Title: Towards Real-Time MinETA Routing
1Towards Real-Time MinETA Routing
Alain L. Kornhauser Professor, Operations
Research Financial Engineering
- Tuesday, December 6, 2005
- RPI, Troy, NY
2Finally Convergence of
Real-Time Decisions that substantially improve
the Bottom line of Carriers Shippers
Optimal Real-Time Management Control of Mobile
Assets
Memory
Robust OS
Real-Time Mobile Information
3Company Fundamental
- PROBLEM How to get from A to B
- Many Paths, Each with a Different Value to the
Decision Maker
4Including 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
5Including 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
6Including 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
7Including Real-Time Information Solution
- During Non-Peak Periods
- Adaptation of Double Exponential Smoothing
- Trend is decay to free flow Conditions
8(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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23Real-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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26Record Send Mi, Mj, Tj-Ti
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28Cell Phones as Traffic ProbesA Way to Get
Started?
29Cell 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
30Cell 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
31Cell Probe Technology
32Cell Probe Privacy
33Handset 49, part 1
34Handset 49, part 2
35Handset 49, part 3
36Handset 49, part 4
37Handset 49, part 5
38Handset 49, part6
39Handset 49, full trip
40Handset 49, full trip
41Path-Finding Drive Tests
42Possible 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
43Applications
- 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
44Applications (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
45Applications (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
46Applications (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
47Safety 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
48Safety Example
Speed Limit