Reference:
A. Jamshidnejad and
B. De Schutter,
"Estimation of the generalized average traffic speed based on
microscopic measurements," Transportmetrica A: Transport
Science, vol. 11, no. 6, pp. 525-546, 2015.
Abstract:
The average speed of vehicles plays an important role in traffic
engineering. In almost any model-based traffic monitoring, analysis,
or control application the average speed is required as a measure of
performance or as an input for traffic models used to simulate fuel
consumption, vehicle emissions, or traffic noise. The average speed is
also used in algorithms that estimate the travel time. It also appears
in the fundamental equation of traffic where density is calculated
based on the average speed and flow. This article presents a new
methodology for estimating the time-space-mean speed (TSMS), which is
an equivalent for the generalized speed introduced by Edie
in the paper "Discussion of Traffic Stream Measurements and
Definitions" (Proceedings of the 2nd International Symposium on
the Theory of Traffic Flow, Paris, France, pp. 139-154, 1963). To
this aim, first tight upper and lower bounds are developed for the
TSMS using individual vehicle speeds that are obtained via point
measurements. To estimate the TSMS from these bounds, and to deal with
the cases where the trajectories of the vehicles might not be straight
lines, a convex combination of the upper and lower bounds is
introduced. In order to assess the convex combination and to compare
its performance with other formulas in literature, two real-life data
sets corresponding to the NGSIM data for the I-880 highway in the San
Francisco Bay Area, and the A13 data near Rotterdam-Delft are used. At
the end, MATLAB simulations are presented to cover scenarios that are
not included in the available real-life data sets. The results
produced by the new formula, both for the real-life data sets and for
MATLAB simulations, are found to be more accurate compared with other
available formulas in literature.