Bicycling renaissance in North America?: Recent trends and alternative policies to promote bicycling

Over the past two decades, the number of bicycle trips in the United States has doubled. Since 48% of trips by all modes in American cities are shorter than three miles, the potential for further growth in bicycling seems enormous. So far, efforts to promote bicycling have focused on building bike paths and bike lanes. Although necessary, separate cycling facilities must be complemented by a comprehensive program to make all roads bikeable, through both physical adaptations and enforcement of cyclists' right to use the road. It seems likely that cycling will continue to grow in North America, but that its mode share will remain far lower than levels in northern Europe. Bicycling in Canada and especially the United States is impeded by the lack of a tradition of cycling for utilitarian purposes and by the marginal legal, cultural and infrastructure status of cyclists in both countries' automobile-based transport systems. As long as car use remains cheap and transportation policy remains dominated by motoring, bicycles will continue to be used primarily for recreation and not for daily urban travel in North America.     

Cycling to work in 90 large American cities: new evidence on the role of bike paths and lanes

This article analyzes the variation in bike commuting in large American cities, with a focus on assessing the influence of bike paths and lanes, which have been the main approach to increasing cycling in the USA. To examine the role of cycling facilities, we used a newly assembled dataset on the length of bike lanes and paths in 2008 collected directly from 90 of the 100 largest U.S. cities. Pearson’s correlation, bivariate quartile analysis, and two different types of regressions were used to measure the relationship between cycling levels and bikeways, as well as other explanatory and control variables. Ordinary Least Squares and Binary Logit Proportions regressions confirm that cities with a greater supply of bike paths and lanes have significantly higher bike commute rates—even when controlling for land use, climate, socioeconomic factors, gasoline prices, public transport supply, and cycling safety. Standard tests indicate that the models are a good fit, with R ² ranging between 0.60 and 0.65. Computed coefficients have the expected signs for all variables in the various regression models, but not all are statistically significant. Estimated elasticities indicate that both off-street paths and on-street lanes have a similar positive association with bike commute rates in U.S. cities. Our results are consistent with previous research on the importance of separate cycling facilities and provide additional information about the potentially different role of paths vs. lanes. Our analysis also revealed that cities with safer cycling, lower auto ownership, more students, less sprawl, and higher gasoline prices had more cycling to work. By comparison, annual precipitation, the number of cold and hot days, and public transport supply were not statistically significant predictors of bike commuting in large cities.     

Factors associated with proportions and miles of bicycling for transportation and recreation in six small US cities

The majority of bicycling in the US is for recreation rather than transportation purposes but few studies have examined the question of bicycling purpose. We use data from an online survey conducted in 2006 in six small cities in the western US to examine factors affecting bicycling for transportation compared to bicycling for recreation. The results indicate that individual, social-environment, and physical-environment factors have important influences on the balance between transportation and recreational bicycling and on miles of bicycling for each purpose. Bicycling comfort and an aversion to driving are associated with more transportation bicycling. A culture of utilitarian bicycling and short distances to destinations are also key factors for transportation bicycling. Bicycle infrastructure appears to play an indirect role through its effect on perceived bicycling safety and through the self-selection effect, by attracting bicycling-inclined people to bicycling-supportive communities.     

We can all get along: The alignment of driver and bicyclist roadway design preferences in the San Francisco Bay Area

Two trends in the United States—growth in bicycling and enthusiasm for complete streets—suggest a need to understand how various roadway users view roadway designs meant to accommodate multiple modes. While many studies have examined bicyclists’ roadway design preferences, there has been little investigation into the opinions of non-bicyclists who might bicycle in the future. Additionally, little research has explored the preferences of the motorists who share roads with cyclists—despite the fact that motorists compose the vast majority of roadway users in the United States and similarly developed countries.This paper presents results from an internet survey examining perceived comfort while driving and bicycling on various roadways among 265 non-bicycling drivers, bicycling drivers, and non-driving bicyclists in the San Francisco Bay Area. Analysis of variance tests revealed that both drivers and bicyclists are more comfortable on roadways with separated bicycling facilities than those with shared space. In particular, roadways with barrier-separated bicycle lanes were the most popular among all groups, regardless of bicycling frequency. Striped bicycle lanes, a common treatment in the United States, received mixed reviews: a majority of the sample believed that they benefit cyclists and drivers through predictability and legitimacy on the roadway, but the lanes were rated significantly less comfortable than barrier-separated treatments—particularly among potential bicyclists.These findings corroborate research on bicyclists’ preferences for roadway design and contribute a new understanding of motorists’ preferences. They also support the U.S. Federal Highway Administration’s efforts to encourage greater accommodation of bicyclists on urban streets.     

