Intelligent Transportation Systems Institute, Center for Transportation Studies
The growing number of traffic safety strategies, including the Intelligent Transportation Systems (ITS) and lowcost proactive safety improvement (LCPSI), call for an integrated approach to optimize resource allocation systematically and proactively. While most of the currently used standard methods such as the six-step method that identify and eliminate hazardous locations serve their purpose well, they represent a reactive approach that seeks
improvement after crashes happen. In this project, a decision support system with Geographic Information System (GIS) interface is developed to proactively optimize the resource allocation of traffic safety improvement strategies. With its optimization function, the decision support system is able to suggest a systematically optimized implementation plan together with the associated cost once the concerned areas and possible countermeasures are
selected. It proactively improves the overall traffic safety by implementing the most effective safety strategies that meet the budget to decrease the total number of crashes to the maximum degree. The GIS interface of the decision support system enables the users to select concerned areas directly from the map and calculates certain inputs
automatically from parameters related to the geometric design and traffic control features. An associated database
is also designed to support the system so that as more data are input into the system, the calibration factors and crash modification functions used to calculate the expected number of crashes will be continuously updated and
Department of Mechanical and Industrial Engineering,
Northland Advanced Transportation Systems Research Laboratories,
University of Minnesota Duluth
Chen, Hongyi; Chen, Fang; Anderson, Chris.
Developing an Intelligent Decision Support System for the Proactive Implementation of Traffic Safety Strategies.
Intelligent Transportation Systems Institute, Center for Transportation Studies.
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