Traffic volumes on Indiana's roadways have increased significantly in the past years. During the period between 1989 and 1993, traffic volumes increased 20.2% on Indiana's urban interstate freeways and expressways, and 13.1% on rural interstates. The increasing traffic volumes have caused congestion and therefore additional costs to highway users. Basically, there are two options to alleviate traffic congestion. The first option is to add new highway lanes and the second one is to use the existing roadways more efficiently. Construction of new highways has been much limited by the budget and other restrictions. Therefore, efficient operation of the existing roadways is often the only practical solution to traffic delay and congestion problems. The objective of this study was to analyze Indiana freeway characteristics, find freeway capacities and to develop methods or models for realtime prediction of freeway traffic flow characteristics. In this report, the traffic characteristics of Indiana freeways are analyzed and discussed. Traffic measures are summarized in terms of average hourly traffic (AHT), average daily traffic (ADT), and average vehicle speed. Also presented are other traffic characteristics such as proportions of heavy vehicles, land distributions, daily variations, and capacity values. A dynamic traffic prediction model was developed using the Kalman Predictor method in combination with the time series theory. With the prediction model, the traffic flow on a given freeway in the next time interval can be predicted using real time traffic data of the current and past one or several time intervals.
Indiana Freeway Traffic Characteristics and Dynamic Prediction of Freeway Traffic Flows
1999
156 pages
Report
Keine Angabe
Englisch
Road Transportation , Highway Engineering , Transportation , Transportation & Traffic Planning , Transportation planning , Traffic delays , Construction sites , Traffic capacity , Indiana , Traffic congestion , Freeways , Costs , Traffic flow , Highway maintenance , Lane closures , Driver attitudes , Data collection , Travel time , Detours , Tables(Data) , Traffic volumes , Urban areas , Work zones
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