Programs & Labs
Subhead H2
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Winter 2005
Improving evacuation traffic operations with adaptive control strategies
Henry Liu
In addition to good planning, an effective evacuation requires effective traffic control to respond to changing conditions and ensure that evacuees follow designated routes. Assistant professor Henry Liu of the civil engineering department hopes to improve traffic flow during emergencies by giving evacuation managers better decision-making tools.
Liu argues that evacuation efforts often run into problems despite elaborate scenario-based planning efforts carried out in advance, because planning can’t predict all possible scenarios. Instead of scenario planning, Liu’s work focuses on real-time traffic management, or, as he put it, “how can we respond to this specific disaster, now.”
By their very nature as extreme events, emergency evacuations resist traditional network evaluation methods, because standard assumptions about network use patterns do not apply. Traffic during evacuations is dominated by movement to “safe zones” and fraught with unpredictable behavior by frustrated and panicked motorists. However, emergency situations do provide the authority for strict centralized control of the traffic system, using signals and traffic control officers on the ground to direct vehicles as needed.
These characteristics led Liu to develop an adaptive control approach to evacuation traffic management. Adaptive traffic control systems, which use current traffic data to change their control behavior in response to changing conditions, offer the ability to compensate for disruptions by rerouting traffic along optimal routes. A reference model of the road network and a traffic simulation engine calculate the overall system objective using current data.
Liu has created a stripped-down simulated version of this system (without origin-destination estimation and resource allocation modules) on a simplified road network containing only a few nodes and links. For each node (intersection) in the network, the system calculates the optimal turning percentage to achieve a desired performance measure, such as lowest total travel time or minimum number of “victim vehicles” (vehicles unable to clear the network before a deadline). The system uses a “rolling horizon” approach to estimate traffic flow characteristics every two minutes and update its control strategy accordingly.
Liu, who joined the Department of Civil Engineering as an assistant professor in August of 2005, began working with adaptive traffic control systems before coming to Minnesota; he said he intends to continue his work here at the University of Minnesota.