Spatial and temporal memory effects in the Nagel-Schreckenberg model for crowdsourced traffic property determination
Name
PhysRevE.104.044102.pdf
Description
Published version
Size
7.77 MB
Format
Adobe PDF
Checksum (MD5)
c6cfdf591efa09d16a017e1233e1b1fa
Author(s)
Botshekan, Meshkat
Ulm, Franz-Josef
Date Issued
2021
Journal
Physical Review E
Publisher
American Physical Society (APS)
Citation
Botshekan, Meshkat and Ulm, Franz-Josef. 2021. "Spatial and temporal memory effects in the Nagel-Schreckenberg model for crowdsourced traffic property determination." Physical Review E, 104 (4).
Version
Final published version
Abstract
We investigate the spatial and temporal memory effects of traffic density and velocity in the Nagel-Schreckenberg cellular automaton model. We show that the two-point correlation function of vehicle occupancy provides access to spatial memory effects, such as headway, and the velocity autocovariance function to temporal memory effects such as traffic relaxation time and traffic compressibility. We develop stochasticity-density plots that permit determination of traffic density and stochasticity from the isotherms of first- and second-order velocity statistics of a randomly selected vehicle. Specifically, provided ergodicity and stationarity, these stochasticity-density plots permit a direct determination of traffic properties from crowdsourced measurements of velocities of vehicles. We illustrate the predictive prowess of the approach for crowdsourced vehicle speed data collected by anonymous smartphone measurements for the state of Massachusetts, USA, as a powerful alternative to classical traffic property estimates from spatially distributed user counts.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
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DOI of Published Version
https://doi.org/10.1103/PHYSREVE.104.044102
