Measuring speed consistency for freeway diverge areas using factor analysis

Xu Qu , Tang-yi Guo , Wei Wang , Qi-zhou Hu

Journal of Central South University ›› 2013, Vol. 20 ›› Issue (1) : 267 -273.

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Journal of Central South University ›› 2013, Vol. 20 ›› Issue (1) : 267 -273. DOI: 10.1007/s11771-013-1484-0
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Measuring speed consistency for freeway diverge areas using factor analysis

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Abstract

Although either absolute speed or speed difference can be considered as a measure for speed consistency, few researches consider both in practice. The factor analysis method was introduced to extract an optimal number of factors from numerous original measures. The freeway diverging zone was divided into four elements, namely the upstream, the diverge area, the downstream and the exit ramp. Operating speeds together with individual vehicle speeds were collected at each element with radar guns. Following the factor analysis procedure, two factors, which explain 96.722% of the variance in the original data, were retained from the initial seven speed measures. According to the loadings after Varimax rotation, the two factors are clearly classified into two categories. The first category is named “speed scale” reflecting the absolute speed, and the other one is named “speed dispersion” interpreting speed discreteness. Then, the weighted score of speed consistency for each diverge area is given in terms of linear combination of the two retained factors. To facilitate the level classification of speed consistency, the weighted scores are normalized in the range of (0, 1.0). The criterion for speed consistency classification is given as 0≤FN<0.30, good consistency; 0.30≤FN<0.60, fair consistency; 0.60≤FN≤1.00, poor consistency. The validation by comparing with previously developed measures shows that the proposed measure is acceptable in evaluating speed consistency.

Keywords

safety / freeway / speed consistency / factor analysis

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Xu Qu, Tang-yi Guo, Wei Wang, Qi-zhou Hu. Measuring speed consistency for freeway diverge areas using factor analysis. Journal of Central South University, 2013, 20(1): 267-273 DOI:10.1007/s11771-013-1484-0

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