Advanced Transportation Management Laboratory
About the ATM Laboratory
Researchers in the ATM Laboratory at Boise State University, under the direction of Dr. Mandar Khanal, conduct research related to different aspects of the surface transportation system. The laboratory is equipped with fifteen workstations, an overhead projection system, a large-format colored printer for posters and drawings, and a fiber optics connection to Traffic Management Center located at the premises of the Ada County Highway District headquarters. The workstations in this lab are equipped with the latest software for traffic simulation, statistical analyses, geospatial analyses, reality modeling, and road design. Research conducted at this lab can be classified into the following classes.
Traffic Operations and Management
Research in this class involves finding ways to improve the operations of existing surface transportation infrastructure through improved management techniques including the use of operations data from newer technologies such as connected vehicles.
Planning for Balanced Growth
Decision makers need a proactive approach to anticipate the demand for transportation in their jurisdiction and prepare plans to meet those needs to the extent possible within funding and other limitations. Research conducted under this classification involves exploring ways to achieve these goals. Examples include the role of micromobility modes in urban transportation and smart growth of cities.
Use of Newer Technologies in Transportation Infrastructure Design
As the technology of data collection and design advances researchers will have to be looking continuously for ways to apply these advances to existing practice. Examples of newer technologies for data collection include mobile-terrestrial or aerial lidar and photogrammetric image capture using drones. Research in this class in focused on these topics.
Improving Safety
More than 38000 people die on US roads each year. Almost every jurisdiction in the US maintains a database of historical crashes. Such databases are useful and help road managers to direct their limited resources to addressing problem areas in their infrastructure network. Such an approach is reactive and not proactive. It is important for researchers to explore ways to be more proactive and find ways to predict the likelihood of crashes before they occur.