Traffic Solutions
How to Test FCD Monitoring Solutions: Performance of Cellular-Based Vs. GPS-based systems
About CellintIsrael Based, office in the USMain products– NetEyes™ for quality of RF networks– TrafficSense™ for traffic monitoring
(cellular-based innovative solution)State wide and metro wide deployments in the Israel, US and Europe (thousands of miles deployed)Granted patents in the US and Europe, pending patents in the rest of the worldCompany owners include Dr. Andrew Viterbi, Co-founder of Qualcomm and the inventor of the Viterbi code (i.e. CDMA/UMTS)
Customers/Partners
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Data from a broken traffic monitoring system, which only reports free flow, will look as follows:
Best Traffic Monitoring SystemVs. the Worst Traffic Monitoring System
Typical chart of speed over road segment with rush hour slowdown, by a good detection system will look as follows:
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Conclusions:1. Average daily speed error should not be considered a
parameter for evaluating traffic monitoring systems2. FCD test drives is not a sufficient way to evaluate system
performance
Observations:1. The average daily error rate can be less than 5% for:•A system that doesn’t detect slowdowns at all•A system detecting slowdowns with 50 minutes delay!2. Sporadic FCD test drives:•Will generate very little statistics for congested times•Can’t tell you how fast your system detected the slowdown
Conclusion: Bad systems Can “Hide”Behind Statistics
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Observations 2:Data VERY reliable, excellent slowdowns detection, no false alarms!
Same Data: Different Perception of Good and Bad
Observations 1:Data Ok on average, but not always reliable
Conclusion: wrong statistics can “kill”good systems
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Testing Performance of FCD systemsWhat do we test?
– We don’t need a system to detect free flow, so focus should be on slowdown detection
Slowdown Detection Latency:– Can only be tested by road sensors, since floating drive test can
only randomly detect a slowdown when it starts– Less than 8 minutes average latency can be provided on highways
and major arterials
Travel Time Measurements During Speed Fluctuations– Must be conducted over short segments, otherwise traffic
conditions can change significantly during a single measurement– Must have statistical significance, since travel times may vary
between two cars by 300% for the same traffic conditions (same road segment/ same time)
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History
Non intrusive FCD solutions seem to be the ultimate solution for future traffic data collection Until 2 years ago, all independent evaluations demonstrated relatively poor results:– US– Netherlands– Italy– Spain
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The reasons for problematic performanceGPS Fleet Tracking– Only few samples per day per road section, even for
most congested urban highways– Long time between location samples– Fleets tend to avoid congestions, if possible, so detection
doesn’t provide proper sampling– As a results – GPS aggregators provide predictive data
based on historical patterns, not real time traffic information
Cellular-based solutions– If location is based on theoretical triangulation – it’s not
accurate due to multi-path (blocking/reflecting elements)
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The ChangeDuring the last 2 years the breakthrough, we were all waiting for, occurred:
– 5 independent evaluations, by different DOTs, show success of Cellint’s TrafficSense system, which provides:
Similar performance to road sensors in detecting slowdowns Best possible travel time measurementSimilar performance to road sensors in measuring local speed
In the following slides, we will review some of these test methods and the performance that can be generated from c cellular based systems
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Atlanta Project Independent Evaluation TrafficSense provides area-wide coverage for construction zone management:
– Most sensors over GA400, one of the busiest corridors in Atlanta, were disconnected due to construction
– TrafficSense provides data, since last year, over the highway and adjustment arterials
Performance evaluation conducted by Georgia Department of TransportationMajor findings:
– TrafficSense speed over short segments (250 meters) matched the sensors’ speed very well in all speed ranges
– TrafficSense travel time was highly accurate, even during the most congested times
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Atlanta: TrafficSense Data is Incorporated for GA400 on Georgia DOT Official Website
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Atlanta Project – Independent Evaluation
Speed Range (mph) Mean Difference %
20-30 3.82%
30-40 7.13%
40-50 6.65%
50-60 2.63%
60-70 -8.88%
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KC Project – Independent Evaluation System was deployed over entire corridor in less than 2 monthsTrafficSense data was compared to inductive loops data of SCOUT (KC traffic management center)Independent evaluation by Kansas Department of Transportation shows:
– 5.9 minutes average delay in detecting slowdowns– Less than 5 mph speed difference in all ranges
Quoting the pilot report:– “TrafficSense data clearly reflects traffic conditions very
well”– “The Cellint system successfully proved the viability of
the technology for traffic applications”
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KC Project Evaluation Method [1]
Magenta: Sensor 69 – I-435 WB at US-69Blue: TrafficSense
TrafficSense speed comparison with road sensors
Speed changes are detected immediately(similar to sensors)
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Magenta: Sensor 69 – I-435 WB at US-69Blue: TrafficSense
Average speed difference over 5 days - 2.76 mphIf no slowdowns were detected – it would be 4.5 mph
TrafficSense speed comparisons with road sensors
