abstract
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Our surface transportation infrastructure is a highly complex system subject to recurring and nonrecurring congestion, event stresses, natural disasters, accidents, sabotage, and possibly even nuisance attack. Under normal traffic conditions, the transportation network operations are optimized in such a way as to maximize certain system-wide or user-specific objective functions. However, when the system is subjected to extreme events or malicious attack, system optimization, balancing, and dynamics become much more complex. Under extreme conditions, not only will components within the system fail, but users of the system will react to those failures by changing their behavior which may further disrupt an already ailing system.
Several researchers have modeled traffic flow based on nominal operating conditions, but few are modeling the affects of extreme events and malicious acts on surface transportation systems. We propose to model this problem using multi-dimensional graph models with distinct dimensions for physical infrastructure, control communications, and vehicles (i.e., users). The configuration and parameters for a dependable and secure surface transportation system operating under extreme conditions and in malicious environments must be identified.
Dependability is defined as the systems ability to do what it is supposed to do in a timely fashion. Security is defined as the system’s characteristic to prevent incorrect operations.
Current state-of-the-practice in intelligent traffic control has not reached the point where real-time network-wide controls can be dynamically altered as a reaction to a special event or disruption. However, advances in detection and communication systems allow for continuous detection of vehicles and for real-time data exchange among vehicles, local traffic controllers, and the regional traffic management center. This provides an opportunity for optimal network-wide management of vehicle operations improving the safety and efficiency of the operations throughout the transportation network. It also provides an opportunity to establish automated contingency plans for rerouting traffic based on anomalous events and failures.
Modeling these complex dynamic interactions is challenging, however. This research proposal seeks funds to explore the use of graph-based dependability and security models for optimizing network-wide surface transportation communications and control networks. Twelve months of activity are planned under this project, consisting of (a) identifying or creating graph-based hierarchical models compatible with existing NIATT simulations tools (e.g., CORSIM, VISSIM) that permit us to manipulate the data using known simulation-based parameters and test the resulting transportation network via graph modeling. It is an interdisciplinary project involving three researchers from three departments with a requested budget of approximately $100,000.
The proposed research uniquely combines graph-based modeling techniques with N-dimensional modeling of surface transportation networks. It is basic research that must occur in order to understand and model the complex interactions in real-time control systems for surface transportation systems. Results will lead to increasingly dependable and secure control systems during normal and abnormal operational conditions.