 intersections. Existing knowledge and data were leveraged to develop the bikeability index that encompasses multiple built environment features (bicycle route length, comfort, connectivity, destination density, and transit coverage) to quantify the bike-friendliness of the network. In addition to the index, the demand model contained five demographic and land use variables. Some of the variables provided unique insights into bike travel behavior within the city, such as the significant and positive influence of the presence of bike signals and bike-accessible bridges. Along with the improved scalability and transferability of the modeling approach, the results and discussion are expected to facilitate and/or guide informed strategies and educational programs to increase nonmotorized activity in Austin as well as other regions.

Catalytic depolymerization of Kraft lignin towards liquid fuels over bifunctional molybdenum oxide based supported catalyst

Catalytic depolymerization of Kraft lignin towards valuable liquid fuels and monomeric phenols has been a significant and extremely attractive target, but it remains a great challenge. Herein, we report a catalytic system consisted of bifunctional molybdenum oxide based supported catalyst for catalytic lignin hydroconversion into alkylated benzenes and phenols. In the meantime, the achieved yield of liquid product was 95% and petroleum ether extracted product was 65% at 300℃ for 12 h over 20%MoOx/ZIF-8@ZIF-67 catalyst. The calorific value was increased from 25.66 MJ/ Kg to 34.31 MJ/Kg. The characterization studies show the incorporation of MoOx species leads to the synergy between redox sites and acid sites. The product analysis and catalytic studies demonstrate its synergism to promote catalytic cleavage of C-O linkages via the coupled hydrodeoxygenation and alkylation reaction. The reasonable catalytic mechanism and redox cycle route of catalyst indicate that the cooperative catalytic system paves the way for high-efficiency waste lignin utilization.

Promoting Bicycling in Car-Oriented Cities: Lessons from Washington, DC and Frankfurt Am Main, Germany

This paper compares bicycling in Washington, DC and Frankfurt am Main, Germany, two car-oriented cities that had adapted their urban transport system to car travel during the 20th century. Our comparative case study shows that both cities have been successful in increasing the percentage of trips made by bicycle between the late 1990s and 2018: Washington, DC from 1% to 5% and Frankfurt from 6% to 20% of trips. Both cities had detailed bike plans and specific mode share goals for bicycling. However, those plans were only used as guideposts for a step-by-step approach to bicycle promotion that focused on integrating bicycling into everyday decision making in transport, traffic engineering, and urban development. This step-by-step approach successfully garnered political, public, and administrative support over time. The downside of this incrementalist approach is that bike route networks in both cities still have many gaps because bikeway infrastructure was built when individual opportunities arose and not as part of an integrated network. Bicycle promotion in both cities used a combination of bikeway infrastructure and soft policy, including marketing measures. In both cities, the quality of newly installed bikeway infrastructure increased over time from simple bike lanes to protected bike lanes separating cyclists from traffic. In contrast to Washington, DC, Frankfurt has a longer history of car-restrictive policies and overall has been more strict in limiting car use.

Individual-level interventions to reduce personal exposure to outdoor air pollution and their effects on people with long-term respiratory conditions.

Individual-level interventions to reduce personal exposure to outdoor air pollution and their effects on people with long-term respiratory conditions.

A Spatiotemporal Prediction Model for Regional Scheduling of Shared Bicycles Based on the INLA Method

Dock-less bicycle-sharing programs have been widely accepted as an efficient mode to benefit health and reduce congestions. And modeling and prediction has always been a core proposition in the field of transportation. Most of the existing demand prediction models for shared bikes take regions as research objects; therefore, a POI-based method can be a beneficial complement to existing research, including zone-level, OD-level, and station-level techniques. Point of interest (POI) is the location description of spatial entities, which can reflect the cycling route characteristics for both commuting and noncommuting trips to a certain extent, and is also the main generating point and attraction point of shared-bike travel flow. In this study, we make an effort to model a POI-level cycling demand with a Bayesian hierarchical method. The proposed model combines the integrated nested Laplace approximation (INLA) and random partial differential equation (SPDE) to cope with the huge computation in the modeling process. In particular, we have adopted the dock-less bicycle-sharing rental records of Mobike as a case study to validate our method; the study area was one of the fastest growing urban districts in Shanghai in August 2016. The operation results show that the method can help better understand, measure, and characterize spatiotemporal patterns of bike-share ridership at the POI level and quantify the impact of the spatiotemporal effect on bicycle-sharing use.