KC Project Evaluation Method [2]
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TrafficSense had significantly fewer false slowdown detections than the Kansas City sensors
Magenta: Sensor 136 – I-435 EB at Wornall RoadBlue: TrafficSense
TrafficSense speed comparisons with road sensors
KC Project Evaluation Method [3]
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Kansas City: Deployment Following a Successful Pilot
0-30 MPH: RED 30-45 MPH: YELLOW 45+ MPH: GREEN
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Tel-Aviv: Independent Evaluation of an Israeli DOT Agency
Two competing cellular-based solutions failed this test
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Tel-Aviv Independent Evaluation [2]
0:00
1:12
2:24
3:36
4:48
6:00
7:12
8:24
9:36
Test Drive
Road Sensors
Traff icSense
Conclusions: •Sensors are less accurate during speed fluctuations•TrafficSense travel-time average difference: 9.3%
TrafficSense Travel-time Comparisons With Road Sensors and Test Drives (Drives conducted by the Israeli DOT)Minutes
14:40 pm 15:08 pm 15:54 pm
Project in Sweden
Deployment over Southern of Sweden for the Swedish Road AdministrationCellint’s TrafficSense system was selected following a competitive tender for Mobile Phone Traffic Monitoring systemMetro wide deployment in the Skåne Regioncovers freeways and trunk road, including city streets in Malmö and LundSuccessful evaluation of TrafficSense’s traffic data has lad to project expansion last month
Project in Sweden
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Israeli National Road Company: Project Evaluation Tested 3 cellular-based systems over Highway 1 and Arterial 44Validated data from the independent evaluation demonstrated 1 minute latency for TrafficSense in detecting slowdowns as compared to road sensors, at the location of the sensorsTrafficSense proved to be better than other solutions
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Israeli National Road Company: Project Evaluation Interface
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TrafficSense Slowdown Detection:A Delay of Only a Few Minutes
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Tel-Aviv Atlanta Kansas City SpringfieldMO
Operator'sSubscriberPenetration (%)
DetectionLatency OverMajor HWs(minutes)
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All cellular-based technologies except TrafficSense use cell sites’ location to calculate vehicles’ locationThis theoretical calculations (either based on some type of triangulation or on cell sector statistics) has a lot of inherent in-accuraciesTrafficSense doesn’t require the location of the cell sites at all, but rather uses ground-truth reference data as a location reference.
This enables TrafficSense to achieve orders of magnitude better location accuracy and slowdown detection latency also in highly dense urban areas
TrafficSense Unique Advantage
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Limitations of All FCD Monitoring Systems
Not enough data for accurate detection during late night hours
– But less than 1% of congestion events occur at nightNo accurate volume counting
– Accurate volumes are not critical for traffic control if you have local speeds, slowdown detection and travel times
– One can get good statistical estimates over time for road planning from the cellular system
Can’t differentiate between lanes– But once a lane is separated by terrain it can be
differentiated due to a different cellular signature (only TrafficSense)
– HOV lanes can be accommodated by using supporting systems
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Limitations of GPS Based SolutionsOnly few samples per day per road section, even for most congested urban highways:
– Due to communication cost (sending data to central location) andprivacy issues
Long time between location samples– Since by definition fleet tracking doesn’t require location data every
few minutesFleets tend to avoid congestions, if possible, so they don’t provide proper sampling when highly needed
– And taxi drivers tend to drive “differently” than normal traffic (usually more aggressive..)
As a results – GPS aggregators provide predictive data based on historical patterns, not real time traffic information
– Providing estimated information only for recurring rush hour slowdowns
Even if non-recurring slowdown is sampled, it might be detected hours after it started
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www.cellint.com
Cellint Traffic Solutions www.cellint.com [email protected] – 973-867-5595 Israel +972-524-77-33-77
TrafficSenseMost Cost Effective Solution for Road ManagementThe Only Validated FCD Solution for Accurate, Real
Time Traffic Information
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Q&A: Smart Use of Cellular-Based Monitoring Systems
Would you pay orders of magnitude more on traditional systems for a metro-wide deployment just due to the night time detection limitation of cellular-based systems?
– Probably notDo you really need volume counting every half mile for real time road management purposes?
– Probably not. However a measurement at least in one point between each two junctions is useful for road planning
How can I ensure proper performance and not get 50-minutes detection delays for slowdowns on major highways?
– Talk to colleagues from other States’ DOTs who conducted independent objective studies and who checked slowdown detection latency, not only average daily speeds
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TrafficSense System HighlightsSignificantly Lower Cost Than Traditional Systems, Providing:– Fast slowdown detection – like road sensors– Most accurate travel time
Plug and Play System– Modular system, super short deployment time– Flexible to road changes and constructions
Virtual Sensors in Small Intervals (every 250 meters in urban area) provide Both :
– Travel time updated to the minute– Very accurate and immediate incident alerts– Local traffic speed measurement similar to road traffic sensors