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.
Consolidation or closure of unnecessary grade crossings is a cost-effective but difficult-to-achieve option for increasing the safety of highway-rail grade crossings. Consolidation not only needs traffic engineering expertise, it also needs the support of local government officials and citizens. It is as much a public relations effort as an engineering exercise. To win local support, proposals for closing selected crossings should appear reasonable to the public, that is, the public should be able to see a need or net benefit. A corridor study is more effective than targeting single crossings for closure. Selecting a corridor with high-potential closure candidates can be the key to the success of winning local approval. Finding the most “hazardous” crossings can help select high-potential corridors. The development of a model to pinpoint Kansas’ best candidates for closure as a key step in selecting corridors where consolidation efforts should be concentrated is described.
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