Development of Traffic Simulation Laboratory for Design Planning and Traffic211 Operations (Phase 1)

摘要

The key element in improving traffic operations and performing effective real211u001etime management is the ability to assess the effectiveness of the various 211u001ealternatives prior to implementation. Simulation methods have long been 211u001erecognized as the most effective tool for such an analysis, and various 211u001esimulators have been developed by different agencies for freeway and arterial 211u001enetworks. While there have been individual tests of each software by various 211u001eagencies, no comprehensive effort has been made to quantify and evaluate the 211u001eperformance of each model. The major difficulty includes the lack of detailed 211u001ereal data and the time-consuming manual effort to prepare input information for 211u001eeach software. Recent installation of the state-of-the art video detection 211u001esystems in the I-394 freeway provides a unique opportunity to develop a 211u001ecomprehensive freeway database that can be used to create various test cases with 211u001edetailed traffic database that can be used to create various test cases with 211u001edetailed traffic information. Further, the I-494 Integrated Corridor Traffic 211u001eManagement project being conducted by MN/DOT will be able to provide valuable 211u001ecorridor traffic data which can be used for evaluating freeway/arterial network 211u001emodels. By evaluating existing traffic simulation models the 211u001eadvantages/disadvantages of each model can be identified. Based on the evaluation 211u001eresults a comprehensive modeling approach for freeway/arterial networks can be 211u001edeveloped. The ultimate goal of this research is to develop a traffic simulation 211u001elaboratory where various roadway design/operatonal alternatives can be evaluated 211u001ewith traffic simulators under an integrated database-simulation environment. The 211u001eproposed research, Phase I, will evaluate existing freeway simulation models with 211u001edetailed traffic data to be collected using machine-vision and loop detection 211u001esystems.