A brief historical perspective on the development of the rate-quality control method and its use in the identification of hazardous roadway locations is presented. The evolution of the formulas used in the ratequality control method from their origin in the late 1950s to their present form is traced. The derivation of the basic formulas used in the method is also presented and discussed. It is suggested that, contrary to assertions in the literature, the accuracy of the equations used in the ratequality method is not improved by eliminating the normal approximation correction factor from the original equations. The need for the correction factor is particularly apparent at higher probability levels. Charts are provided for determining an appropriate correction factor for those who may wish to incorporate these factors into the equations.
Recent federal legislation allowing states to set their own speed limits on highways, as well as increases in the number of requests from citizens and neighborhood groups to implement actions to reduce “excessive” speeding on their streets and highways, has created considerable debate about and scrutiny of the appropriate speed limits that should be posted on state highways. Various speed studies have indicated that sensible and cautious drivers will most likely drive at the speed dictated by roadway and traffic conditions rather than relying on a posted speed limit. To incorporate roadway characteristics and traffic volumes into the selection of the most appropriate (i.e., comfortable, safe, and efficient) speed limit, actual engineering field speed studies are carried out. Generally, the 85th percentile speed at which the drivers surveyed are driving is selected as a primary factor in determining the posted speed limit. Carrying out such field studies for all highway sections is a costly and time-consuming process. Therefore, characterizing the relationship between the 85th percentile speed and the roadway characteristics will assist in selecting the most appropriate posted speed limit on highway sections where field surveying is difficult due to resource limitations. A back-propagation neural network is used to extract the relationship between roadway characteristics and 85th percentile speed. The developed neural-network-based speed model was found to perform satisfactorily for characterization of speed on Kansas two-lane, uninterrupted-flow rural highways and for quantifying the influence of prevailing roadway characteristics on the anticipated 85th percentile speed.
Traditionally, highway improvement project evaluation is done without incorporating highway users’ views. The Kansas Department of Transportation (KDOT) wants drivers to be satisfied and have “good feelings” about its passing lanes program. KDOT needs input to decide whether passing lanes are efficient, safe, and acceptable to the public. Drivers’ views were solicited via a questionnaire survey which was part of a comprehensive study on passing lanes in Kansas. Generally, drivers support the passing lane program and suggest construction of more passing lanes. Drivers think that passing lanes are more beneficial for improving safety than for saving time. They are equally divided on the length of passing lanes between “too short” and “just right,” although the provided lengths are within the recommended optimum lengths found in the literature. The “too short” responses could be due to existing passing lane spacings, preference of four-lane highways over two-lane highways, and difference in local conditions from those used to determine lengths. Drivers cited fellow drivers’ failure to follow signs and markings properly, and failure to use the lanes properly; this seems to indicate that improvements in signing and pavement markings should be considered. A smaller proportion of drivers, satisfied with a lower frequency of local travel on a route closer to the state’s borders (i.e., more unfamiliar drivers), suggests the importance of standardizing highway operating and design practices throughout the country.
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