A hybrid-choice latent-class model for the analysis of the effects of weather on cycling demand

In this paper we analyze demand for cycling using a discrete choice model with latent variables and a discrete heterogeneity distribution for the taste parameters. More specifically, we use a hybrid choice model where latent variables not only enter into utility but also inform assignment to latent classes. Using a discrete choice experiment we analyze the effects of weather (temperature, rain, and snow), cycling time, slope, cycling facilities (bike lanes), and traffic on cycling decisions by members of Cornell University (in an area with cold and snowy winters and hilly topography). We show that cyclists can be separated into two segments based on a latent factor that summarizes cycling skills and experience. Specifically, cyclists with more skills and experience are less affected by adverse weather conditions. By deriving the median of the ratio of the marginal rate of substitution for the two classes, we show that rain deters cyclists with lower skills from bicycling 2.5 times more strongly than those with better cycling skills. The median effects also show that snow is almost 4 times more deterrent to the class of less experienced cyclists. We also model the effect of external restrictions (accidents, crime, mechanical problems) and physical condition as latent factors affecting cycling choices.     

The objective versus the perceived environment: what matters for bicycling?

This paper examines the relationship between the objectively measured and perceived built environment, and the relative strength of their association with bicycling behavior. By drawing on socio-cognitive theory, a conceptual model was proposed to explain the relationships between the objective environment, perceived environment, and bicycling behavior. Objective and perceived bike environments were measured using two latent constructs and structural equation modeling was employed to estimate the models based on data from three neighborhoods in Portland, Oregon. Results of this study showed that the perception of the environment had a direct and significant effect on bicycling behavior, while the direct effect of the objective environment on bicycling behavior became insignificant when controlling for perception. We therefore concluded that the objective environment may only indirectly affect bicycling behavior by influencing perceptions. An objectively good environment for bicycling was necessary but not sufficient for bicycling. Intervention programs to improve people’s perceptions of the environment may be necessary to reap the full potential of planning and design policies.     

Crowdsourced data for bicycling research and practice

ABSTRACT

Cities are promoting bicycling for transportation as an antidote to increased traffic congestion, obesity and related health issues, and air pollution. However, both research and practice have been stalled by lack of data on bicycling volumes, safety, infrastructure, and public attitudes. New technologies such as GPS-enabled smartphones, crowdsourcing tools, and social media are changing the potential sources for bicycling data. However, many of the developments are coming from data science and it can be difficult evaluate the strengths and limitations of crowdsourced data. In this narrative review we provide an overview and critique of crowdsourced data that are being used to fill gaps and advance bicycling behaviour and safety knowledge. We assess crowdsourced data used to map ridership (fitness, bike share, and GPS/accelerometer data), assess safety (web-map tools), map infrastructure (OpenStreetMap), and track attitudes (social media). For each category of data, we discuss the challenges and opportunities they offer for researchers and practitioners. Fitness app data can be used to model spatial variation in bicycling ridership volumes, and GPS/accelerometer data offer new potential to characterise route choice and origin-destination of bicycling trips; however, working with these data requires a high level of training in data science. New sources of safety and near miss data can be used to address underreporting and increase predictive capacity but require grassroots promotion and are often best used when combined with official reports. Crowdsourced bicycling infrastructure data can be timely and facilitate comparisons across multiple cities; however, such data must be assessed for consistency in route type labels. Using social media, it is possible to track reactions to bicycle policy and infrastructure changes, yet linking attitudes expressed on social media platforms with broader populations is a challenge. New data present opportunities for improving our understanding of bicycling and supporting decision making towards transportation options that are healthy and safe for all. However, there are challenges, such as who has data access and how data crowdsourced tools are funded, protection of individual privacy, representativeness of data and impact of biased data on equity in decision making, and stakeholder capacity to use data given the requirement for advanced data science skills. If cities are to benefit from these new data, methodological developments and tools and training for end-users will need to track with the momentum of crowdsourced data.     

