An Empirical Reappraisal of the Level of Traffic Stress Framework
Laura Cabral, Toole DesignShow Abstract View Presentation
Amy Kim, University of Alberta
Measuring bicycle network connectivity requires a decision on what elements of the street network should be considered part of the cycling network. Several frameworks exist to define the level of service or level of comfort of different cycling environments, but few explicitly consider the unique preferences of different cyclist types. This is one of the strengths of the Level of Traffic Stress (LTS) framework, which roughly matches its four levels of infrastructure ratings to the Four Types of Cyclists typology (No Way No How, Interested but Concerned, Enthused and Confident, and Strong and Fearless). Despite its popularity and ease of use, the LTS framework has several limitations, including the lack of empirical evidence to define thresholds that trigger a change in LTS level. The cyclist typology it relies on was also subjectively developed. This work builds on our previous finding that cyclists form three groups rather than four when derived from empirical data: Uncomfortable or Uninterested, Cautious Majority, and Very Comfortable Cyclists. We use survey data from Edmonton, Canada to update the LTS framework such that levels match the three types of cyclists. Direct infrastructure ratings, binary logistic regression, and route choice data provide the empirical foundation to determine infrastructure characteristics that are suitable for the three types of cyclists. The adjusted framework is called Level of Cycling Comfort and emphasizes high comfort rather than low stress. We apply the framework to Edmonton and compare connectivity outcomes using both LTS and LCC frameworks.
Validation of Bicycle Level of Traffic Stress and Perceived Safety: A Study of Children in Denver
Nicholas Ferenchak, University of New MexicoShow Abstract View Presentation
Wesley Marshall, University of Colorado, Denver
The Level of Traffic Stress (LTS) methodology was developed to measure, track, and improve the suitability of bicycle networks. Thanks to the simplicity of its data needs and interpretation, LTS has been implemented by several states, regions, cities, non-profits, and researchers. However, relatively few validations of the methodology exist. There is a specific gap in terms of safety perceptions for children, an important group since it serves as the critical population for LTS 1. This study validates LTS using a survey of parents in Denver, Colorado, in which we ask them about perceived safety and biking allowance relative to roadway design characteristics. After we determine the LTS score and biking allowance rates for 612 roadway scenarios, we use a one-way analysis of variance (ANOVA) to determine the suitability of LTS for children. Findings suggest that while LTS 1 and LTS 4 align well with stated preferences, children can also tolerate some roadway conditions that are currently considered LTS 2 or even LTS 3. These scenarios are primarily on low-volume roadways that have bike lanes. By further refining LTS, we hope to ensure that all populations have access to safe and comfortable bicycle facilities.
The Role of Attitudes in Perceptions of Bicycle Facilities: A Latent-Class Regression Approach
Calvin Clark, Georgia Institute of Technology (Georgia Tech)Show Abstract View Presentation
Patricia Mokhtarian, Georgia Institute of Technology (Georgia Tech)
Giovanni Circella, University of California, Davis
Kari Watkins, Georgia Institute of Technology (Georgia Tech)
While many professionals support bicycling for transportation to improve public health, many potential cyclists see the risks from traffic injuries as a major barrier. The purpose of this study is to investigate the impact of bicycle facilities on perceptions of bikeability, and how these perceptions vary amongst different groups. A survey (N=2,157) was deployed in ten study neighborhoods as part of two research projects. Respondents were asked to rate a series of images of hypothetical roadways regarding comfort, safety, and willingness to try bicycling on such a roadway. Latent-class regression models were used to model these responses, with bicycle facility type and roadway characteristics as explanatory variables and sociodemographics and attitudes (car preference, bike enjoyment, risk tolerance, and anti-exercise) as covariates for class membership. A recurring theme among the presented solutions is the emergence of two pro-bicycle classes, distinguished by their risk tolerance, together with one pro-car class. Results indicate that the impact of protected bicycle facilities on perceptions are much higher for the pro-bike-risk-averse group. The major implication of these findings is that there likely exists a sizeable segment of the population that, although they may be just as interested in biking as the typical pro-bicycle class, are much more cautious in their decision-making, but would be persuadable by high-quality protected bicycle facilities.
A Grounded Theory Approach to Understanding Bicyclists Interactions on Unprotected Facilities: A Proof of Concept from Munich, Germany
Cat Silva, Technical University of MunichShow Abstract View Presentation
Kelly Clifton, Portland State University
Rolf Moeckel, Technical University of Munich
Protected bicycle lanes are held up as the end-all of bicycle infrastructure, with unprotected bicycle lanes being widely considered unsafe and inferior. This perspective is supported by existing research showing people’s preference for protected vs unprotected bicycle lanes. Scant research, however, has explored this topic area using an observational research method. When an observational method is used, the research is typically count-based and focused on predetermined sets of known variables determined prior to the observation period, hindering research from advancing findings beyond frequencies and known. Without a clearer understanding of how people are using and interacting on streets with either type of bicycle lane, it is difficult, if not impossible, to adequately assess whether, and which, facility type best accommodates safe bicycle mobility. This paper introduces a new qualitative-quantitative method for conducting observational research which takes a grounded theory approach to gain new insights into how people behave and interact while using street segments, intersections, and other public places. This method follows a four-step process which involves qualitatively identifying events recorded on video, using deductive and inductive logic to document independent variables associated with the event, and concludes in a quantitative analysis of the qualitatively produced data. As a display of the applications of this method, a case study is presented here which used the new method to investigate bicyclist’s interactions with other road users on a street segment with an unprotected bicycle lanes in Munich, Germany.
User-Rated Comfort and Preference of Separated Bike Lane Intersection Designs
Chris Monsere, Portland State UniversityShow Abstract View Presentation
Nathan McNeil, Portland State University
Rebecca Sanders, Arizona State University
Improved bicycle infrastructure has become increasingly common in the United States as cities seek to attract the new riders, including the demographics of people who do not feel comfortable riding with motor vehicle traffic. A key tool in low-stress networks are separated or protected bicycle lanes and intersections are the critical links. This paper presents an analysis of the perceived level of comfort of current and potential bicyclists from 277 survey respondents who rated 26 first-person video clips of a bicyclist riding through mixing zones, lateral shifts, bend-in, bend-out and protected intersection designs. A total of 7,166 ratings were obtained from surveys conducted at four locations in Oregon, Minnesota, and Maryland, including urban and suburban locations. Survey respondents were categorized into four groups based on their response to attitudes and bicycling behavior by cluster analysis. Descriptive analysis and regression modeling results find that designs that minimize interactions with motor vehicles, such as fully separated signal phases and protected intersections, are rated as most comfortable (72% of respondents rated them as very comfortable or somewhat comfortable). Mean comfort drops off significantly for other designs and interactions with turning vehicles result in lower comfort ratings though there are differences for each design. Importantly, as the exposure distance, measured as the distance a person on a bicycle is exposed to traffic, increases the comfort decreases.