The paper presents a classification and analysis of the results achieved using various tools for the estimation of level of service (LOS) of urban streets. The basic premise of urban streets and LOS are discussed. LOS is analyzed quantitatively and qualitatively. Average travel speed (ATS) on street segments is considered as the measure of effectiveness in defining LOS criteria of an urban street using quantitative methods. The travel speed data collection procedure has been changing over time from the traditional followed moving observer method to a distance measuring instrument and now global positioning system is being extensively used worldwide. Classifying urban streets into number of classes and ATSs on street segments into number of LOS categories are essential components of LOS analysis. Emphasis is put on application of soft computing techniques such as fuzzy set theory, genetic algorithm, neural network, cluster analysis and modeling and simulation for the LOS analysis of urban streets both quantitatively and qualitatively. Quality of service of urban streets is analyzed using the satisfaction level that the road user perceived while using the urban road infrastructure. Possibilities are shown regarding the further improvement in research methodology.
展开▼
