International Journal of Automotive Technology, Vol. 7, No. 4, pp. 509−517 (2006)
`
`Copyright © 2006 KSAE
`1229−9138/2006/028−15
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`OVERVIEW OF TELEMATICS: A SYSTEM ARCHITECTURE
`
`APPROACH
`
`K. Y. CHO1), C. H. BAE1), Y. CHU2) and M. W. SUH3)*
`
`1)Graduated School of Mechanical Engineering, Sungkyunkwan University, Gyeonggi 440-746, Korea
`2)Electrical and Computer Engineering Department, Mississippi State University, Box 9571,
`Mississippi State, MS 39762, USA
`3)School of Mechanical Engineering, Sungkyunkwan University, Gyeonggi 440-746, Korea
`
`(Received 25 January 2004; Revised 28 December 2005)
`
`ABSTRACT−In the mid 1990s, the combination of vehicles and communication was expected to bolster the stagnant car
`industry by offering a flood of new revenues. In-vehicle computing systems provide safety and control systems needed to
`operate the vehicle as well as infotainment, edutainment, entertainment, and mobile commerce services in a safe and
`responsible manner. Since 1980 the word “telematics” has meant the blending of telecommunications and informatics.
`Lately, telematics has been used more and more to mean “automotive telematics” which use informatics and
`telecommunications to enhance the functionality of motor vehicles such as wireless data applications, intelligent cruise
`control, and GPS in vehicles. This definition identifies telecommunications transferring information as the key enabling
`technology to provide these advanced services. In this paper, a possible framework for future telematics, which is called
`an Intelligent Vehicle Network (IVN), is proposed. The paper also introduces and compares a number of existing
`technologies and the terms of their capabilities to support a suite of services. The paper additionally the paper suggests and
`analyzes possible directions for future telematics from current telematics techniques.
`
`KEY WORDS : Vehicle telematics, Intelligent vehicle network, In-vehicle network architecture
`
`1. INTRODUCTION
`
`Telematics technologies might indeed deliver an enticing
`variety of in-vehicle services, which may still revolutionize
`the experience of driving. Telematics may help carmakers
`obtain an ongoing revenue stream and help regulators
`progress towards intelligent transportation system and
`their associated benefits of pollution reduction, reduced
`transit times, and reduced road fatalities. Also for con-
`sumers there should be an effective service price reduc-
`tion via economies of scope and the less quantifiable
`benefits associated with access to safety and security
`services. There is a very interesting report published by
`ATX Technologies about customers’ desire for advanced
`technologies (Wallace, 2000). Through surveying their
`telematics subscribers, ATX Technologies confirmed the
`popularity of telematics systems. Approximately 70
`percent of the subscribers indicated they would ask a
`telematics system on their next vehicle. Over 80 percent
`would recommend the telematics system to a friend or
`acquaintance.
`It is important to understand the definition of telematics
`
`*Corresponding author. e-mail: suhmw@yurim.skku.ac.kr
`
`and what constitutes a telematics-enabled automobile.
`Since 1980 the word “telematics” has meant the blending
`of telecommunications and informatics (Zhao, 2002).
`This definition identifies telecommunications transferring
`information as the key enabling technology to provide
`these advanced services. Also from a hardware stand-
`point we expect, in general, the following conditions are
`required for future telematics (Mattias, 1998):
`
`• In-vehicle processor with application programs.
`• Bus-based or wireless networking.
`• Safety unit and dynamic navigation.
`• Self-diagnostic device with user-friendly interfaces.
`• Enterainment and multimedia devices.
`• Emergency support, etc.
`
`In this paper, we introduce current telematics techno-
`logies and propose a possible framework for future
`telematics, which is called Intelligent Vehicle Network
`(IVN). For current technologies, we introduce and com-
`pare a number of existing technologies and the terms of
`their capabilities to support suitable services. In addition,
`the paper suggests and analyzes possible directions for
`future telematics from current telematics techniques.
