Editor: Fei-Yue WangUniversity of Arizona andChinese Academy of Sciencefeiyue@sie.arizona.edu

IEEE Intelligent Transportation Systems Society (previ-ously the IEEE ITS Council). The conference featuredover 200 papers and hosted approximately 300 attendees,representing 35 countries. Furthermore, it exemplified theextraordinary progress ITS theory and applications havemade over the last decade toward improving transporta-tion systems’ safety, efficiency, and quality. Here, we reviewthe topics covered at ITSC 05, providing a broad overviewof the field’s current research programs and projects.

Intelligent systems methodsIntelligent systems methods are cost effective in dealing

with the functions, dynamics, and complexity of today’stransportation systems. At ITSC 05, quite a few interestingmethods emerged for theoretical analysis as well as foractual applications.

Petri netsPetri nets have become an attractive option for traffic

modeling and control. Four ITSC 05 papers addressed thistopic, covering

• a switching modeling system to represent and controlurban traffic,

• the formal design of public transport stations based onhybrid Petri nets,

• a human-computer interface modeled with Petri nets forreporting on disabled transportation, and

• traffic-signal priority and preemption control with col-ored Petri nets.

Figure 1 shows the Petri net model for an urban trafficarea consisting of two intersections and 12 roads.1 Petrinets have proved to be effective for both analytical model-ing and graphic representation for many other intelligentsystems, especially computer-integrated manufacturingsystems. However, their effectiveness in traffic applicationscan quickly recede in the face of tedious notations and com-plex analysis, as figure 1 shows. Future work must intro-duce modular design and hierarchical representation.

Computational intelligenceComputational intelligence can help predict traffic, oper-

ate and maintain traffic-control systems, and monitorhuman behaviors. A major issue discussed at ITSC 05 wasshort-term traffic prediction using fuzzy c-means and cellu-lar automata. Presenters also considered neural or neural-fuzzy approaches for tracking school field trips, identifyingthe state of traffic, and detecting when a driver is drowsy.Another major issue discussed was using genetic or evolu-tionary methods to locate automatic vehicle-identificationreaders and to enable automated highway systems to assignlanes. Such methods can also help traffic controllers createa dynamic origin-destination matrix for traffic demandsand distributions in a network, estimating in real time theratio of turning movements in different directions at inter-sections and solving the single-vehicle pickup and deliveryproblem with specified time windows.

Data mining and analysisThe conference included three sessions on data mining

and analysis for ITS. Major topics included

• identifying rear-end crash patterns on instrumentedfreeways,

The IEEE held its eighth annual International Con-

ference on Intelligent Transportation Systems last

September in Vienna, Austria. This was ITSC’s first time

in Europe and its first time as the annual conference of the

ITSC 05: Current Issues andResearch TrendsShuming Tang, Shandong Academy of SciencesFei-Yue Wang, University of Arizona Qinghai Miao, Chinese Academy of Sciences

96 1541-1672/06/$20.00 © 2006 IEEE IEEE INTELLIGENT SYSTEMSPublished by the IEEE Computer Society

I n t e l l i g e n t T r a n s p o r t a t i o n S y s t e m s

This issue summarizes the major ITS developments and projectspresented at the 2005 IEEE International Intelligent TransportationSystems Conference, held in Vienna, Austria. As the President ofIEEE ITSS, I invite you to attend our annual conference ITSC 2006,to be held September 17-20, 2006, in Toronto, Canada.

—Fei-Yui Wang

Editor‘s Introduction

• identifying and analyzing journeys usingdata collected from electronic fare systems,

• using cluster analysis to determine high-way flow patterns,

• forecasting traffic flow,• predicting travel destinations using fre-

quent crossing patterns from drivinghistory,

• identifying the fastest paths on urbannetworks using rule-based prediction,

• identifying time-of-day break points fortraffic signal timing plans using k-meansclustering, and

• collecting level-of-service informationfrom induction loops for variable-message-system displays.

Two groups reported on real-world datamining applications. The first group usedarchived induction-loop-detector data tostudy bottleneck activation for a 30-kmsection of the northbound Autobahn 5 nearFrankfurt, Germany.2 The researchersequipped the Frankfurt study site withinduction-loop detectors (D1 through D30in figure 2) in each lane and on most ramps.The detectors recorded separate counts andvelocities for autos and trucks at one-minuteintervals. Figure 2 shows speeds averagedacross all lanes for each interval, with timeas the x-axis, distance as the y-axis, andspeed variation in color. The group mappedin time and space the activation of 15 bot-tlenecks along Autobahn 5 on 19 Septem-ber 2001 (G1 through G15 in figure 2).With the increasing availability of reliablefreeway sensor data, it’s important to con-tinue the systematic empirical analysis offreeways to reveal the spatial and temporalaspects of dynamic freeway traffic-flowphenomena.