The factors influencing bicycling in the Bangalore city

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

Synopsis of bicycle demand in the City of Toronto: Investigating the effects of perception,consciousness and comfortability on the purpose of biking and bike ownership

This paper provides an empirical basis for the evaluation of policies and programs that can increase the usage of bikes for different purposes as well as bike ownership. It uses an integrated econometric model of latent variable connecting multiple discrete choices. Empirical models are estimated by using a bicycle demand survey conducted in the City of Toronto in 2009. Empirical investigations reveal that latent perceptions of ‘bikeability’ and ‘safety consciousness’ directly influence the choice of biking. It is also found that the choice of the level of bike ownership (number of bikes) is directly influenced by latent ‘comfortability of biking’. The number of bikes owned moreover has a strong influence on the choices of biking for different purposes. It is clear that bike users in the City of Toronto are highly safety conscious. Increasing on-street and separate bike lanes proved to have the maximum effects on attracting more people to biking by increasing the perception of bikeability in the city, comfortability of biking in the city and increasing bike users’ sense of safety. In terms of individuals’ characteristics, older males are found to be the most conformable and younger females are the least comfortable group of cyclists in Toronto.     

Exploring the impact of walk–bike infrastructure,safety perception,and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

This study estimates a random parameter (mixed) logit model for active transportation (walk and bicycle) choices for work trips in the New York City (using 2010–2011 Regional Household Travel Survey Data). We explored the effects of traffic safety, walk–bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk–bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the local authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Further, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists, will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The model would be an essential tool to estimate the impact of improving traffic safety and walk–bike infrastructure which will assist in investment decision making.     

Optimal deployment of charging lanes for electric vehicles in transportation networks

Given the rapid development of charging-while-driving technology, we envision that charging lanes for electric vehicles can be deployed in regional or even urban road networks in the future and thus attempt to optimize their deployment in this paper. We first develop a new user equilibrium model to describe the equilibrium flow distribution across a road network where charging lanes are deployed. Drivers of electric vehicles, when traveling between their origins and destinations, are assumed to select routes and decide battery recharging plans to minimize their trip times while ensuring to complete their trips without running out of charge. The battery recharging plan will dictate which charging lane to use, how long to charge and at what speed to operate an electric vehicle. The speed will affect the amount of energy recharged as well as travel time. With the established user equilibrium conditions, we further formulate the deployment of charging lanes as a mathematical program with complementarity constraints. Both the network equilibrium and design models are solved by effective solution algorithms and demonstrated with numerical examples.     

Characterizing the speed and paths of shared bicycle use in Lyon

Data gathered relating to the Lyon’s shared bicycling system, Vélo’v, is used to analyze 11.6 millions bicycle trips in the city. The data show that bicycles now compete with the car in terms of speed in downtown Lyon. It also provides information on cycle flows that can be of use in the planning of dedicated bicycle lanes and other facilities.     

Making Cycling Irresistible: Lessons from The Netherlands,Denmark and Germany

Abstract

This article shows how the Netherlands, Denmark and Germany have made bicycling a safe, convenient and practical way to get around their cities. The analysis relies on national aggregate data as well as case studies of large and small cities in each country. The key to achieving high levels of cycling appears to be the provision of separate cycling facilities along heavily travelled roads and at intersections, combined with traffic calming of most residential neighbourhoods. Extensive cycling rights of way in the Netherlands, Denmark and Germany are complemented by ample bike parking, full integration with public transport, comprehensive traffic education and training of both cyclists and motorists, and a wide range of promotional events intended to generate enthusiasm and wide public support for cycling. In addition to their many pro‐bike policies and programmes, the Netherlands, Denmark and Germany make driving expensive as well as inconvenient in central cities through a host of taxes and restrictions on car ownership, use and parking. Moreover, strict land‐use policies foster compact, mixed‐use developments that generate shorter and thus more bikeable trips. It is the coordinated implementation of this multi‐faceted, mutually reinforcing set of policies that best explains the success of these three countries in promoting cycling. For comparison, the article portrays the marginal status of cycling in the UK and the USA, where only about 1% of trips are by bike.     