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`The structure of this paper is as follows: In section
`2 which is composed into four sub-sections, we introduce
`and compare a number of existing technologies and the
`terms of their capabilities to support a suite of services;
`A possible framework for future telematics, which is
`called an Intelligent Vehicle Network (IVN), proposed in
`this paper is discussed in section 3; and section 4 suggests
`and analyzes possible directions for future telematics
`from current telematics techniques and concludes this
`study.
`
`2. CURRENT TELEMATICS TECHNOLOGIES
`
`In this section, we introduce and compare a number of
`existing technologies and the terms of their capabilities to
`support suitable services. These technologies can be
`generally divided into four parts, in-vehicle networking
`(IN), intelligent transport system for driver’s safety,
`vehicle diagnostics system, and in-vehicle entertainment
`system.
`
`2.1. In-vehicle Networking (IN)
`Many vehicles already have a large number of electronic
`control systems. The growth of vehicle electronics is
`partly the result of the customer’s wish for better safety
`and greater comfort. And it is partly the result of the
`government’s requirements for improved emission control
`and reduced fuel consumption. The complexity of the
`functions implemented in these systems needs an exchange
`of the data between each device. With conventional
`systems complex (William et al., 1997), data
`is
`exchanged by means of dedicated signal lines, but this is
`becoming increasingly difficult and expensive as control
`functions become ever more. Moreover, a number of
`systems are being developed that implement functions
`covering more than one control device. For overcoming
`these problems, various methods have been carried
`out.
`The candidate protocols of IN should satisfy the
`conditions, which are simple wire, easy to use, wide
`application range, flexibility and low cost.
`In the following, the protocol, which is developed or
`being developed, is introduced and compared by terms of
`its characteristics and advantages.
`
`2.1.1. D2B (Domestic Digital Bus)
`Philips Consumer Electronics developed Domestic Digital
`Bus, or D2B for short, in 1988, and the standard was
`published in 1991. Originally developed with home audio
`in mind, it later became apparent that D2B was suitable
`for in-car use (Sweeney, 2002).
`D2B Transfer Technology has the advantage of low
`cost, no interference and reliable operation, and no
`quality loss of the signal.
`
`2.1.2. Bluetooth
`Bluetooth is a short-range general-purpose wireless networ-
`king standard. Originally intended as a wire replacement
`for connections between computers, PDA (personal digital
`assistants), cell phones, and other devices, it has grown to
`become a personal area network (PAN) standard the
`applications of which grow daily (Khan, 2001).
`Bluetooth Transfer Technology has the advantage of
`low cost, low power, good at Wide Area Network (WAN)/
`Local Area Network (LAN) access points, support both
`voice and data, and operate in a license free band 2.45
`GHz (Chaari et al., 2002).
`
`2.1.3. CAN (Controller Area Network)
`CAN, Controller Area Network, is a serial bus system
`designed for networking ‘intelligent’ devices as well as
`sensors and actuators within a system. CAN was original-
`ly developed for passenger car applications. CAN is a
`serial bus system with multi-master capabilities, which
`means that all CAN nodes are able to transmit data and
`several CAN nodes can request the bus simultaneously.
`The serial bus system with real-time capabilities is the
`subject of the ISO 11898 international standard and
`covers the lowest two layers of the ISO/OSI reference
`model (Wense, 2000).
`CAN protocol has the advantage of very little cost and
`effort to expend on personal training, low-cost controller
`chips can be employed in data link, and high transmission
`reliability/Short reaction times.
`
`2.1.4. LIN (Local Interconnect Network)
`In June 1999, five major European car manufacturers,
`one semiconductor supplier, and one tool vendor agreed
`on a specification for a class - multiplex protocol called
`LIN (Local Interconnect Network) (MOST Cooperation,
`1999).
`LIN message structure has the advantage of only
`master node determines scheduling, no arbitration takes
`place, schedule determined by a table, and latency &
`transmission are well known.
