Cyclists’ exposure to air pollution, noise, and greenery: a population-level spatial analysis approach

Urban travel exposes people to a range of environmental qualities with significant health and wellbeing impacts. Nevertheless, the understanding of travel-related environmental exposure has remained limited. Here, we present a novel approach for population-level assessment of multiple environmental exposure for active travel. It enables analyses of (1) urban scale exposure variation, (2) alternative routes’ potential to improve exposure levels per exposure type, and (3) by combining multiple exposures. We demonstrate the approach’s feasibility by analysing cyclists’ air pollution, noise, and greenery exposure in Helsinki, Finland. We apply an in-house developed route-planning and exposure assessment software and integrate to the analysis 3.1 million cycling trips from the local bike-sharing system. We show that especially noise exposure from cycling exceeds healthy thresholds, but that cyclists can influence their exposure by route choice. The proposed approach enables planners and individual citizens to identify (un)healthy travel environments from the exposure perspective, and to compare areas in respect to how well their environmental quality supports active travel. Transferable open tools and data further support the implementation of the approach in other cities.Peer reviewe

Toward Sustainability: Bike-Sharing Systems Design, Simulation and Management

The goal of this Special Issue is to discuss new challenges in the simulation and management problems of both traditional and innovative bike-sharing systems, to ultimately encourage the competitiveness and attractiveness of BSSs, and contribute to the further promotion of sustainable mobility. We have selected thirteen papers for publication in this Special Issue

Modeling Route Choice of Utilitarian Bikeshare Users from GPS Data

This research examines the behavior of bikeshare users from Grid Bikeshare Program in Phoenix, Arizona under two behavioral frameworks: facility usage assessment and route choice assessment. The analysis is performed for the two different categories of subscribers: registered and casual subscribers. This is the first study that uses the real-time GPS data from bikeshare users to model their route preferences. The data used for this study were obtained from 9,101 trips made by 1,866 bikeshare. An important aspect of this bikeshare is that it allows non-station origin and destinations. The GPS points collected from the trips made by bikeshare users were matched to the street base network to determine the attributes of the route followed by the cyclists. Facility usage assessment included the determinations of use of roadway segments based on Annual Average Daily Traffic, posted speed limit, and roadway classification. Similarly, wrong direction riding behavior on the road was compared for one-way versus two-way roads and road segments with bicycle facilities versus without bicycle-facilities. Route choice decisions were modeled using the Path Size Logit model, which is based on a Multinomial Logit framework. The major findings include behavioral differences between the two groups of users such as average distance travelled, time of the day and day of the week variation and composition of the total users. Registered users, although fewer in number, made significant number of trips. Casual users were involved more in wrong direction riding in forty selected road segments from Downtown of Phoenix. The results from the discrete route choice model show that riders were very sensitive to travel distance, with positive utility towards using bike-friendly infrastructure. Having bike-specific infrastructures for the complete route is equivalent to decreasing distance by 44.9% (53.3% for casual users). Left turns imposed higher disutility for casual users as compared to right turns. A number of signalized intersections had a positive effect in selecting the route whereas the proportion of one-way segments, traffic volume and length of the route had a negative influence on route choice

Promoting Bicycle Commuter Safety, Research Report 11-08

We present an overview of the risks associated with cycling to emphasize the need for safety. We focus on the application of frameworks from social psychology to education, one of the 5 Es—engineering, education, enforcement, encouragement, and evaluation. We use the structure of the 5 Es to organize information with particular attention to engineering and education in the literature review. Engineering is essential because the infrastructure is vital to protecting cyclists. Education is emphasized since the central focus of the report is safety

What It’s Like to Ride a Bike: Understanding Cyclist Experiences

Cyclists can make important contributions to transport policy, if only we ask them. This thesis explores how people experience cycling in three case study cities – Perth, Melbourne and Utrecht. Cyclists were recruited for semi-structured and go-along interviews. The key findings indicate that the combination of traditional and mobile methods yield valuable information for developing understandings of the embodied experience of cycling, which can be used to inform policy and guide the creation of sustainable cities

2015 Annual Report Transportation Research Center for Livable Communities

Table of Contents Messages from the Director and Representatives TRCLC Mission and Objectives Center Personnel Research Investigators Consortia Our Research List of Research Projects Highlighted Projects Technology Transfer and Outreach Activities Student Awards Upcoming Event

Book of abstracts of the 24th Euro Working Group on Transportation Meeting

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Estimation of Average Annual Daily Bicycle Count Using Bike-Share GPS Data and Bike Counter Data for an Urban Active Transportation Network

In 2018, the City of Kelowna entered into a license agreement with Dropbike to operate a dockless bike-share pilot in and around the downtown core. The bikes were tracked by the user's cell phone GPS through the Dropbike app. The City's Active Transportation team recognized that this GPS data could help understand the routes used by cyclists which would then inform decision-making for infrastructure improvements. Using OSMnx and NetworkX, the map of Kelowna was converted into a graph network to map inaccurate, infrequent GPS points to the nearest street intersection, calculate the potential paths taken by cyclists and count the number of trips by street segment though the comparison of different path-finding models. Combined with the data from four counters around downtown, a mixed effects statistical model and a least squares optimization were used to estimate a relationship between the different traffic patterns of the bike-share and counter data. Using this relationship based on sparse data input from physical counting stations and bike share data, estimations and visualizations of the annual daily bicycle volume in downtown Kelowna were produced. The analysis, modelling and visualization helped to better understand how the bike network was being used in the urban center, including non-traditional routes such as laneways and highway crossings.Comment: Published in 17th International Conference on Data Science (ICDATA'21