Integrated Corridor Management Systems Impacts of Data Quality on - - PowerPoint PPT Presentation
Integrated Corridor Management Systems Impacts of Data Quality on Decision-Making Dr. Francois Dion Dr. Qijian Gan University of California - Berkeley 04/25/2019 Outline 2 Definition of ICM Systems Example: I-210 Pilot ICM System
Definition of ICM Systems Example: I-210 Pilot ICM System Data Needs and Issues
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Systems attempting to bring together the operation of:
Freeways Arterials Transit systems Emergency vehicles Parking systems
Greatly focus on the use of technology and information
Monitor the operation of various systems Provide value-added information to system operators Provide relevant information to travelers
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Typical project goals
Improve operational situational awareness Promote collaboration among corridor stakeholders Improve incident response Improve travel reliability Improve overall corridor mobility Empower travelers to make informed travel decisions Facilitate multi-modal movements across the region Improve corridor safety
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Freeway/arterials projected to be under ICM management
EB Detours WB Detours
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California Highway Patrol Local Law Enforcement Information Providers
Traveler Information Apps Radio Weather CAD System Local Dispatch Systems
LA SAFE
DSS
Pasadena TMC Arcadia TMC County TMC Caltrans TMC LA Metro Foothill Transit Pasadena Transit Other Data Suppliers
Traffic Signals - SCATS
Monrovia Duarte
Traffic Signals - Transparity Travel Time Devices Traffic Signals - KITS Travel Time Devices Electronic Wayfinding Signs Traffic Signals - KITS Lane Closure System ATMS Traffic Signals - TSMSS CAD/AVL System Rail CAD/AVL System Bus CAD/AVL System CAD/AVL System Freeway Detectors Ramp & Connector Meters Freeway CMSs PeMS Probe Vehicle Data Crowd Sourcing Park & Ride Management System
Parking Operators
Parking Management Systems (future) Freeway Service Patrol 511 System Call Boxes
DSS ICM
Travel Time Devices Traffic Signals - KITS Travel Time Devices Arterial CMSs Electronic Wayfinding Signs Traffic Signals - TransSuite Travel Time Devices Electronic Wayfinding Signs Electronic Wayfinding Signs Electronic Wayfinding Signs
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Current traffic conditions
Freeway segments ◼ Mainline lanes ◼ On-ramps / Off-ramps ◼ HOV lanes Arterial segments ◼ Midblock counts ◼ Turning counts at intersections ◼ Detector counts at intersections
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How can we quickly obtain reliable incident
Incident/event characteristics (location, lane(s)
How can we identify unusual traffic
How to quantify deviation from normal
How can we track driver responses to
Percent traffic exiting freeway Alternate route followed
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Reliance on loop or point detectors only provide
Must extrapolate what happen between detection stations Poor detector health at certain key locations Require additional work to either fix problematic detectors
Consistency of counts across successive detectors Traffic counts at individual detectors do not always match
upstream counts
Count accuracy in congested areas Detectors may have difficulty counting vehicles in dense
traffic
Counts reflect capacity, not necessarily the traffic demand 13
Inadequate coverage of entry/exit movements at
Need to be able to track vehicle movements with
Wrong setup configuration between HOV and
Require advance techniques to identify such
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Counts on arterials are inherently very variable Effect of actuated/adaptive signals Vehicle entering/exiting between main intersections Ease of changing path to go around incidents or congested
areas
Non-ideal placement for accurate counts Location of approach detectors may allow vehicles to go
by without being detected
Incomplete detector coverage for traffic estimation Some intersection approaches are only covered by either
stop line or advance detectors
Count accuracy in congested areas Counts from stop line detectors are normally
underestimated when traffic is congested
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How to measure turning counts from shared lanes? Possible, but typically requires more expensive detection
system
How can we track vehicle movements? Require data at a finer granularity, either event-based
data or probe data
Capacity reduction caused by shared lane
Throughputs at certain lanes are much lower than the
normal saturation flow rates in such a case
How to model traffic demand?
Representative day? Representative weekday and weekend day? Set of representative days: Mon, Tue, Wed, etc.? Set of representative days for each month? How about holidays?
How to capture impacts of incidents occurring outside control area?
Outside incidents can affect traffic demand
How to determine actual demand in presence of congestion?
Sensors measure roadway capacity, not actual traffic demand
How can we determine routes followed by vehicles?
Probe data is promising, but current market penetration rates
very low
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Due to processing needs, data used in decision support systems are generally a few minutes old
Result in systems generally responding what has been
Effect of navigational apps
Navigational apps may push vehicles to take different route
than plan by traffic managers
Length of decision interval
Do we update control decisions every 5 min, 10 min, 15 min?
Forecasting future traffic is possible, but may be affected by various elements
Quality of the underlying data Size/complexity of network Normal fluctuations in traffic demand/patterns Incidents
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Consistency of data formats Various systems use different data formats, not
always fully compatible
Which format/standard to use? 19
Current technology does not provide perfect data Control decisions must account for
Potential data inaccuracies Data collection lag Drivers not behaving as desired Apps providing contradictory directions
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