`
`2.1.5. MOST (Media Oriented Systems Transport)
`MOST, Media Oriented Systems Transport, was develop-
`ed in conjunction with DaimlerChrysler, Becker, BMW,
`and Oasis beginning in 1997. It can be looked at as a
`successor of D2B even though D2B is an independent
`system that will continue in other applications. With the
`ever-increasing number of devices in vehicles, it was
`apparent that a new form of data transfer had to be
`developed to cope, and MOST is the result (Parnell,
`2003).
`MOST protocol has the advantage of ease of use, wide
`application range, synchronous bandwidth, asynchronous
`bandwidth, flexibility, synergy with consumer and PC
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`industry, low implementation cost, and open systems
`interconnect reference model.
`
`module's definition and detail content is described at the
`following paragraphs.
`
`2.1.6. IDB-1394
`The IDB (Internal Data Bus) Form manages the IDB-C,
`IDB-1394 buses, and standard IDB interfaces for OEMs
`for the development of after-market and portable devices.
`Based on the CAN bus, IDB-C is geared toward devices
`with data rates of 250 Kbps. Applications for IDB-C
`include connectivity through consumer devices such as
`digital phones, PDAs, and audio systems (Hadeler and
`Mathony, 2000).
`
`2.1.7. System comparison
`The requirements with respect to data transfer rate,
`protocol mechanism, reliability, fault tolerance, and costs
`are dependent of their applications and have led to the
`development and introduction of different network types.
`Figure 1 shows the characteristics of in-vehicle networks
`(Juliussen, 2003).
`
`2.2. Intelligent Transport System
`In the field of vehicle telematics, an intelligent transport
`system project has been developed to improve the
`driver's safety and driving comfort on any type of roads.
`This section introduces N.A.I.C.C. (Navigation Aided
`Intelligent Cruise Control) system that is presented by
`(Lauffenburger et al., 2000). Generally, the purpose of an
`N.A.I.C.C. system is the driver alarm and the velocity
`control. In order to achieve this purpose, the N.A.I.C.C.
`system is based on a positioning module, a map-matching
`algorithm, a digital map database, a real-time velocity
`estimator, and a speed prediction module.
`The appropriate speed can be predicted by considering
`the road characteristics. When the appropriate speed is
`calculated, the constraints are provided data such as
`driving style and speed reference. The sensors mounted
`on the vehicle and the real-time velocity estimator
`provides some information to the constraints. Each
`
`Figure 1. Characteristics of in-vehicle networks.
`
`2.2.1. The positioning module
`Positioning information is obtained by multi-sensor inte-
`gration and fusion. Each sensor has its own capabilities
`and independent failures. The reason for multi-sensor
`integration and fusion is to compensate for the failures.
`The positioning module is based on GPS (global position-
`ing system) system (Guo et al., 2001) and Dead-
`Reckoning (Redmill et al., 2001; Calafell et al., 2000)
`data fused via filtering methods such as Kalman filters.
`Dead-Reckoning (DR) method and GPS systems operate
`together to compensate for their failures because the DR
`method uses relative positioning techniques and GPS the
`system is absolute positioning techniques. The position-
`ing module is very important in the N.A.I.C.C. system,
`because most accurate vehicle positioning is best
`performance of the N.A.I.C.C. system. Therefore, the
`fusion algorithm (Lauffenburger et al., 2000) has been
`implemented for accurate vehicle positioning. The
`fundamental concept of fusion algorithm increases
`accuracy by using the DR method when Differential
`Global Positioning System (DGPS) is used in an
`inappropriate environment. In other words, this algorithm
`uses the DGPS data when the signals are available and
`switches to the DR method when the number of visible
`satellites is not sufficient to ensure an accurate position.
