APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT



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APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT Toshhko Oda (1), Kochro Iwaoka (2) (1), (2) Infrastructure Systems Busness Unt, Panasonc System Networks Co., Ltd. Saedo-cho 600, Tuzuk-ku, Yokohama 224-8539, Japan (1) +81-45-938-1541, oda.toshhko@jp.panasonc.com (2) +81-45-938-1551, waoka.kochro@ jp.panasonc.com Satosh Nkura Traffc Regulaton Secton, Kanagawa Prefectural Polce Headquarters 2-4 Kagan-dor, Naka-ku, Yokohama 231-8403, Japan +81-45-211-1212 ext.5170 Kunhro Kamata Unversal Traffc Management Socety of Japan 2-6 Ichgaya-tamach, Shnjuku-ku, Tokyo 162-0843, Japan +81-3-3235-6520, kamata@utms.or.jp ABSTRACT Ths paper descrbes a study of usng probe data for traffc management. We equpped nearly one hundred taxes travelng around the center of Yokohama Cty wth onboard unts. The onboard unts communcate va nfrared beacons on the roadsde to allow the collecton of the probe data transmtted from the equpped vehcles. The results suggest that the probe data of only one hundred taxes can be successfully appled to traffc management f probe data are accumulated for suffcently long perods of tme and are used n combnaton wth vehcle detector data. INTRODUCTION In Japan nfrared beacons have been wdely and rapdly nstalled snce early 1990s wth the advancements of Intellgent Transport Systems (ITS), wth approxmately 51,000 unts on arteral roads. Through the two-way communcaton between nfrared beacons and vehcles equpped wth onboard unts, the passng vehcles can be detected and data can be transmtted. Traffc Control Center collects nformaton such as vehcle dentfcaton number and travel tme va the beacons for traffc management purposes. Unversal Traffc Management Socety of Japan (UTMS Japan) has been actvely workng on varous research by utlzng such specal capabltes of the beacons.

The core functons of an urban traffc control system are sgnal control and nformaton provson. To fulfll these functons, t s necessary to collect nformaton of road traffc condtons. In the exstng system, traffc flow has been observed manly by vehcle detectors nstalled on arteral roads. The detectors enable the measurements of traffc volume and tme occupancy, then to generate traffc attrbutes ncludng congeston length, travel tme and others. It should be noted, however, that such nformaton s only avalable from arteral roads nstalled wth the detectors. On the contrary, there have been nnovatve and new approaches for traffc data collecton recently. The new approach s based on the use of probe vehcles to collect travel data wth the recent development of onboard unts wth a new capablty to store large capacty of travel records. The advantage of probe data s that t enables traffc admnstrators to observe road traffc condtons of ordnary roads ncludng local streets, where no addtonal vehcle detectors are requred to be nstalled. Due to ths advantage, there have been great expectatons for the developments and mplementaton of the new concept. Orgnally, UTMS Japan had worked on research to use moble phones as a communcaton meda to obtan probe data [1]. Later, UTMS Japan decded to utlze the nfrared beacons that have been deployed at many locatons, whch elmnates the hgh communcaton costs of moble phones [2]. Ths paper examnes the travel condtons of prove vehcles, and descrbes the feasblty of makng use of ths data for traffc management. EXPERIMENTS EXPERIMENTAL SYSTEM An expermental system has been constructed at Traffc Control Center of Kanagawa Prefectural Polce Headquarters [6]-[8]. Fgure 1 llustrates the overvew of the expermental system [9]. Traffc Control Center We equpped nearly one hundred taxes Probe travelng around the center of Yokohama Cty Data Base wth onboard unts. The feature of our Decompresson of approach s that the travel records ncludng the Probe Data lattude and longtude of each vehcle at every second or ffteen meters are compressed n the Compresson of Infrared Probe Data onboard unts and transmtted to Traffc Beacon Floatng Vehcle Control Center va nfrared beacons. The Onboard Unt Traffc Control Center receves and decompresses the compressed the data, from whch the travel trajectory and traffc condton of roads can be reconstructed [2]-[5]. Fgure 1 Overvew of expermental system.

TRAVEL STATUS OF PROBE VEHICLES The data used n these experments were collected for sx months from md June through md December 2007, and from early March to end of August 2008, respectvely. Subsequently data were analyzed. Frst, to grasp actual travel condtons of probe cars, we conducted a survey on ther operatng status durng the perod. Fgure 2 shows the fluctuaton of the number of travelng vehcles wth the change of tme of day. The average number of travelng vehcles was 71.5 throughout a day whle the number stayed around eghty vehcles from 11:00 to 2:00 mdnght. Fgure 3 descrbes the total travel dstance by month, ndcatng that the rato of the arteral roads was 83.3%, n other words, most vehcles traveled arteral roads. Fgure 4 and 5 llustrate the total dstance for each day and road type, respectvely. The daly travel dstance of a probe car turned out to be 90.0km on the average, wth the maxmum of 151.7km. Fgure 6 gves the fluctuaton of average speed for each road type. The average speed turned out to be 29.2km/h, 29.9km/h and 25.3km/h for all roads, arteral roads and the others, respectvely [9]. Fgure 2 Number of travelng probe vehcles. Fgure 3 Total travel dstance by month. Fgure 4 Total travel dstance for each day type. Fgure 5 Total travel dstance for each road type. Fgure 6 Average speed for each road type.

