Module 2 : Traffic Measurement Procedures

Lecture 05 : Measurement at a Point

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	Multiple linear regression model Multiple linear regression method try to represent the speed of a traffic stream as function of number of variables. For example, the percentile speed $v_p$ can represented as: $$v_p=v_f+c_1\times V_c+c_2\times V_t+c_3\times V_r+c_4\times V_o+c_5\times V_a$$ (1) where $v_f$ is the free speed, $V_c$ is the number of passenger cars, $V_c$ is the number of trucks $V_r$ is the number of recreational vehicles, $V_r$ is the number of other types of vehicles, $V_a$ is the number of vehicles moving against the current stream, $C_1$ to $C_5$ are coefficient representing the relative sizes of speed reductions for each vehicle type. Although this model was formulated for two lane highways with opposing traffic flow, it could be applied to multi-lane highways by setting the coefficient $C_5$ to zero. Using the speed reduction coefficients, $E_n$, the PCU for a vehicle type $n$ is calculated as: $$E_n=\frac{C_n}{C_1}$$ where $C_n$ is the speed reduction coefficient for vehicle type n and $C_1$ is the speed reduction coefficient for passenger cars.