`
`2.2.2. The digital map database
`In the N.A.I.C.C. system, the digital map database
`(Claussen, 1993) is an important system that relates to
`matching the trajectory and the known road or deter-
`mining the optimal speed. The road curvature provided
`by the digital map database is used to determine whether
`the vehicle is located on a straight road or not and to
`predict the optimal speed. The Bezier curves approxi-
`mation method (Venhovens et al., 1999) allows a
`parametric description of the curve. This approximation
`method enables any type of curve to be defined.
`Therefore, the storage memory for a digital map database
`is not important compared with a traditional database
`structure. The basic concept of approximation is to
`consider every road as a bend, a straight line having a
`particular bend with an infinite radius of curvature.
`
`2.2.3. The map-matching module
`As presented in section 2.2.1 the fusion algorithm
`switches to the DR method when the DGPS is not
`sufficient to ensure an accurate position. Once the DR
`method is active, the system will gather an accumulative
`error. Thus, the DR position must match the nearest point
`on the digital map. The map-matching module for the
`N.A.I.C.C. system is based on an algorithm using only
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`geometric information called Geometric Point-to-Point
`Matching. The basic concept of Geometric Point-to-Point
`Matching is to match the point provided by the position-
`ing module to the nearest point of a Bezier curve in the
`digital map database. This is more efficient than a
`traditional point-to-point algorithm because it is only
`necessary to calculate the distance between the dead-
`reckoned point and each point in the database to find the
`nearest point (Caves et al., 1991).
`
`2.2.4. The speed prediction module
`As shown earlier, the purpose of the N.A.I.C.C. system is
`the driver alarm and the velocity control. The optimal
`speed predicted by the speed prediction module (Holzmann
`et al., 1997) is compared with the estimated vehicle
`speed, and the system warns the driver of an inappro-
`priate speed. At the same time, the system automatically
`adjusts the vehicle speed via a cruise control system
`(Ioannou et al., 1993). The speed prediction module
`requires some specific information to calculate the
`appropriate speed. Finally, the determination of the
`velocity is modeled by a finite state machine and adapted
`to the N.A.I.C.C. system.
`The N.A.I.C.C system will play an important role in
`the future, not only to assess macroscopic traffic situ-
`ations, but also to build microscopic road geometry
`databases. Communication technologies with an appro-
`priate bandwidth, latency, and coverage need to be
`developed in order to enable the N.A.I.C.C. On the GPS
`side, there is a clear need for accurate low-cost receivers
`in combination with an extensive network of differential
`corrections.
`
`2.3. Vehicle Diagnostics System
`Vehicle diagnostics systems have been developed as
`design controls for system faults, which may result in
`failure modes. The final goal of diagnostics systems is to
`provide to the vehicle the best possible performance of all
`the electronics systems placed in the vehicle. Low cost
`displays and processors allow sophisticated diagnostics
`information to be accessed and displayed in the vehicle
`without requiring additional service-bay tools. In addition,
`inexpensive wireless wide-area networks allow remote
`access to the vehicle’s electronic systems and thus allow
`for services such as predictive maintenance (Cirilo et al.,
`2000). This section introduces architecture of remote
`diagnostics system.
`
`2.3.1. The vehicle electronic architecture & diagnostics
`system
`The vehicle electronic architecture (Amberkar et al.,
`2000) has two modules. An engine control module is
`responsible for capturing the electric signals of the
`sensors’ management and the ideal amount of fuel to be
`
`injected on the exact moment through the time of
`opening and closing of the injection valves. Another
`module is responsible for receiving the electronic signals
`of the footpedal accelerator and also of providing other
`functions of the cabin, such as engine brake, power take
`off, management of the sent or received information from
`the instrument cluster, and others. Besides, these modules
`can also interact with other existent ECU (Electronic
`Control Unit)’s in the electronic architecture responsible
`to manage specific functions of the vehicle, such as
`brakes, maintenance, gearbox and retarders, door
`controls and immobilizers.
