Context-specific volume–delay curves by combining crowd-sourced traffic data with automated traffic counters: A case study for London – FOSA
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Context-specific volume–delay curves by combining crowd-sourced traffic data with automated traffic counters: A case study for London

FOSA
FOSA

The city-scale research team recently published a paper…that uses innovative sources of real-world data to calibrate a widely used empirical relationship in traffic engineering. The paper aims to address the difficulty of calibrating the macroscopic relationship between traffic volume and speed….This would benefit the transportation planning by pinpointing the bottlenecks in fast-changing traffic environments
Context-specific volume–delay curves by combining crowd-sourced traffic data with automated traffic counters: A case study for London
Cambridge Journal of Data-Centric Engineering reported SGI News April 2021
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