The second group, Robert Bertini,Spicer Matthews, Steven Hansen, AndyDelcambre, and Andy Rodriguez, reportedon the recent development of archived-datauser service in their paper, “ITS ArchivedData User Service in Portland, Oregon:Now and into the Future.” (This and otherITSC 05 papers referenced in this depart-ment appear in Proc. 8th IEEE Int’l Conf.Intelligent Transportation Systems, IEEEPress, 2005.) They discussed the hardwareand software used to build that system andthe basic functionality of the data archive.They also gave an update on future designplans and described several of the data ar-chive’s features, comparing them to othersystems being implemented elsewhere.

Agent technologySeveral papers discussed how to apply

agent technology to dynamic vehicle rout-ing and to route-guidance problems, aswell as to simulations of driver behavior. In“MADARP: Multi-Agent Architecture forPassenger Transportation Systems,” Clau-dio Cubillos, Franco Guidi-Polanco, andClaudio Demartini proposed a multiagentarchitecture for passenger transportationsystems. The architecture provides agents

that implement basic planning and controlfunctionality to process transport requestscoming from different users.

Driving safety and assistanceThis was one of the hottest topics at

ITSC 05, with five sessions covering it.Several papers discussed safety concerns,including pedestrian guidance, detection,and protection using various sensing meth-ods and landmark designs.

MARCH/APRIL 2006 www.computer.org/intelligent 97

Figure 1. A Petri net model for an urban traffic area: (a) an urban traffic area consistingof two intersections and 12 roads, and (b) the Petri net representing that area.1

(a)

(b)

Driving-assistance issues included

• lane-departure warning and lane guidance,• parking assistance,• visual assistance by virtual mirrors at

blind intersections,• frontal-collision warning,• virtual drivers and driver-in-the-loop

assistance,• networked environments for advanced

assistance,• sensor fusion,• calibration of cameras and other sensors,

and• driving-assistance performance evaluation.

Figure 3 illustrates the functional speci-fication for SASPENCE (Safe Speed and SafeDistance), a new approach in supportingdriver functions, cofunded by the EuropeanCommission (see www.prevent-ip.org/en/prevent_subprojects/safe_speed_and_safe_following/saspence).3 Another interesting

project from Europe is the INTERSAFE, whichfocuses on intersection safety. INTERSAFE

combines a bottom-up approach based onusing state-of-the-art sensors, high-levelmaps, and infrastructures for vehicle com-munication, and a top-down approach basedon a driving simulator (see figure 4).4

Traffic and travelerinformation services

Three ITSC 05 sessions covered thistopic. Presenters discussed public-trans-port information requirements as well aspassenger requirements for public-trans-port ticketing systems. They also discusseddynamic virtual-roadway-loop detectors,traffic information estimation using cellu-lar network data, and traffic-state detectionwith floating car data in road networks.(Floating car data entails recording trafficdata for a small number of vehicles that“float” with the traffic and serve as mea-suring stations. These vehicles are

equipped with traffic telematics devicesand record variables such as speed, posi-tion and direction of travel for a particulartrip.) Other topics included validating pre-dicted rural-corridor travel times from anautomated license plate recognition systemand using data fusion to examine trafficdynamics on freeways with variable speedlimits.

One author, Christian Steger-Vonmetz,discussed how to help make more carpool-ing efficient. In his paper “Improving ModalChoice and Transport Efficient with the Vir-tual Ridesharing Agency,” he reports on avirtual ridesharing agency in Austria calledWIGeoPOOL. The heart of WIGeoPOOLis corridor search, a GIS-based intelligentmatching algorithm.

Another interesting project in this area isRoncalli, which provides position-dependent,real-time information for drivers.5 The in-vehicle client (see figure 5) for Roncalliservices

98 www.computer.org/intelligent IEEE INTELLIGENT SYSTEMS

Figure 2. Northbound Autobahn 5 speed diagram.2 G1 through G15 represent bottlenecks.