`In general, vehicle diagnostic systems are composed of
`an on-board diagnostic system, an off-board diagnostic
`system, and wireless communications. The on-board
`diagnostic system (Shultz et al., 2002) performs presen-
`tation of diagnostics information to the vehicle operator,
`other
`telematics applications, transmission of vehicle
`information, reactions to updates of vehicle parameters,
`and maintenance of security for access to vehicle
`diagnostic systems. Thus, the vehicle diagnostic system
`requires access to vehicle information that is provided
`from a data bus on-board the vehicle. The off-board
`diagnostic system gives necessary information to perform
`a preventive and corrective maintenance of the vehicle in
`the workshop. In the off-board diagnostic system, much
`diagnosis information requires more technical know-
`ledge. Wireless communication is used to interface
`between the on-board and off-board diagnostic system
`for vehicle diagnostic systems. The progress of wireless
`communication increases the capabilities of vehicles to
`self-diagnose known failure modes that they have been
`pre-programmed to detect.
`
`2.3.2. Architecture of integrated diagnostics system
`Architecture of integrated diagnostics system (Campos et
`al., 2002) is composed of the enterprise, application, and
`client.
`The enterprise data layer is composed of the vehicle
`specific configuration database, vehicle diagnostic con-
`tent database, and the vehicle test specification database.
`These databases support the lower level diagnostic appli-
`cations. The lower level diagnostic applications need to
`interface with other enterprise information systems. In
`order to interface with other enterprise information
`systems, the J2EE (Borland, 2003) framework provides a
`connector API (Application Program Interface), which is
`used to create adapters to provide common access to the
`enterprise layer. The enterprise data layer also captures
`the summary data that is being collected from all of the
`diagnostic sessions. Thus, the diagnostics experiential
`database contains not only the information about the
`symptoms of a vehicle problem, but also a history of the
`diagnostic steps. This information can be used to opti-
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`mize the diagnostic processes that are used to resolve
`future problems.
`The application server layer performs hosting diagnostic
`applications, managing diagnostic sessions, sending dia-
`gnostic bundles to diagnostic clients, pre-processing and
`sending configuration data to the client-side diagnostic
`applications, downloading configuration data to vehicle
`processors, and downloading new software to vehicle on-
`board processors. The remote diagnostic scenario is a
`subset of the total diagnostics infrastructure needed to
`support the vehicle fleet during its lifecycle. For the
`remote diagnostics scenario, the diagnostic application
`developer will have to perform a trade-off between on-
`board and off-board processing. The obvious benefit of
`this architecture is that every unit in the fleet could
`receive a software update without having to return to the
`base location.
`Client devices and applications perform hosting on-
`board diagnostic applications, executing diagnostic bundles
`delivered from the remote server, reading data from
`processors on the vehicle data bus, sending data to the
`remote server, writing configuration parameters to pro-
`cessors on the vehicle data bus, downloading new soft-
`ware to vehicle processors, and commanding processors
`to actuate devices under their control. The client architec-
`ture provides secure and controlled access to the vehicle
`data bus through the implementation of custom bundles
`for server messaging and vehicle communications inter-
`face.
`Vehicle diagnostics systems may be the most impor-
`tant telematics application for the auto manufacturers
`because vehicle diagnostics system has potential savings
`in operational cost, warranty cost, and design improve-
`ments.
`
`data include navigation information from a GPS and
`maps, entertainment systems, mobile phones, and in
`some regions, road-tolling systems, that can be updated.
`The output data include driver and passenger screens and
`audio.
`An in-vehicle entertainment system must include traffic
`information systems, Internet/Web access, electronic game
`consoles, mpeg music download capability, digital radio
`reception, and mobile commerce services. The optical
`bus system enables further integration of computing
`functions and computing applications, which require
`interactivity for Internet access and games. These appli-
`cations can be connected via gateways to PC platforms.
`A gateway is a router between the different electrical and
`optical buses in a vehicle. Gateways to the optical bus
`may connect the mobile phone, the media changer, the
`navigation unit and other devices to a PC in the vehicle,
`at the same time may give displays for the front and rear
`seats access to the PC unit.
