Recalibration of the BPR function for the strategic modelling of connected and autonomous vehicles

Abstract

This paper assesses the adequacy of the BPR volume delay function for the strategic modelling of Connected and Autonomous Vehicles (CAVs). Three testbed environments are simulated at 10% increments of CAV penetration rates (CPR) to observe network performance in mixed fleet environments. The microsimulation dataset is compared with the BPR travel time predictions to evaluate the need for recalibration. Where appropriate, the BPR modelling parameters are redefined as a function of the CPR. The predictive quality of the recalibrated model is then validated by comparing it against the BPR function on synthetic data. The numerical results indicate an overall improvement in travel time prediction using the recalibrated model, with a significant reduction in root mean square error from 15.16 to 8.86. The recalibrated model also outperformed the traditional BPR model in 67% of the 4620 cases used for validation, and better-predicted travel time by 5.43 times.

KEYWORDS:

• Connected and autonomous vehicles
• volume delay function
• strategic modelling
• microsimulation

Acknowledgements

The authors would like to acknowledge the assistance provided by the Research Centre for Integrated Transport Innovation (rCITI), School of Civil and Environmental Engineering, University of New South Wales (UNSW) Sydney, NSW 2052 Australia.

Disclosure statement

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