An advanced subway train localization system using a vision-based kilometer marker recognition-assisted multi-sensor fusion method

Abstract

To solve the high costs of the existing transponder/odometer-based wayside subway train localization method and the discontinuity of the GNSS-based subway train localization method in blocked GNSS environments, an advanced and alternative subway train localization system using the INS/Vision/ODO/MM fusion method is first proposed in this research. To evaluate the performance of the proposed INS/Vision/ODO/MM fusion method, a railway test was conducted on the Beijing Changping Line. The results show the proposed localization method can provide available and continuous 1-D positioning results with an accuracy of 10.82 m, which is a 52.71% improvement compared with the existing ATO. It also shows that the proposed vision-aided multi-sensor fusion method can be used as an alternative to the existing wayside-transponder-based localization system to provide navigation solutions for train safe operation without relying on wayside equipment and with low cost and easy maintenance.

KEYWORDS:

• Subway train localization
• vision identification
• autonomous localization
• multi-sensor integrated navigation

Disclosure statement

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

Data availability statement

Data will be made available on request.