`An in-vehicle entertainment controller is composed of
`processor, telematics, interface, and entertainment, as
`shown Figure 2. The processor provides all of the control
`functions of the system. The GPS, wheel sensors, and
`tachometer interfaces receive navigational, wheel-speed,
`and engine-speed information and pass it to the LCD
`graphics controller for display. The entertainment unit
`provides access to the automobile's CD-ROM player,
`where MP3 music files are stored. The system's naviga-
`tional data, as used by the GPS system, can also be stored
`here. MP3 music files are sent to the automobile's audio
`system for playback via the audio interface. The interface
`unit provides the controller access to all of the auto-
`mobile's driver-information and entertainment systems,
`such as the on-board-computer, via the Ethernet interface.
`
`2.4. In-vehicle Entertainment System
`(Schopp and
`An
`in-vehicle entertainment system
`Teichner, 1999) is a system integrator that displays data
`efficiently for the driver and other passengers. The input
`
`3. INTELLEGENT VEHICLE NETWORK(IVN)
`
`In this paper, a possible framework for future telematics,
`which is called an Intelligent Vehicle Network (IVN), is
`
`Figure 2. Configuration of the in-vehicle entertainment system.
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`and wireless Web connection, it also displays/announces
`information of a vehicle’s conditions and controls a sub-
`unit’s behavior.
`The detailed conditions required for an MCU are
`shown in Figure 4. That is, the interface to the sub-units
`is always made through an in-vehicle network connec-
`tion. The format of the requests and responses are
`standardized.
`Defining the interface as a network connection makes
`the interface programming independent and flexible.
`Because the software life cycle is shorter than a vehicle’s,
`the MCU can be upgraded easily after installation through
`wireless communication. The communication with the
`driver must be supported by various methods, such as a
`user-friendly graphic interface and voice recognition.
`In the Table 1, the platforms Microsoft Car.Net and
`Sun Microsystems Java platform are introduced (Rogers
`et al., 2000). Figure 5 shows the concept of relationship
`between MCU and Adaptive Network Architecture (ANA).
`
`3.2. Adaptive Network Architecture
`This section describes the overall architecture of an
`adaptive network. The fast improvement of the networks
`has led to the change of service from text based media
`applications to multimedia applications. In these condi-
`tions, two factors should be considered.
`Firstly, service specific network environment should
`be provided. According to a media type, different trans-
`mit systems and different levels of Quality of Service
`(QoS) are used. Secondly, networks should have an
`
`Figure 5. Master control unit & adaptive networkar-
`chitecture.
`
`Figure 3. Intelligent vehicle network.
`
`Figure 4. The requirement of master control unit.
`
`proposed. The IVN consists of a Master Control Unit
`(MCU), an Adaptive Network Architecture (ANA), an
`In-vehicle network, a User Friendly Diagnosis (UFD)
`unit, a safety unit, and an entertainment unit. Figure 3
`shows the relationship between units.
`
`3.1. Master Control Unit (MCU)
`In this section, a description is given of MCU, which is a
`platform of the telematics systems that manages many
`customized services such as information, entertainment,
`
`Table 1. The comparison of car.net and java.
`
`The Microsoft Car.Net platform
`
`Sun Microsystems Java platform
`
`• A potential platform for delivering Telematics applications
`
`• Available for a wide variety of devices
`
`• An XML/internet centric framework
`
`• The most widely known user interface
`
`• Neutral language platform
`
`• Extensive standard libraries
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`tecture is proposed here. An example model of Adaptive
`Network Architecture is shown in Figure 6. The vehicle
`contains an MCU and an ANA and connects across an
`air-interface by wireless communication to a server and
`call center system (Noh et al., 2001; Ciocan, 1990).