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• offers intelligent speed adaptation and dis-plays the current speed limit at all times;

• warns the driver of poor skid resistanceor deep ruts;

• warns the driver of areas (mostly cross-ings) with high accident rates;

• warns the driver about “atypical” roadusers who need special attention, such aschildren (for example, it alerts driverswhen they’re near a school during schoolhours); and

• helps drivers reduce fuel consumptionand CO2 production by teaching andjudging eco-driving (environmentallyresponsible driving) using GPS data.

Vision-based technologySix sessions dealt with vision-based tech-

nology, and another dozen or so sessionsheld related discussions. Despite this cover-age, no new issues or applications emerged;presentations revealed that progress in thisarea has been incremental.

Discussions mostly focused on drivingassistance and safety, although BernhardHulin and Stefan Schüßler presented aninteresting vision-system application in theirpaper, “Measuring Vegetation along Rail-way Tracks.” The system, mounted on atrain, uses three multispectral cameras sensi-tive in both the visible and near-infraredspectrums. Using multispectral cameras isnecessary for distinguishing between thegreen vegetation and the overhead contactsystem’s green masts.

Communication and location-based services

Applications of ad hoc networks in trans-portation, especially for intervehicle com-munication (IVC), emerged at ITSC 05 as afast-growing research area. Figure 6 presentsa proposed functional architecture for in-carad hoc networks.6 When fully deployed, theIVC network will likely be one of the largestmobile ad hoc networks, so IVC networkprotocols must be able to scale to this largenetwork size and high nodal densities. How-ever, several other IVC issues exist. First,we need consecutive radio-zone DSRC(dedicated short-range communication) withan in-vehicle reactance diversity (which pro-vides a high-speed wireless link for travelingvehicles). We also need intervehicle commu-nication based on CSMA (carrier sense mul-tiple access) with distributed and pollingcoordination. Furthermore, we need to

explore adaptive space-division multiplex-ing and hybrid (both frequency-hoppingand direct-sequence) spread-spectrum tech-niques. Finally, we need media-access-control protocols for integrated intervehicleand road-to-vehicle communications.

The main IVC applications presented atITSC 05 were

• a complete simulator architecture forIVC-based intersection warning systems,

• a vehicle-to-vehicle-based traffic infor-mation system,

• traffic modeling and cost optimizationfor transmitting traffic messages over ahybrid broadcast and cellular network,

• a collision-avoidance and warning systemfor automobiles based on signals fromglobal-navigation satellite systems, and

• a T4 telematic system architecture fortransparent transports based on the openservices gateway initiative.

Finally, researchers reported on two inter-esting but primitive projects on location-

based services: location-based ticketing forpublic transportation and Web-based ubiqui-tous location-based services. The conceptsand methods proposed in those projects havegreat potential in the age of a connectedworld, but more testing and evaluation areneeded before their deployment.

Traffic modeling, simulation,and control

This is a traditional research area in trans-portation, and most papers presented in thisarea solve problems using conventionalmethods. However, several studies in trafficmodeling and simulation are applying newmethods and concepts to traditional problems:

• hardware-in-the-loop simulation ofembedded automotive control systems,

• a simulator of intelligent transportationsystems,

• the GESTRAF cellular-automata-basedtraffic simulator,

• the DisTrain train-dispatching simulator,and

MARCH/APRIL 2006 www.computer.org/intelligent 99

Short-rangeobstacledetection

Vehicle-to-vehicle

communication

Long-range obstacledetection

Maps andnavigation

Lanedetection

Vehicle globalpositioning

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Positionand

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Sensor and modules used in SASPENCE Scenario reconstructionand estimation

Criteria for HMI

Referencemaneuver

Host-vehiclepath

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Warningand

interventionstrategies

Human-machineinterface

Vehicle data

Figure 3. The functional specification for SASPENCE (Safe Speed and Safe Distance).3

• dynamic equilibrium assignment withmicroscopic traffic simulation and simu-lation-based dynamic traffic assignment.

Four studies with the PARAMICS simula-tion tool are very interesting. The first studyis developing and calibrating an integratedfreeway and toll-plaza model for the NewJersey Turnpike. The second is modelingand simulating an unconventional trafficcircle, and the third is developing a distrib-uted, scalable, and synchronized frameworkfor large-scale microscopic traffic simula-tion. The final study is modeling distributedlarge-scale traffic networks. A new develop-ment presented at ITSC 05 is the extensionof computer simulation to computationalexperiments based on artificial transporta-tion systems for ITS studies.7,8

Major new directions and applicationsfor ITS control and management include

• a general framework for managing trans-portation systems affected by recurrentadverse weather conditions,

• a mathematical programming modulefor merge control in system optimaldynamic traffic assignment,

• control of spatio-temporal traffic con-gestion at highway bottlenecks,

• traffic synchronization in Central Euro-pean upper airspace,

• a new incident-detection scheme devel-oped in the Netherlands,

• design and evaluation of a roadway con-troller for freeway-traffic, and

• an adaptive freeway-traffic-state esti-mator.