Increasing the capacity of signalized intersections by allocating exit lanes to turning movements

Unconventional intersection designs have been used to increase the capacity of intersections that are over‐saturated under conventional ones. However, existing unconventional designs typically require extra land space and their effectiveness often depends on drivers' familiarity with the uncommon operating rules. To overcome these challenges, we propose a new unconventional design, where movements that are mutually incompatible under the conventional design can be made compatible of each other by allocating exit lanes to them appropriately, thereby creating opportunities for capacity improvement. We develop a lane‐based capacity optimization model that incorporates the allocation of exit lanes as decision variables. The model is formulated as a Binary Mixed Integer Linear Programming problem, which can be efficiently solved by standard branch‐and‐bound algorithms. Numerical experiments show that significant capacity improvement can be obtained under our design. Besides proposing a new unconventional design, we also contribute to the literature of lane‐based signal optimization methods by providing a novel linear formulation for the latest, yet nonlinear, model described in Wong and Heydecker [Transportation Research Part B 45(4):667–681]. This improvement is methodologically beneficial as linear models are computationally more convenient than nonlinear ones. Copyright © 2017 John Wiley & Sons, Ltd.     

Influences on bicycle use

A stated preference experiment was performed in Edmonton in Canada to both examine the nature of various influences on bicycle use and obtain ratios among parameter values to be used in the development of a larger simulation of household travel behaviour. A total of 1128 questionnaires were completed and returned by current cyclists. Each questionnaire presented a pair of possible bicycle use alternatives and asked which was preferred for travel to a hypothetical all-day meeting or gathering (business or social). Alternatives were described by specifying the amounts of time spent on three different types of cycling facility and whether or not showers and/or secure bicycle parking were available at the destination. Indications of socio-economic character and levels of experience and comfort regarding cycling were also collected. The observations thus obtained were used to estimate the parameter values for a range of different utility functions in logit models representing this choice behaviour. The results indicate, among other things, that time spent cycling in mixed traffic is more onerous than time spent cycling on bike lanes or bike paths; that secure parking is more important than showers at the destination; and that cycling times on roadways tend to become less onerous as level of experience increases. Some of these results are novel and others are consistent with findings regarding bicycle use in work done by others, which is seen to add credence to this work. A review of previous findings concerning influences on cycling behaviour is also included.     

Multiple criteria evaluation of transportation system improvement projects: The case of korea

As a newly industrialized country, Korea has shown remarkable economic progress in the last three decades. This phenomenal growth has rapidly increased demands for better quality of life. This includes, among others, increasing demand for high quality transportation system services. In this paper, the method of Analytic Hierarchy Process (AHP) is utilized to evaluate rural highway improvement projects in Korea. The appropriate rural highway improvement projects for widening and paving were selected and studied on the basis of some selection criteria. The results have shown that there are some significant differences in prioritizing projects using the traditional economic evaluation method as compared to those resulting from the use of AHP. As demonstrated, the AHP proves to be an effective tool in evaluating transportation system projects.     

Critical success conditions of collaborative methods: a comparative evaluation of transport planning projects

This paper explores critical success conditions of collaborative planning projects in the area of urban transport, evaluating the impact of new collaborative methods, instruments and processes on project performance. Hypothesis building is based on a comparative, empirical research design, rather than on deductive theory construction. Potential critical success conditions are derived from literature. Based on five urban transport planning projects in Gothenburg (Sweden), London (United Kingdom), Milwaukee (United States), Tokyo (Japan) and Mexico City (Mexico), a rough set analysis of the five cases reveals validated success conditions, which can be used for formulating hypotheses for further research or for policy and process improvement. The results suggest that a dedicated management of the multi-actor network, a high diversity of actors, as well as an extensive use of knowledge integration methods in combination with a high network density are critical success conditions of these planning processes. Surprisingly, the extensive use of unilateral methods also showed to be an important success condition. The traditional role of the planner will have to be complemented with the expertise of network and methodology management. The authors conclude that rough set analysis can be a valuable addition to narrative, single-case analysis of collaborative urban transport planning processes.     