`The vehicle subsystems can also be presented in more
`detail, as shown in the example in Figure 7. The user
`interface controller represents the audio-video display
`and input methods such as buttons, touch screen, and
`voice. Communication between the in-vehicle compo-
`nents and the exterior is managed by the ANA.
`
`4. THE FUTURE OF VEHICLE TELEMATICS
`
`AND CONCLUSIONS
`
`During the last two decades, the automobile has made the
`transformation from an analogue machine with mostly
`mechanical and hydraulic control systems to a digital car
`with a rapidly growing volume of computer-based control
`systems. Vehicles in the future will have significant
`increases in capability and demands for wireless com-
`munications resources. Applications include vehicle status
`and maintenance information, navigation information,
`entertainment, and concierge services. To meet these
`needs, the vehicle must have the capability to allocate
`and prioritize communications resources in response to
`the needs of applications (Arnholt, 2000).
`The telematics connection in the vehicle of 2010 very
`likely will incorporate most of the leading-edge items
`that can be found in many high-end vehicles today or will
`be in the not-too-distant future: a built-in GPS and
`wireless phone link and a connection to all of the
`vehicle's on-board sensors and an in-vehicle display unit
`
`Figure 6. Adaptive network architecture.
`
`Figure 7. Adaptive network architecture decomposition.
`
`ability to adapt against the change of QoS.
`At present, a lot of research on adaptation in mobile
`networks are carried on, as are the studies on QoS
`management and adaptation. An adaptive network archi-
`
`Table 2. Prospect of the automobile telematic system.
`
`Current offering
`
`Future offering
`
`Safety and
`security
`
`Mapping/Traffic
`
`· Automatic collision notification
`· Roadside assistance
`· Remote door unlock
`· Embedded voice service
`
`· On-board turn by turn directions
`· CD based electronic maps
`· GPS location tracking
`· Dynamic route guidance
`
`Entertainment
`
`· Satellite radio
`· Stand-alone devices
`
`Communications
`
`· Hands free voice dialing
`
`· Basic auto diagnostics
`· Medical profiling
`· Voice recognition
`
`· Real-time traffic information
`· Location based services
`· Off-board, real time navigation info
`
`· Streaming media
`· Chat
`· Web browsing
`· Mp2/MPEG download
`· Mobile-commerce
`· Games
`
`· Mobile office
`· Voice mail
`· E-mail
`· Video phone
`· Personal data synchronization
`· Vehicle service appointments
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`or portable display units similar to current PDAs (personal
`digital assistants) (Greer, 2001).
`Automotive system engineers have begun evaluating
`different types of advanced wireless technologies for
`inclusion in their future models. Driven by the profound
`success of cellular and personal communications systems
`(PCS), information access is the key to providing new
`consumer value. And wireless is the only way to get it in
`an automobile. In the coming years, expect to see all of
`Table 2: (Telematics Research Group, 2002).
`Continued technology improvements and cost declines
`will drive the telematics industry. Telematics hardware,
`software, and services will improve dramatically in the
`next ten years due to telematics and automotive electro-
`nics advances, and also from technology improvements
`in the computer, tele communications and consumer
`electronics industries. The role of future telematics will
`increase the interaction between the driver, the vehicle
`and the environment. There are still many huddles to
`overcome, such as costs for hardware devices, bandwidth
`of air carriers and operating costs. We believe these will
`diminish over the next few years.
`In this paper, we have introduced and compared a
`number of existing technologies and the terms of their
`capabilities to support a suite of services. In addition, the
`paper has suggested the possible framework for the
`architecture of future telematics. Telematics can be a key
`to making car sharing or public transport work. Also the
`use of telematics can be very effective in making the zero
`and low emission vehicles an attractive alternative for the
`end users.
`This paper will have a major impact on the work of
`telematics consultants and policy makers who will be
`able to rapidly understand the configuration of new
`architecture and techniques in the management and
`planning of transportation areas.
`
`ACKNOWLEDGEMENT−The author’s are grateful for the
`support provided by a grant from the Brain Korea project.
`
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