Looking into Detection, Model Results and Message Quality
Looking into Detection, Model Results and Message Quality
Looking into Detection, Model Results and Message Quality
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<strong>Looking</strong> <strong>into</strong> detection, modelresults <strong>and</strong> message qualityTomas Epp, PTV Austria GmbHAndreas Schmid, PTV AG
Forecast in a service meansTake <strong>into</strong> accountthe situation whichwill be presentonce you will getto a place.This is different fromthe current situation!Mid Term orDay forecastShort TermforecastCurrentsituation10/22/2010 3
Forecast in a service requires fusionASDA/FOTO currentsituationof various informationover time <strong>and</strong> space(there is rarely one goodsource for all).Redundant informationcan cover leaks.<strong>Quality</strong> assuranceon the final resultnot reasonableShort Term forecastsMedium Term forecastsLong Term forecastDigital map10/22/2010 4
Insight - current traffic stateby ASDA/FOTOSpatial interpolation:simple, but wrongbetter: model basedDetect dangerous jam endseven where no detector is!timeASDA = Automatische StaudynamikanalyseFOTO = Forecasting of Traffic ObjectsBoris S. Kerner, 2004. The Physics of Traffic5
ANS – ASDA/FOTO Native SciagramTime‐spacex‐rayimageRoad driving directionMQ, Det133,135MQ, Det123,456VLINKVLINKVLINKVLINKVLINKVLINK00:00 00:00 h12:00 12:00 h24:00 24:00 hVLINKtime6
ANS – ASDA/FOTO Native SciagramDetector measurementsconverted to coloursRoad driving directionMQ, Det133,135MQ, Det123,456VLINKVLINKVLINKVLINKVLINKVLINK24:00 24:00 hVLINKZeit7
ANS – ASDA/FOTO Native SciagramRoad in driving directionDetektor1,2,3Detektor4,5,6measurement locationDetektor7,8,9Detektor10,11,12Detektor13,1412 13 14 15 16 17 18 19MinuteintervalsKeyFaulty measurementsLOS freeLOS denseLOS JAMNo dataTime (minutes of the day)10/22/2010 8
ANS – ASDA/FOTO Native SciagramASDA/FOTO Objects: : JAM or SYNC flowRoad driving directionMQ, Det133,135MQ, Det123,456SYNCJAMVLINKVLINKVLINKVLINKVLINKVLINK00:00 00:00 h12:00 12:00 h24:00 24:00 hVLINKtime9
ANS – ASDA/FOTO Native SciagramLevel of Service (LOS) on a link>= 1 jamObjekt?>=1 Sync-Objekt?Road driving directionMQ, Det133,135MQ, Det123,456SYNCJAMVLINKVLINKVLINKVLINKVLINKVLINK00:00 00:00 h12:00 12:00 h24:00 24:00 hVLINKtime10
ANS – ASDA/FOTO Native Sciagram<strong>Message</strong>sSource 1Source 2Source 3Source 4Road driving directionMQ, Det133,135MQ, Det123,456Deviation in time <strong>and</strong> spaceVLINKVLINKVLINKVLINKVLINKVLINK00:00 00:00 h12:00 12:00 h24:00 24:00 hVLINKZeit11
ANS – ASDA/FOTO Native Sciagram„Real world“ example (www.bayerninfo.de(system)12
Insight: Prognosis diagrams10/22/2010 13
Insight: travel time• How does it work• Examples of Vienna10/22/2010 14
How does it work• Using FCD information• About 3000 Taxis (Vienna)• Velocity is sent every 15 minutes10/22/2010 15
How does it work• Given on each link• Filtering ofExclusive Lanesfor Taxi Cabs <strong>and</strong>Buses• Coverage ca. 85%10/22/2010 16
How does it work• Comparison of travel times– Setting the test track– Calculate travel time based on forecast results– Calculate travel time based on Taxi Cabs information• Calculate the deviation–difference = 1 −forecastTaxi10/22/2010 17
Examples of Vienna• 11x2 main routesthrough Vienna• Calcuated every 15minutes10/22/2010 18
Examples of Vienna• Example: week 20 (May 2010)10/22/2010 19
Examples of Vienna• Example: 20 May 201010/22/2010 20
Examples of Vienna• Example: three forecast steps10/22/2010 21
Metrics – automatic control• Images good for– Human interpretation(always richer than machines!)– Limited, dedicated (test) locations• Statistic figures needed– For large scale evaluations10/22/2010 22
Metrics – what figure to use?• <strong>Looking</strong> at Volumesexpected measured missed5000 veh/h 4800 veh/h ‐4% 200 veh100 veh/h 96 veh/h ‐4% 4 veh500 veh/h 300 veh/h ‐67% 200 veh10/22/2010 23
Metrics – a figure <strong>and</strong> its parameter<strong>Looking</strong> for a perceived quality index parameter nlist of values perceived as "same quality"count <strong>Model</strong> n <strong>Quality</strong> metrics:computedvalue−"truth"10 20 0,67 Q = ∆/T n <strong>Quality</strong>Index =20 36 0,67 ∆ = |model result - count result|("truth") n50 85 0,63 T = "Truth", e.g. count result or 0.7*count + 0.3*model100 160 0,61 n: parameter (to be determined)200 300 0,59500 700 0,54 Result: Median: Average1000 1300 0,52 n = 0,61 0,612000 2400 0,575000 5700 0,51 Values should be on a line (same "qualty parameter")10000 11000 reference20000 21600 0,68 Values outside [0,1] not logical50000 53000 0,6810/22/2010 24
Metrics – ExampleValue (e.g. flow)7.0006.0005.0004.0003.0002.0001.00010987654321<strong>Quality</strong> index"truth"comparison basecomputedvalues<strong>Quality</strong> =difference/ truth00 4 8 12 16 20 24time [h]010/22/2010 25
Metrics – Alternative• Geoffrey E. Havers1970’se.g. adopted in UK Highways Agency'sDesign Manual for Roads <strong>and</strong> Bridges(DMRB)M = <strong>Model</strong> ValueC = Count Value10/22/2010 26
Thank youfor your attention!Thomas.Epp@ptvaustria.atAndreas.Schmid@ptv.de