Towards Real-Time MinETA Routing

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Towards Real-Time MinETA Routing
Alain L. Kornhauser Professor, Operations
Research Financial Engineering

• Tuesday, December 6, 2005
• RPI, Troy, NY

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Finally Convergence of
Real-Time Decisions that substantially improve
the Bottom line of Carriers Shippers

• GPS

Optimal Real-Time Management Control of Mobile
Assets
Memory
Robust OS
Real-Time Mobile Information
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Company Fundamental

• PROBLEM How to get from A to B
• Many Paths, Each with a Different Value to the
  Decision Maker

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Including Real-Time Information Concepts
Peak Hour Characteristics Return to Normalcy
Burleigh - Zoo
Moorland - Downtown
During Peak Hours, Traffic Patterns Remain at a
relatively constant distance to Historical
Estimate There will be a time at which traffic
patterns will return to free flow conditions
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Including Real-Time Information Concepts
Exponential Smoothing

• Method of smoothing a time series of
  observations
• Most recent observations are given a high weight
  and previous observations are given lower weights
  that decrease exponentially with the age of the
  observation

Single
Double
Triple
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Including Real-Time Information Solution

• During Peak Periods
• Adaptation of Double Exponential Smoothing
• Trend is the Trend of the Historical Estimate
• Observation weighted with Most Recent Estimate
  Slope for Smoothed Estimate
• Forecast done by adding trend to most recent
  estimate

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Including Real-Time Information Solution

• During Non-Peak Periods
• Adaptation of Double Exponential Smoothing
• Trend is decay to free flow Conditions

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(a)
(b)
(c)
Figure Empirical testing of forecasting
algorithm. (a) Forecast from most recent
observation. (b) Weighting on most recent
observations. (c) Realization of travel time
data.
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Real-Time Congestion Dependent Sat/Nav
Conducted its version of the abandoned
Advance project

• 250 Volunteers using CoPilotLive commuting
  to/from RPI
• CoPilot continuously shares real-time
  probe-based traffic data
• CoPilot continuously seeks a minimum ETA route

Link
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Record Send Mi, Mj, Tj-Ti
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Cell Phones as Traffic ProbesA Way to Get
Started?
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Cell Probe Technology

• Part of general trend away from fixed sensors
  toward vehicle-based information
• Reflects frustration with high costs and slow
  pace of deployment for traditional sensors
• Characteristics
• Low cost
• full regional coverage
• performance-based, and
• self sufficient business model

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Cell Probe Technology

• Practical success requires more than cell phones
• Cell phone movement based on cell location and
  hand-offs from one cell to another
• Pattern recognition techniques filter out data
  from those not on the highway
• Then traffic algorithms generate travel times and
  speeds on roadway links
• Cell phones need to be turned on, but not
  necessarily in use
• Full regional systems in place in Baltimore,
  Antwerp, and Tel Aviv 4,600 miles

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Cell Probe Technology
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Cell Probe Privacy
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Handset 49, part 1
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Handset 49, part 2
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Handset 49, part 3
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Handset 49, part 4
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Handset 49, part 5
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Handset 49, part6
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Handset 49, full trip
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Handset 49, full trip
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Path-Finding Drive Tests
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Possible Applications

• Travel Times
• For message signs web sites
• Performance measures
• Include arterial network
• Top 10 routes
• TTI-type reports
• Operations planning
• Special events
• Work zone management
• Evaluation of actions
• Safety
• Focus on problem areas and assessments
• Port/intermodal access
• Local/regional web sites
• Statewide coverage

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Applications

• General Planning and Management
• Regional congestion management
• Archived data supports system analysis, average
  day information, long-range planning
• Integrated regional or corridor management
• Plan for extreme or special events
• Homeland security applications no-notice
  evacuations
• Rapid evaluation of alternatives
• Work zone management
• Rural planning and operations
• Traffic volume estimates -- future

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Applications (2)

• Performance Measurement
• System performance in near real time
• Reliability measures critical from users
  perspective (travel time index, planning time
  index, etc.)
• Performance-based systems information for
  operators, users, and the public
• Congestion management support for HOT lanes and
  other finance alternatives
• Economic value from partnerships with business
  the DOT a part of just in time delivery

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Applications (3)

• Travel Demand and Air Quality Modeling
• Today Validate travel demand and Mobile6 models
• Tomorrow origin/destination data
• Tomorrow New model development activity-based
  and beyond
• Safety
• Analysis and prediction
• Targeted deployment of safety personnel
• Communication
• Public participation real data on congestion
• Near real-time data web, PDA, 511
• Premium 511 service

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Applications (4)

• Freight Operations
• Web- or cell-based distribution of roadway
  information
• Individual dynamic routing recommendations based
  on congestion
• Travel time prediction to improve asset
  utilization
• Freight Analytics
• Strategic analysis of freight movement for
  congestion mitigation
• Origin/destination data to examine flows and set
  priorities
• Support for cost/benefit and alternatives analysis

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Safety Example

• Operational tool
• Assign patrol cars to road segments based on
• Average speed Z percent above speed limit
• Trigger points X percent of traffic more than Y
  percent above speed limit
• Identify trends and historical patterns
• Short-term forecasts
• Evaluation tool near real-time
• Assess what worked and how well
• Statistical analysis of patterns

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Safety Example
Speed Limit