Context-sensitive, first-principles approach to bicycle speed estimation

• Published in: IET intelligent transport systems Vol. 11; no. 7; pp. 411 - 416
• Main Authors: Tengattini, Simone, Bigazzi, Alexander York
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 01.09.2017
• Subjects: advanced traffic signal systems; bicycle free‐flow speeds; bicycles; clearance interval calculation; context‐sensitive bicycle speed estimation; estimation theory; first‐principles approach; geometric design; health assessment; mathematical analysis; mathematical framework; microsimulation models; Research Article; road grade; road safety; roadway attributes; safety assessment; traffic signal operations; transportation; estimation theory; geometric design; clearance interval calculation; mathematical framework; road grade; mathematical analysis; road safety; advanced traffic signal systems; transportation; safety assessment; health assessment; context-sensitive bicycle speed estimation; bicycle free-flow speeds; microsimulation models; roadway attributes; bicycles; first-principles approach; traffic signal operations
• ISSN: 1751-956X; 1751-9578; 1751-9578
• DOI: 10.1049/iet-its.2017.0012

Bicycle speed estimation is important for geometric design, traffic signal operations, microsimulation models, and health and safety assessment, among other applications. Bicycle speeds can vary greatly with the characteristics and power output of the rider and with travel conditions, especially road grade. This study presents a mathematical framework to address the non-trivial and practical problem of estimating bicycle free-flow speeds in a way that is sensitive to cyclist and roadway attributes. A closed expression is derived from first principles to determine speed from bicyclist power output. The method is extended to the problem of speed estimation for bicycles with limited gearing. Results are consistent with speed surveys in the literature. Application of the method to clearance interval calculation demonstrates the importance of context-sensitive bicycle speed estimation for advanced traffic signal systems.