ANALYSIS OF TRAFFIC INDEXES TRAVEL TIME Travel tme s one of most mportant traffc nformaton. It s usually estmated based upon vehcle detector data, and appled to provson nformaton system called VICS (Vehcle Informaton and Communcaton Systems). To verfy the travel tme calculated by probe data, ths paper examned the dfference between travel tmes provded VICS and obtaned by probe data. Fgure 7 and 8 show the fluctuaton of the travel tmes on nbound and outbound drecton on Natonal Hghway Route 16, respectvely. Fgure 9 llustrates the travel tmes on nbound drecton on Kamakura-kado. The ratos of root mean squared errors n these Fgures are 15.7%, 14.2% and 17.2%, respectvely based on an assumpton that VICS travel tme s the ground truth. Fgure 10 gves the comparson of travel tmes on nbound Hrato-sakuragcho-sen, and the correlaton coeffcent s 0.80. These results do not necessarly secure suffcent accuracy. In future we would be overcome wth long-term data storage. Fgure 7 Comparson of travel tmes on nbound drecton on Natonal Hghway Route 16. Fgure 8 Comparson of travel tmes on outbound drecton on Natonal Hghway Route 16. Fgure 9 Comparson of travel tmes on nbound drecton on Kamakura-kado. Fgure 10 Correlaton between travel tmes on nbound drecton on Htato-sakugagcho-sen.

TOTAL DERAY TIMES Furthermore, usng probe and vehcle detector data, we computed total delay tme and examned a correlaton between the delay and tme occupancy obtaned from vehcle detectors. Total delay tme d at phase and approach j of an ntersecton s calculated usng traffc volume q measured va vehcle detectors and travel tme t obtaned from probe data. The calculaton follows the equaton (1) as wrtten below; d = q t t ) (1) ( 0 where 0 0 t = 0 denotes crtera travel tme at a regulaton speed and d = 0 f t < t. Fgure 11, 12 and 13 descrbe the fluctuaton of the total delay tme of the Bando-bash, Chojamach-gocho-me and Hatsune-cho Intersecton, respectvely. The total delay tme n these fgures were calculated usng the data collected n 2008. Table 1 gves the correlaton coeffcents of these ntersectons between the delay and tme occupancy. These results show the correlaton coeffcent of each ntersecton was relatvely hgh. Fgure 11 Total delay at Bando-bash Intersecton. Fgure 12 Total delay at Chojamach-gocho-me Intersecton. Fgure 13 Total delay at Hatsune-cho Intersecton. Table 1 Correlaton coeffcent between tme occupancy and total delay. Correlaton Intersecton Coeffcent 2007 2008 Bando-bash 0.77 0.70 Chojamach-gocho-me 0.76 0.77 Hatsune-cho 0.85 0.68

CALCUILATION OF SIGNAL CONTROL PARAMETRES USING PROBE DATA Usng the total delay tme, we also computed splt whch s a crtcal factor n sgnal controllng. The splt λ of phase denotes a perod tme allocated to each phase n a cycle tme, and s calculated based on the equaton (2): maxd j λ = (2) max d where λ = 1. j Fgure 14 and 15 show the splts of major and mnor roads at Bando-bash and Chojamach-gocho-me Intersecton, respectvely. These are calculated usng the data collected n 2008. Fgure 16 and 17 llustrate the comparson of operatonal and calculated splts of major road, respectvely. As shown n these Fgures, we succeeded to obtan values that are close to the actual operatonal values. We antcpate to conduct further studes based on collected data sets. Fgure 14 Splt calculated based on probe data at Bando-bash Intersecton. Fgure 15 Splt calculated based on probe data at Chojamach-gocho-me Intersecton. Fgure 16 Comparson of operatonal and calculated splts of major road at Bando-bash Intersecton. Fgure 17 Comparson of operatonal and calculated splts of major road at Chojamach-gocho-me Intersecton.

CONCLUSIONS In ths paper, we analyzed probe data collected va nfrared beacons to reveal the travel status of probe vehcles, and calculated several traffc ndexes and sgnal control parameters to explore the feasblty of usng probe data for traffc management purpose. Addtonally, we examned the valdty of the calculated data by comparng t wth exstng measured and operatonal data. The results suggest that the probe data of only one hundred taxes can be successfully appled to traffc management functons f probe data are accumulated for suffcently long perods of tme and are used n combnaton wth vehcle detector data. REFERENCES [1] S. Adach et at., A Study of Sensor Fuson Technology for Traffc Informaton Servces Employng Wde Range Communcaton Meda, Proc. of the 9th World Congress on ITS, CD-ROM (2002) [2] S. Adach et al., Compresson Method for Probe Data, Proc. of the 11th World Congress on ITS, CD-ROM (2004) [3] H. Nsh et al., Examnng of the Possblty of Collectng Probe Data Usng Infrared Beacon, Proc. of the 11th World Congress on ITS, CD-ROM (2004) [4] M. Mochzuk et al., Verfcaton of Traffc Informaton Generated From Probe Data, Proc. of the 11th World Congress on ITS, CD-ROM (2004) [5] S. Adach al., Research of Compresson Method of Probe Data -A Lossy Compresson Algorthm for Probe Data -, The Paper of Techncal Meetng on ITS, IEE Japan, ITS-05-10, pp.13-182005(n Japanese) [6] S. Adach et al., Research of Collecton of Probe Data Usng Infrared Beacons, Proc. of the 5th European ITS Congress, CD-ROM (2005) [7] N. Terazak et al., Demonstratve Experment of Probe Informaton Collectng Systems Usng Infrared Beacons, Proc. of the 12th World Congress on ITS, CD-ROM (2005) [8] T. Sato et al., Research of Collecton of Probe Data Usng Infrared Beacons, Proc. of the 13th World Congress on ITS, CD-ROM (2006) [9] T. Oda et al., A Study on Applcaton of Probe Data Collected va Infrared Beacons to Traffc Management, The Paper of Techncal Meetng on ITS, IEE Japan, ITS-09-17, pp.25-30 2009(n Japanese)