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ISSN: 2165-784X

Journal of Civil & Environmental Engineering
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Research Article

Updated Traffic Flow Dispersion Model Considering Effects of in-Vehicle Advisory Messages

Fengxiang Qiao*, Qing Li and Lei Yu

Innovative Transportation Research Institute, Texas Southern University, USA

*Corresponding Author:
Fengxiang Qiao
PhD, Professor, Innovative Transportation Research Institute Texas Southern University
3100 Cleburne Street, Houston, Texas - 77004 USA
Tel: 713-313-1915; Fax: 713-313-1856;
E-mail: [email protected]

Received date: February 20, 2017; Accepted date: April 11, 2017; Published date: April 15, 2017

Citation: Qiao F, Li Q, Yu L (2017) Updated Traffic Flow Dispersion Model Considering Effects of in-Vehicle Advisory Messages. J Civil Environ Eng 7: 270. doi: 10.4172/2165-784X.1000270

Copyright: © 2017 Qiao F, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Traditional dispersion models; such as the travel time distribution based normal distribution model and geometric distribution model; are dedicated to traffic situations with conventional traffic signs and signals; which may not be able to depict the platoon dispersion phenomenon under a connected vehicle system with in-vehicle advisory messages. This research re-examines the traditional dispersion models with suitable adjustment considering impacts of in-vehicle messages. A correction factor was employed to update the travel time distribution model; while travel time distributions of leading vehicles with and without the in-vehicle messages were simulated in a driving simulator with forty-five subjects tested. Parameter calibrations for travel time dispersion of traffic flow in work zone and intersections with sun glares were conducted to illustrate the entire modeling and calibration procedure. With more practical simulations and field tests; the flow dispersion models can be further calibrated for more applications in traffic flow simulation and optimizations.

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