Assessing cyclists\u2019 routing preferences by analyzing extensive user setting data from a bike-routing engine

IntroductionMany municipalities aim to support the uptake of cycling as an environmentally friendly and healthy mode of transport. It is therefore crucial to meet the demand of cyclists when adapting road infrastructure. Previous studies researching cyclists’ route choice behavior deliver valuable insights but are constrained by laboratory conditions, limitations in the number of observations, or the observation period or relay on specific use cases.MethodsThe present study analyzes a dataset of over 450,000 observations of cyclists’ routing settings for the navigation of individual trips in Berlin, Germany. It therefore analyzes query data recorded in the bike-routing engine BBBike and clusters the many different user settings with regard to preferred route characteristics.Results and ConclusionResults condense the large number of routing settings into characteristic preference clusters. Compared with earlier findings, the big data approach highlights the significance of short routes, side streets and the importance of high-quality surfaces for routing choices, while cycling on dedicated facilities seems a little less important.Consequentially, providing separated cycle facilities along main roads – often the main focal point of cycle plans – should be put into the context of an integrated strategy which fulfills distinct preferences to achieve greater success. It is therefore particularly important to provide a cycle network in calm residential streets as well as catering for short, direct cycle routes.

Using environmental audits and photo-journeys to compare objective attributes and bicyclists’ perceptions of bicycle routes

BackgroundBicycling is known to have many health benefits. For this reason, transport planners and public health officials in Canada increasingly aim to encourage bicycling for transport. On- and off-street infrastructure is often implemented to facilitate bicycling and planners rely on a range of tools for informing the design of the network of facilities. This mixed methods study compares objectively measured attributes and bicyclists’ perceptions of the built environment along inferred bicycle routes in Hamilton, Ontario. MethodsEnvironmental audits were conducted along six bicycle routes in Hamilton to document the attributes that might support or hinder bicycling. The routes were inferred based on the output of a model of bicycling flows. Bicyclists, 9 male and 5 female, then participated in semi-structured interviews where a form of photo elicitation, which we call photo-journeys, was used to explore their perceptions and preferences of the routes. Interview data were analyzed using both inductive and deductive thematic analysis based on the categories of the audit instrument. ResultsBicyclists prefer routes that have dedicated bicycle infrastructure, or residential streets with low volumes of traffic even if they lack infrastructure. They dislike routes with busy arterial roads or that lack bicycle infrastructure. Their experiences and knowledge of bicycling in a city transitioning to be more bicycle-friendly revealed preferences that can help to improve existing infrastructure and bicycle routes, which may also help to reduce barriers for non-bicyclists. ConclusionsPhoto-journeys are an innovative and practical approach to explore perceptions of regular bicyclists, which can be leveraged to inform policies and interventions to make bicycling routes and infrastructure safer and more attractive. Transport planners in developing cycling cities should pay attention to both the objective attributes of the built environment and how they are perceived by the public.

‘Real-world’ bicycle commuting: Characterizing the intensity and cycling routes of adults in the city of Natal, Brazil

IntroductionBicycle commuting has economic, environmental, and health benefits. However, it is not clear whether adults meet the physical activity guidelines when performing bicycle commuting in ‘real-world’ scenarios. This study aimed: (1) to verify whether adults reach the maximum heart rate percentage (%HRmax) recommended by the physical activity guidelines when doing bicycle commuting; (2) to compare the cardiorespiratory fitness of adults who meet and do not the physical activity guidelines and how they bicycle commute. MethodsIn experiment A, 20 healthy adults (25.1 ± 7.6years; 23.0 ± 1.9 kg/m2) were monitored during their habitual bicycle commuting using a Global Positioning System device with a HR monitor for one week. In experiment B, 20 healthy adults (27.8 ± 4.7years; 24.1 ± 3.1 kg/m2) were assessed (peak oxygen uptake, VO2peak; peak power output, PPO) and the following characteristics of the cycling route were compared between active and inactive individuals for one week: time commuting; distance covered; speed; %HRmax; time spent at a vigorous intensity. ResultsParticipants in experiment A cycled at a moderate intensity (68.1 ± 8.7%HRmax) and covered ~4.2 ± 2.6 km per route. Meanwhile, the active and inactive individuals in experiment B showed similar VO2peak (P > 0.05), but the active participants reached a higher PPO (P < 0.05). Active individuals spent more time cycling, covered a higher distance, cycled at a higher speed, and showed a higher %HRmax and time spent at vigorous intensity than their inactive peers (Ps < 0.01). ConclusionBicycle commuting should be encouraged for adults to meet the physical activity guidelines. Policymakers, companies, educational institutions should consider implementing measures to promote bicycle commuting.

