, Associate Professor, UMD-Mechanical & Industrial Eng
The growing number of traffic safety strategies, including intelligent transportation systems (ITS) and low-cost proactive safety improvements (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 identifies and eliminates 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 a geographic information system (GIS) interface was developed to proactively optimize 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 overall traffic safety by implementing the most effective safety strategies within budget to decrease the total number of crashes to the maximum degree. The GIS interface of the decision support system enables 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 was 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 refined.
- Project number: 2011015
- Start date: 07/2010
- Project status: Completed
- Research area: Transportation Safety and Traffic Flow