AASHTO SCOTE Annual Meeting 2011 Dr. Nick Compin Caltrans Office of Systems Management Planning Performance Measurement and Traffic Data Branch Ph: (916)

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AASHTO SCOTE Annual Meeting 2011 Dr. Nick Compin Caltrans Office of Systems Management Planning Performance Measurement and Traffic Data Branch Ph: (916)

 Caltrans has deployed over 30,0000 automated detection systems on almost all of its urban freeway system, meaning that vehicle count and speed information is available in these areas.

Real-time Archive Data Management System PeMS collects detailed, raw, data in real-time – Fixed location sensors Processes these values in real- time, performing: – Diagnostics – Imputation for missing values – Speed calculations (if needed) – Aggregations over space and time – Many analysis functions Numbers of reports and tools to plot, chart, tabulate, etc.

How do we get here?How do we get here? The PeMS is Here!The PeMS is Here!

 The objective of the Tools for Operational Planning (TOPL) Project is to provide quick quantitative assessment of the congestion relief strategies for freeways and urban arterials.  These strategies include: demand management - focuses on reducing "excess demand"; incident management - targets resources to alleviate accident hot spots; traveler information - seeks to reduce traveler buffer time; and traffic control - implements aggressive ramp metering at locations where maximum reductions in congestion are likely to occur.

 Complete model of arterial management, including signal coordination (offset, cycle time, phase-split),  Complete model of coordinated ramp control that takes into account the limits on ramp capacity by sharing ‘space’ among a series of adjacent ramps,  Coordination of arterial signals and ramp metering,  Incorporation of ‘emissions’ and ‘travel time reliability’ as performance metrics

Our Goal Now is to Create a real-time Operator Decision Support System with the following components.  A short-term traffic simulation model that receives real-time field data and predicts behavior two hours into the future under a variety of recurrent uncertainty (chiefly demand and capacity variation) and non-recurrent uncertainty (chiefly incidents, events, lane closures)  A set of scenarios of recurrent and non-recurrent events that stress the system  A set of pre-emptive and retroactive tactical countermeasures that an operator may take to reduce the stress on the system that the scenario simulation uncovers