using cell phone technology to collect travel data d. kyle ward may 11, 2011
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Using Cell Phone Technology to Collect Travel Data D. Kyle Ward May 11, 2011. Outline. Intro to Tech and Pilot Program Application to MPO Business Model Congestion Management Process Travel Demand Modeling Pilot Results Future of the Technology Origin-Destination Estimation - PowerPoint PPT PresentationTRANSCRIPT
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Using Cell Phone Technology to Collect Travel Data
D. Kyle WardMay 11, 2011
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• Intro to Tech and Pilot Program
• Application to MPO Business Model– Congestion Management Process– Travel Demand Modeling
• Pilot Results
• Future of the Technology– Origin-Destination Estimation– Viability vs. Competing Technology
Outline
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• Uses cell-tower triangulation to locate cellular devices– Similar to GPS, but less accurate– Ubiquitous cell phone use compared to GPS
• Numerous metrics can be estimated– Speeds– Demographics
Intro to Tech
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• Contracted with AirSage– 834 centerline miles of coverage– Significant arterial coverage– 24/7 for March, 2010– Data scrubbed of personal information– Fraction the cost of traditional methods
Speed Pilot
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• Congestion Management Process– Yearly data collection program– Before and After Metrics– Congestion Monitoring– Project Identification– Project Programming
Application to MPO
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Application to MPO
• Travel Demand Modeling– Validation of Speeds and Travel Time– Volume-Delay Functions
• Accurate Free-Flow Speeds• Speed data matched to counts
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Pilot Results
5:30 pm
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Pilot Results
4:15 pm
• First signs of slowing– I-40 at Wade Avenue– US 70 between Lynn
and Millbrook
1/6
4:30 pm
• Bottleneck at Wade
2/6
4:45 pm
• Queue backs up along I-40
3/6
5:00 pm
• I-440 begins to slow
• I-40 congestion worsens
4/6
5:15 pm
• US 70 bottlenecks
5/6
5:30 pm
• Delay peaks on all routes
6/6
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Pilot Results
• Speed profiles– Peak vs All Day Congestion– Weekend Congestion
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• Concerns– Validation of Results?
• Purchase from different vendor/tech
– Default speed data capped at speed limit• Poor posted speed data impacts results• Uncapped speeds prone to outliers
– Solution: establish reference speeds
Pilot Results
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• Modeling of Non-Recurring Congestion– 5-minute interval data reporting
• Origin-Destination Estimation– Currently being piloted by the MPO/Airsage– Requires enormous amount of observations
• Currently not possible with GPS
– Estimation of all trips, regardless of purpose
Future Applications
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Competing Tech
• Infrastructure-based monitoring– Example: Bluetooth
• Expensive• Limited Coverage
• GPS– More accurate– Less samples (but growing)
• GPS-enabled devices doubling every year?