Empirical study of traffic velocity distribution and its effect on VANETs connectivity

Abstract

In this article we use real traffic data to confirm that vehicle velocities follow Gaussian distribution in steady state traffic regimes (free-flow, and congestion). We also show that in the transition between free-flow and congestion, the velocity distribution is better modeled by generalized extreme value distribution (GEV). We study the effect of the different models on estimating the probability distribution of connectivity duration between vehicles in vehicular ad-hoc networks.

Comment: 5 pages, 5 figures, presented at the ICCVE 2014 (International conference on connected vehicles & expo); http://www.iccve.org

Original document

The different versions of the original document can be found in:

• http://arxiv.org/abs/1502.07282

• http://arxiv.org/pdf/1502.07282

• http://xplorestaging.ieee.org/ielx7/7284675/7297490/07297577.pdf?arnumber=7297577,

http://dx.doi.org/10.1109/iccve.2014.7297577

• https://dblp.uni-trier.de/db/journals/corr/corr1502.html#AbueleninA15,

https://arxiv.org/pdf/1502.07282,

http://ui.adsabs.harvard.edu/abs/2015arXiv150207282A/abstract,

https://arxiv.org/abs/1502.07282,

https://www.researchgate.net/profile/Sherif_Abuelenin/publication/272845252_Empirical_Study_of_Traffic_Velocity_Distribution_and_its_Effect_on_VANETs_Connectivity/links/550bd9e10cf290bdc1121a57.pdf,

https://trid.trb.org/view/1427473,

http://export.arxiv.org/abs/1502.07282,

https://128.84.21.199/abs/1502.07282,

https://academic.microsoft.com/#/detail/1935973663