Renegotiating PPP Contracts: Reinforcing the ‘P' in Partnership

Abstract

The issue of renegotiation is becoming increasingly important as a tool to address uncertainty of public private partnership (PPP) projects and as a mechanism to restore its economic and financial equilibrium. This paper aims to understand how and why renegotiations occur in long-lasting PPP projects and what are the pros and cons of the renegotiation. We depart from a literature review on contract incompleteness and on the determinant factors for the renegotiation of infrastructure concessions. To illustrate the discussion, the case studies of nine European PPP projects are analysed by examining the specific exogenous and endogenous determinant factors that conduce to renegotiating contracts. The implications of contractual renegotiations are explained and summarized through a comparison of our case studies with literature. Although renegotiation, per se, is not a solution for the successful implementation of PPP projects, our findings reinforce the idea of contractual flexibility as a tool that allows adapting to uncertainty. Moreover, effective communication mechanisms allow a better response to unforeseen events, reinforcing the partners’ commitment to deliver a win–win project.     

极端复杂地质条件下TBM隧道施工关键技术研究及应用北大核心CSCD

大瑞铁路高黎贡山隧道、引汉济渭秦岭隧洞、滇中引水香炉山隧洞等工程的相继开工建设,使富水破碎极软地层带来的TBM卡机、高地应力极硬岩地层带来的岩爆等TBM施工问题日益凸显。文章首先对比阐述了国内TBM隧道工程建设过程中常遇到的软弱破碎、极硬花岗岩等典型不良地质及其对TBM掘进所带来的影响,在总结分析辽西北供水、引松供水、引洮供水等工程建设过程中出现的隧道局部塌方、TBM卡机等案例及其影响因素的基础上,以极端复杂地质条件TBM掘进关键技术为对象进行了系统研究论述,结果表明:(1)超前地质预报技术是TBM施工应对极端复杂地质的重要手段,但目前尚无法对前方中远距离地质状况进行准确量化预测;基于微震监测分析结果,根据可能发生的轻微、中等、强烈等不同等级的岩爆,制定对应处置措施;节理发育、炭质板岩、断层破碎带等不同软弱破碎地层,应采取针对性的防卡机措施,同时可根据不良地质段的长度来选择合适的脱困方案;(2)TBM推力、推进速度、刀盘转速及扭矩等掘进参数的异常波动,是表征掌子面前方地质条件状态的重要指标,TBM掘进前,根据前期预判的全断面硬岩、软弱破碎等围岩条件,分别选择合适的掘进参数;TBM掘进过程中,应基于掘进参数异常变化,纠正地质条件预判并采取对应的调控措施,进而确保TBM处于最佳掘进状态;(3)针对既有TBM难以适应现有地质条件的情况,以引洮供水隧洞、引红济石隧洞、引汉济渭隧洞等工程为例,对TBM改造技术进行了分析论述。最后,针对极端复杂地质条件下的TBM隧道工程建设新问题及其应对措施进行了展望与探讨。     

Using smartphones as a very low-cost tool for road inventories

Road inventories are a key component in the planning of road networks as they allow for efficient management and a better return on the investment. Current techniques for carrying out road inventories are expensive and entail long planning processes and data postprocessing. Furthermore, these inventories are only useful to those parties interested in designing and building road networks. This study presents a new method for create road inventories based on the use of the latest generation cellular phones, also called smartphones. This paper describes the use of several mobile apps developed for this project that were implemented during the different stages of road inventory process. The results indicate that the data processing speed, its low cost, and the ease of implementation from any type of vehicle validate the proposed procedure as an invaluable tool (1) to do inventories of all types of road networks that are not accessible to cars; (2) to manage the routine maintenance of small road networks; and (3) as a basis for future research projects on road design and outline.