01656820

Component

Cycling is an increasingly popular mode of travel in cities owing to the great advantages that it offers in terms of space consumption, health and environmental sustainability. However, cycling is still also perceived as relatively unsafe, and therefore it has yet to be adopted to a wider extent by users as a true alternative to the private car. Rising accident numbers, unfortunately, confirm this perception as reality,with a particular source of hazard appearing to originate from the interaction of cyclists with motorised traffic at low speeds in urban areas. Technological advances in recent years have resulted in a number of attempts to develop systems to prevent cyclist-vehicle collisions, but they have generally stumbled upon the challenge of accurate cyclist localisation and tracking, which can enable predicting a collision within a short-term time-horizon (5-10 seconds). Indeed, cyclist positioning accuracy is essential for any collision avoidance system, not only to ensure the effective operation of the system, but to minimise the occurrence of false alerts. As such, this paper focuses on the aspect of accurate bicycle localisation and presents a novel sensor fusion method to improve positioning accuracy and reliability based on an instrumented bicycle system. The paper describes the derivations of the essential models and design of the algorithms, and then presents the results from a field experiment in order to demonstrate the overall approach.

This paper was sponsored by TRB committee ABJ35 Standing Committee on Highway Traffic Monitoring.

18-00973

English

6p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; Photos; References

Algorithms; Bicycle crashes; Bicycles; Data fusion; Instrumented vehicles; Mathematical prediction; Safety; Tracking systems

Localization

Data and Information Technology; Pedestrians and Bicyclists; Vehicles and Equipment

Transportation Research Board Annual Meeting 2018 Paper #18-00973

TRIS, TRB, ATRI

Jan 8 2018 10:14AM