Another interesting direction is the idea of“soft control” in Variable Message Systems-based highway management. Examplesinclude providing information as a controlmeasure and the concept of line-control sys-tems (a succession of VMSs with displaysseparated by 1 to 3 km along a roadway).9

Also, in “A Novel Algorithm for Optimized,Safety-Oriented Dynamic Speed Regulationon Highways: INCA,” Vukanovic and hiscolleagues discussed using variable speedand information displays to optimize thedynamic regulation of roadway traffic toincrease traffic safety and to reduce unneces-sary delays.

Emerging research andtechnologies

Emergency evacuation as well as trans-portation intelligence for security are twoemerging research areas. Researchers atITSC 05 presented a case study of a hurri-cane in Ocean City, Maryland, where theyused an integrated emergency evacuationsystem for real-time operations. Relatedworks at ITSC 05 include global monitoringand security assistance based on the next-generation Internet and dynamic handling ofmultiple incidents in traffic evacuation man-agement. We should expect intensifiedresearch into emergency evacuations owingto increased concerns regarding terroristattacks and natural disasters, especially afterthe major traffic jam in Houston, Texas, dur-ing Hurricane Rita.

A special session on security informaticsand its application in ITS featured presenta-tions on prospective spatio-temporal dataanalysis for security informatics, the identi-fication of deceptive behavioral cues such ashead movement or certain gestures extractedfrom video, and target-vehicle identification

100 www.computer.org/intelligent IEEE INTELLIGENT SYSTEMS

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Road markings

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Scene model

Figure 4. The INTERSAFE system architecture.4 The architecture includes object detection,road-marking detection, and navigation based on natural landmarks.

Intelligent speedadaptation

Skidresistanceand ruts

Sensitiveareas

Accidentspots

Figure 5. A standard PDA as the in-vehicleclient for Roncalli services. 5

for border safety using mutual information.Intelligence and security informatics forITS will be a key technology for homelandsecurity.10–12

ITSC 06 will run from 17 to 20 Septem-ber 2006 in Toronto (see the “Conferences”sidebar). We hope to see more discussionon intelligent agent-based control for net-worked transportation systems. We alsohope to see more research into using large-scale and new computing methods such asgrid computing and peer-to-peer comput-ing for real-world transportation analysisand decision-making.

AcknowledgmentsThis work is supported in part by the National

Natural Science Foundation of China (grants60504025, 60334020, and 60125310), the Chi-

nese Academy of Sciences (grant 0359), Shan-dong Province (grant 2004GG1104001), Shan-dong Academy of Sciences (grants 2005006 and2004029), and the Key Laboratory of ComplexSystems and Intelligence Science of the ChineseAcademy of Sciences (grant 20050101).

References

1. A. Di Febbraro and D. Giglio, “On Adoptinga Petri Net-Based Switching Modeling Sys-tem to Represent and Control Urban Areas,”Proc. 8th IEEE Int’l Conf. Intelligent Trans-portation Systems (ITSC 05), IEEE Press,2005, pp. 185–190.

2. R.L. Bertini et al., “The German Autobahn:An ITS Test Bed for Examining DynamicTraffic Flow Phenomena,” Proc. 8th IEEEInt’l Conf. Intelligent Transportation Systems(ITSC 05), IEEE Press, 2005, pp. 502–507.

3. F. Tango et al., “Towards a New Approach inSupporting Drivers Function: Specificationsof the SASPENCE System,” Proc. 8th IEEE Int’lConf. Intelligent Transportation Systems(ITSC 05), IEEE Press, 2005, pp. 614–620.

4. K.C. Fuerstenberg, “A New EuropeanApproach for Intersection Safety—The EC-Project INTERSAFE,” Proc. 8th IEEE Int’l Conf.Intelligent Transportation Systems (ITSC 05),IEEE Press, 2005, pp. 343–347.

