Bikeability and Emerging Phenomena in Cycling: Exploratory Analysis and Review

Abstract

Recent strategies to improve the performance of the cycling mode of transport are based on infrastructural, behavioral, and multimodal measures, which are related to the concept of bikeability. A literature review on “bikeability indexes” was conducted focusing on indicators, using a four-step systematic process. Fourteen studies were included for the final analysis and provided 138 indicators, 17 criteria, and four domains. The exploratory analysis evidenced limited application of indicators related to pollution, scarce use of indicators related to bicycle sharing systems (BSS), absence of indicators related to electric bicycles, lack of indicators related to digital solutions, and the need of a calibration and validation process for bikeability indexes. Considering the changes and opportunities created by emerging innovations (namely BSS and electric bicycles) and the health trade-off related to pollution reduction, this research reveals that the current bikeability indexes do not fully address the real potential of a cycle network, limiting its use as a comprehensive tool for the promotion of sustainable mobility.

The Role of Shared E-Scooter Systems in Urban Sustainability and Resilience during the Covid-19 Mobility Restrictions

“…Table 4 shows the different subjects searched to compound the studies of the impacts of sharing e-scooters systems in sustainability with different methodologies (discussion, LCA, survey, spatial analyses, pilot studies). The methodology used [65] comes to demonstrate that even if the number of papers about e-scooters and shared e-scooters in both platforms (Scopus and WoS) is growing over the years (when comparing the number of publications by year from 2016 until 2021), the ones focusing on sustainability impacts are still low.…”

Assessing bikeability with street view imagery and computer vision

“…Table 2 summarizes the issues mentioned above. Literature reviews on bikeability by Kellstedt et al (2021) and Castañon and Ribeiro (2021) indicate that the past development of bikeability assessment has been driven by innovative uses of advanced new technologies, thereby suggesting that newer technologies may overcome these issues mentioned above. While there have been studies that have utilized SVI and CV techniques to assess bikeability, and thus indicating the reliability of SVI as a data source that can be used in a scalable manner, they suffer from shortcomings which we seek to mitigate in our work.…”

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

“…Many empirical studies on bicycle travel analysis show that there are many factors that are considered when cyclists choose routes. They include travel distance or time [4]; safety [5]; stress [34]; pollution [35]; travel distance/time and safety [7]; travel time and suitability [14]; travel time and pollution [12]; travel distance, safety, and pollution [8]; and bikeability [36,37]. Due to the diverse set of influential factors that are at play during bicycle travel, route planners provide a variety of bicycle routes based on different factors (e.g., least elevation gain route, shortest distance route, safest route, bike friendly route, etc.)…”