Instrumented bikes and their use in studies on transportation behaviour, safety, and maintenance

ABSTRACT

Instrumented bikes are a critical tool to understanding cyclist behaviour and preferences to incorporate cycling into modelling, designing, and planning the transportation system. Literature using instrumented bikes for transportation-related research has increased in popularity, especially in the last 6 years. As these studies are growing in number and maturity, now seems a good time to review how the bikes have been used, choices of sensors and methodology, and where there are gaps to be filled by future work. Therefore, the objectives of this literature review are to 1) discuss sensor choice in relation to methodology, 2) review findings from topics studied using instrumented bikes, and 3) discuss gaps in the literature. Two databases were searched for transportation-based literature using instrumented bikes with a total of 75 articles meeting the inclusion criteria. The literature was organised into nine focus areas with the most common topics being E-bikes, vehicles passing cyclists, and critical events. The results show that instrumented bikes are versatile tools that can shed light on a variety of aspects of cyclist behaviour and safety as well as how to maintain the system for them. Various sensors were used for these studies, but cameras, GPS, and accelerometers were the most common. The review highlights the importance of study technique (naturalistic vs quasi-naturalistic vs other) on sensor choice with GPS and/or cameras being critical to any naturalistic study. However, GPS and cameras are the most challenging data types to work with due to difficulty and the time-consuming nature of processing the data. The variation in sensors also suggests some need to standardise set-ups for comparison of data across international contexts. Areas for future research are also discussed, including a new perspective for passing-distance studies and incorporating instrumented bikes into the connected vehicle/infrastructure space.

KEYWORDS:

• Instrumented bikes
• naturalistic cycling
• sensors
• behaviour
• safety

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Science Foundation Graduate Research Fellowship: [Grant Number DGE-1650044].