01336724

Component

The major factors which contribute to freeway work zone capacity reduction in different areas vary widely, and the data availability for freeway work zone capacity estimation is naturally different from one site to another. The objective of this study is to develop a decision-making model based on rough set and information entropy for freeway work zone capacity estimation, taking into account the regional differences and the data availability for specific work zones. Rough sets are used to extract classification decision rules based on observed work zone data, in which the information entropy tools were introduced to discretize the continuous work zone data, such as speed, distance, without changing their properties. The proposed model was implemented in the MatLAB software with the capacity data obtained from Maryland and Texas, which were used to construct seven groups of decision-making rough sets. The validation results show that the newly developed model is capable to discover the major factors in determining freeway work zone capacity and generate decision-making rules for work zone capacity estimation according to given conditional attributes. The average errors of the training samples for each rule are less than 100 pcphpl (<10%), which indicates improved performance in comparison with the existing work zone capacity models.

01329018

11-3207

English

19p

2011

Transportation Research Board 90th Annual Meeting

DVD

Figures (4) ; References (31) ; Tables (6)

Decision making; Entropy (Communications); Highway capacity; Traffic data; Traffic models; Transportation planning; Validation; Work zone safety; Work zone traffic control

Rough set analysis

Maryland; Texas

Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2011 Paper #11-3207

TRIS, TRB

Feb 17 2011 6:26PM