Classification of Bicycle Traffic Patterns in Five North American Cities

Abstract

This study used a unique database of long-term bicycle counts from 38 locations in five North American cities and along the Route Verte in Quebec, Canada, to analyze bicycle ridership patterns. The cities in the study were Montreal, Quebec; Ottawa, Ontario; and Vancouver, British Columbia, in Canada and Portland, Oregon, and San Francisco, California, in the United States. Count data showed that the bicycle volume patterns at each location could be classified as utilitarian, mixed utilitarian, mixed recreational, and recreational. Study locations classified by these categories were found to have consistent hourly and weekly traffic patterns across cities, despite considerable differences between the cities in their weather, size, and urban form. Seasonal patterns across the four categories and in the cities also were identified. Expansion factors for each classification are presented by hour and day of the week. Monthly expansion factors are presented for each city. Finally, traffic volume characteristics are presented for comparison purposes.

Examining travel patterns and characteristics in a bikesharing network and implications for data-driven decision supports: Case study in the Washington DC area

“…1c. The bikeshare trip distributions show a primary utilitarian pattern (Miranda-Moreno et al, 2013). It is consistent with the 2016 CaBi survey (LDA Consulting, 2016), where 65% of respondents confirmed that commuting was a primary trip purpose for their bikeshare usage.…”

“…7 shows the comparisons of the temporal distributions of hourly averaged trip counts between weekday and weekend by different types of trips and users respectively. Both the O-O trip users and casual users take more trips in weekend than in weekday, expressing a typical recreational pattern (Miranda-Moreno et al, 2013) as shown in Fig. 7a and Fig.…”

“…In general, bike users take two basic types of trips in terms of trip purpose, which is either utilitarian or recreational (Miranda-Moreno et al, 2013). If the primary purpose of a trip is utilitarian, for example, commuting for work, the bike user would more likely prefer a shorter travel time to reach the destination and the user normally does not take any intermediate stop (Conley and Agrawal, 2016).…”

Crowdsourcing Bicycle Volumes: Exploring the role of volunteered geographic information and established monitoring methods

“…In terms of time-based factoring and trip purposes, this study provides further evidence that the bicycle factor groupings developed by Miranda-Moreno et al (2013) later extended to mixed-mode trail traffic by Hankey et al ( 2014) generally are supported by the CycleTracks trip purpose responses. Researchers and practitioners are urged caution in the application of a potentially growing field of crowdsourced datasets, for they may or may not represent the given population that is considered in a transportation planning context.…”

Photos, tweets, and trails: Are social media proxies for urban trail use?

“…These efforts typically involve establishment of a set of permanent automated counters at a fixed number of locations believed to represent specific traffic patterns and then collection of a large number of short-duration (e.g., two to seven day) samples that can be used to characterize flows on a network. Statistics and ratios from the permanent sites are used to extrapolate the sample counts and obtain estimates of daily traffic (Federal Highway Administration, 2013;El Esawey, Lim, Sayed, & Mosa, 2013;Miranda-Moreno, Nosal, Schneider, & Proulx, 2013;Nordback, Marshall, Janson, & Stolz, 2013;Hankey, Lindsey, & Marshall, 2014). Several studies of trail use using these technologies and monitoring approaches have been reported (e.g., Lindsey, Wilson, Rubchinskaya, Yang, & Han, 2007;Wang, Lindsey, Hankey, & Hoff, 2014).…”