| dc.description.abstract | The objective of this paper is to develop motorized level of service models using advanced heuristic techniques like functional networks, ordered probit analysis, and multivariate autoregressive spline for uncontrolled intersections under mixed traffic conditions. A total of 13 uncontrolled intersections from India are chosen and geometric, traffic, and roadside environmental data are collected using high-definition cameras. A novel influence area (INA) method for critical gap and follow-up time measurement is also developed. Over 7,000 effective uncontrolled intersection motorized driver responses are collected based on user satisfaction scores (1 = excellent to 6 = very bad). Eight variables with high significance (p<0.001) effects on perceived scores from Spearman’s correlation technique are modeled. Functional networks model showed greater efficiency as indicated by greater marginal ranking index of 11 (leading to lowest rank of first) among all the three level of service models proposed in this study. According to the sensitivity analysis, analogous to the proposed functional network model, volume to capacity ratio (highest effect), percentage of on-street parking (second highest effect), and service delay (third highest effect) showed superlative sensitivity toward level of service predictions at uncontrolled intersections compared to other parameters. The imperative outcomes of this research may help transport planners and traffic engineers to quantify operational evaluation of uncontrolled intersections and take crucial decisions toward their improvement. | |
