Development of Highway Congestion Index with Fuzzy Set Models

Abstract

Development of a highway congestion index on the basis of expert and user opinions with fuzzy set theory was attempted. Forty 1-min videotape segments showing different highway traffic flow conditions were displayed to a group of highway experts and users. They were asked to complete the relevant questionnaires on the existence and acceptability of congestion for each video segment display. Five congestion-descriptive variables of travel speed, travel rate, delay rate, travel rate ratio, and delay ratio were determined for each video segment. Information about the values of congestion-descriptive variables for the displayed videos, questionnaire responses, and fuzzy set theory were used to develop congestion fuzzy set membership functions. The membership functions characterized the congestion intensity fuzzy values of “congested” and “unacceptably congested.” The membership functions were suggested as congestion indexes measured on a scale of 0 to 1. In the questionnaire, the surveyed group also provided opinions regarding the relative importance of the descriptive variables in explaining congestion. This information was used to determine average weighting values for the developed indexes. Using the average weighting values, overall indexes for “congested” and “unacceptably congested” were developed. The overall congestion indexes were also suggested for congestion intensity assessment and evaluation. The relationships between the Highway Capacity Manual levels of service and the developed congestion indexes were studied. The results were used to address some issues regarding normative index development. Although the study findings are based on a rather limited database and are location specific, the applied methodology can be used to capture congestion intensity perception in any future index development. The study index development was based on fuzzy set theory and is suggested as an alternative or complementary approach to past normative index development methods.