Optimization of Bike Routes for Sustainable Urban Road Network

The transport department of urban cities always needs to keep abreast of sustainable developments such as in Port Said city that is an important urban city in Egypt. Bike routes planning mission is not an easy occupation, especially in developing countries. Mixed traffic is the main shape of the transportation system in most of their systems. The increase of the bike user's percent is an expected objective and be one of the modern sustainable transport solutions. On another side, a lot of problems and accidents had been occurred according to bike crossings among other transport vehicles; cars, buses, taxis, and others. This paper aims at studying the introduction of the bike route's effectiveness. It concludes the driver's reaction to a definite planning scenario and the optimistic effect of the modal change on the objective function that has been assumed by attaching a suitable time-saving for bike users using the Artificial Neural Network ANNs Approach. It shows the effect of bike speed change on the route using a greedy algorithm. The study designated only four streets from seven selected streets to be suitable routes for bike routes introduction. The average bike speed is predicted to increase from 1.5 km per hour to be 2.4 km per hour after introducing the bike routes.

Impact of One-Way Streets and Contraflow on Low-Stress Bicycle Network Connectivity

One-way restrictions on local streets, which tend to have low traffic stress, can create a significant barrier to low-stress cycling. Contraflow, a treatment that undoes one-way restrictions on bike travel, has the potential to improve low-stress connectivity. Although contraflow is applied routinely in the Netherlands and Belgium, it has been sparingly applied in the United States. We propose refined measures of connectivity and accessibility that account for one-way restrictions by requiring a low-stress round trip path between origins and destinations. Different methods of associating origin–destination demand from polygons with a street network were analyzed. These methods are particularly important where there are one-way restrictions and irregular street networks because of the assumptions they entail in relation to first- and last-segment travel. In a case study of Greater Boston, we found that with the current bike network, low-stress connectivity between homes and jobs would increase from 1.2% to 8.7% if one-way restrictions on local streets were eliminated. We also found that even with a dense mesh of low-stress main bike routes, connectivity would still be 16% lower without contraflow on local streets than with. These results suggest that creating a network of main bike routes is not always enough; it is also important to provide contraflow on local streets. The Boston study also found that providing contraflow on selected links representing only 3% of local one-way street mileage delivered 40% of the connectivity impact of universal contraflow. Based on this finding, a method is proposed for prioritizing streets for contraflow conversion.

Assessment of PM2.5 Exposure during Cycle Trips in The Netherlands Using Low-Cost Sensors.

Air pollution, especially fine particulate matter (PM2.5), is a major environmental risk factor for human health in Europe. Monitoring of air quality takes place using expensive reference stations. Low-cost sensors are a promising addition to this official monitoring network as they add spatial and temporal resolution at low cost. Moreover, low-cost sensors might allow for better characterization of personal exposure to PM2.5. In this study, we use 500 dust (PM2.5) sensors mounted on bicycles to estimate typical PM2.5 levels to which cyclists are exposed in the province of Utrecht, the Netherlands, in the year 2020. We use co-located sensors at reference stations to calibrate and validate the mobile sensor data. We estimate that the average exposure to traffic related PM2.5, on top of background concentrations, is approximately 2 μg/m3. Our results suggest that cyclists close to major roads have a small, but consistently higher exposure to PM2.5 compared to routes with less traffic. The results allow for a detailed spatial representation of PM2.5 concentrations and show that choosing a different cycle route might lead to a lower exposure to PM2.5. Finally, we conclude that the use of mobile, low-cost sensors is a promising method to estimate exposure to air pollution.