CPS: TTP Option: Synergy: Collaborative Research: Dynamic Methods of Traffic Control that Impact Quality of Life in Smart Cities
Nikos Papanikolopoulos, Professor, Computer Science and Engineering
- John Hourdos, Director, MN Traffic Observatory, Civil, Environmental and Geo-Engineering
Traffic control management strategies have been largely focused on improving vehicular traffic flows on highways and freeways, but arterials have not been used properly and pedestrians are mostly ignored. This work introduces a novel hierarchical adaptive controls paradigm to urban network traffic control that adapts to changing movement and interaction behaviors from multiple entities (vehicles, public transport modes, bicyclists, and pedestrians). Such a paradigm leverages several key ideas of cyber-physical systems to rapidly and automatically pin-point and respond to urban arterial congestion thereby improving travel time and reliability for all modes. Safety also is improving since advanced warnings actuated by the cyber-physical system alert drivers to congested areas, thereby allowing them to avoid these areas or to adapt their driving habits. Such findings have a tangible effect on the well-being, productivity, and health of the traveling public.
The primary goal is to create a cyber-control network (CCN) that integrates seamlessly across heterogeneous sensory data to produce effective control schemes and actuation sequences. Accordingly, this project introduces a cyber-physical architecture that then integrates: (i) a sub-network of heterogeneous sensors, (ii) a decision control substrate, and (iii) a sub-actuation network that carries out the decisions of the control substrate (traffic control signals, changeable message signs). This is a major departure from more prevalent centralized supervisory control and data acquisition (SCADA), in that the CCN uses a hierarchical architecture to dynamically instantiate the sub-networks together to respond rapidly to changing cyber-physical interactions. Such an approach allows the cyber-physical system to adapt in real-time to salient traffic events occurring at different scales of time and space. The work consequently introduces a controlware module to realize such dynamic sub-network reconfiguration and provide decision signal outputs to the actuation network.
A secondary, complementary goal is to develop a heterogeneous sensor network to reliably and accurately monitor and identify salient arterial traffic events. Other impacts of the project include the integration of the activities with practitioners (e.g., traffic engineers), annual workshops/tutorials, and outreach to K-12 institutions.
- Start date: 09/2015
- Project Status: Active
- Research Area: Transportation Safety and Traffic Flow