MARCH/APRIL 2006 www.computer.org/intelligent 101

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Figure 6. A proposed functional architecture for in-car ad hoc networks.6

ITSC 06: www.ewh.ieee.org/tc/its/itsc2006

IEEE Intelligent Vehicles Symposium: www.cvl.iis.u-tokyo.ac.jp/iv2006

IEEE Intelligence and SecurityInformatics Conference: www.isiconference.org/2006

2006 IEEE International Confer-ence on Service Operation andLogistics, and Informatics:www.ssglobal.org/2006

Conferences

5. R. Spielhofer et al., “Roncalli: Position Depen-dent In-Vehicle Real-Time Information forRoad Users—An Overview,” Proc. 8th IEEEInt’l Conf. Intelligent Transportation Systems(ITSC 05), IEEE Press, 2005, pp. 1012–1016.

6. M. Rabel,A. Schmeiser, and H.P. Grossmann,“Ad-Hoc In-Car Networking Concept,” Proc.8th IEEE Int’l Conf. Intelligent Transporta-tion Systems (ITSC 05), IEEE Press, 2005,pp. 143–148.

7. F-Y. Wang and S. Tang, “Artificial Societiesfor Integrated and Sustainable Developmentof Metropolitan Systems,” IEEE IntelligentSystems, vol.19, no. 4, 2004, pp. 82–87.

8. F-Y. Wang and S. Tang, “A Framework forArtificial Transportation Systems: FromComputer Simulations to ComputationalExperiments,” Proc. 8th IEEE Int’l Conf.Intelligent Transportation Systems (ITSC 05),IEEE Press, 2005, pp. 1130–1134.

9. F-Y. Wang et al., “Toward Intelligent Trans-portation Systems for the 2008 Olympics,”IEEE Intelligent Systems, 2003, vol. 18, no.6, pp. 8–11.

10. H.S. Chen and F.Y. Wang, “Artificial Intelli-gence for Homeland Security,” IEEE Intelli-gent Systems, vol. 20, no. 5, 2005, pp. 12–16.

11. W. Chang, D. Zeng, H. Chen, “ProspectiveSpatio-Temporal Data Analysis for SecurityInformatics,” Proc. 8th IEEE Int’l Conf. Intel-ligent Trans. Systems (ITSC 05), IEEE Press,2005, pp. 1120–1124.

12. M.L. Jensen et al., “Identification of Decep-tive Behavioral Cues Extracted from Video,”Proc. 8th IEEE Int’l Conf. Intelligent Trans-portation Systems (ITSC 05), IEEE Press,2005, pp. 1135–1140.

102 www.computer.org/intelligent IEEE INTELLIGENT SYSTEMS

Shuming Tang is a research scientist at the Institute of Automation,Shandong Academy of Sciences, and a professor at Xi’an JiaotongUniversity and Shandong University of Science and Technology.Contact her at sharron@ieee.org.

Fei-Yue Wang is a professor in the University of Arizona’s Systems & Industrial EngineeringDepartment and the director of the university’s Program in Advanced Research of Complex Sys-tems. He’s also the director of the Key Laboratory of Complex Systems and Intelligence Scienceat the Chinese Academy of Sciences. He’s president of the IEEE ITS Society and a fellow of theIEEE and Int’l Council of Systems Engineering. Contact him at feiyue@sie.arizona.edu.

Qinghai Miao is a research assistant at the Key Laboratory of Com-plex Systems and Intelligence Science at the Chinese Academy ofSciences’ Institute of Automation. Contact him at miaoqh@gmail.com.

CA

LLFORFOR

IEEE PERVASIVE COMPUTINGINTELLIGENT TRANSPORTATION

IEEE Pervasive Computing invites articles describingthe application of pervasive computing technologies,systems, and applications to vehicles, roads, and other transportationsystems. Example topics include the following:

• Vehicular pervasive applications• Intelligent transportation systems• Inter- and intravehicle communication and networking protocols• Automated or cooperative vehicles• Location sensing and awareness in intelligent transportation• Entertainment systems based on vehicular networking• Usability concerns, including real-time and safety issues• Human factor issues, including human-to-vehicle communication • Security, privacy, and trust issues in intelligent transportation• Impact of intelligent transportation on society

We invite full-length submissions of 4,000 to 6,000 words and work-in-progress submissions of 250 words or less.Please see the complete call for papers for additional details:

www.computer.org/portal/pages/pervasive/content/cfp4.html

Guest Editors: Liviu Iftode, Rutgers University, iftode@cs.rutgers.edu; Keith Farkas, HP Labs,keith.farkas@hp.com; John Heidemann, Information Sciences Institute, johnh@isi.edu

SUBMISSION DEADLINE: 31 MAY 2006 Submission address:

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