01592751

Component

Classical traffic flow models cannot be readily applied in heterogeneous traffic systems owing to the complex nature of their traffic dynamics. This paper develops a stochastic macroscopic model for traffic state estimation and short-term prediction in such systems. The proposed model takes into account the wide variation in the operating and performance characteristics of vehicles in heterogeneous condition through the use of variable fundamental diagrams (FDs) for different links. The model also allows for the underestimation of flow and speed due to the effect of vehicular influence area in the stated traffic condition. For this, normally distributed stochastic state influencing terms are used with the basic state estimation equations. In addition, an empirical parameter is introduced in the speed dynamics of the model to capture the sensitivity of traffic speed to the speeds of multiple leaders in a heterogeneous mix. To confirm the structure of the FD, initially the speed-density plots of the field data for different links are fitted with four general structures: namely, the linear, logarithmic, exponential and polynomial forms. It is revealed that the 3rd degree polynomial structure is best suited for prevailing traffic condition. The optimized link-specific parameters of the model comply with those obtained from the regression analysis. Field validation with high-resolution traffic data proved that the proposed model can capture traffic dynamics quite accurately. To determine the individual contributions of the proposed model features, different structural variations of the final model are also investigated.

This paper was sponsored by TRB committee AHB45 Standing Committee on Traffic Flow Theory and Characteristics.

01584066

16-2730

English

18p

2016

Transportation Research Board 95th Annual Meeting

Digital/other

Figures; References; Tables

Macroscopic traffic flow; Stochastic processes; Traffic models; Vehicle mix

Fundamental diagram

Dhaka (Bangladesh)

Data and Information Technology; Highways; Operations and Traffic Management

Transportation Research Board Annual Meeting 2016 Paper #16-2730

TRIS, TRB, ATRI

Jan 12 2016 5:12PM