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AUTOMATIC VEHICLE IDENTIFICATION: TECHNOLOGIESAND FUNCTIONALITIESDavid Bernstein a & Ammar Y. Kanaan ba Massachusetts Institute of Technology , 77 Massachusetts Ave., Room 1-138, Cambridge,MA, 02139, USAb Parsons De Leuw, Inc , Prudential Center, Boston, MA, 02199, USAPublished online: 24 Oct 2007.
To cite this article: David Bernstein & Ammar Y. Kanaan (1993) AUTOMATIC VEHICLE IDENTIFICATION: TECHNOLOGIES ANDFUNCTIONALITIES, I V H S Journal: Technology, Planning, and Operations, 1:2, 191-204, DOI: 10.1080/10248079308903792
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IVHS Journal. 1993, Vol. 1(2), pp. 191-204 Reprints available directly from the publisher Photocopying permitted by license only 0 1993 Gordon and Breach Science Publishers S.A. Printed in the United States of America
AUTOMATIC VEHICLE IDENTIFICATION: TECHNOLOGIES AND FUNCTIONALITIES
David Bernstein' and Ammar Y. Kanaan2 I: Massachusetts Institute of Technology
77 Massachusetts Ave., Room 1-138 Cambridge, MA 02139 USA
2: Parsons De Leuw, Inc. Prudential Center Boston, MA 021 99 USA
Automatic vehicle identification (AVI) was first introduced in the United States in the 1960s and 1970s However, in spite of several successful tests, AVI systems were not widely implemented. Now there is a resurgence of interest in AVI, both because of recent techno- logical advances and because of the important role that AVI plays in integrated intelligent vehicle highway systems (IVHS). This paper reviews different AVI technologies and their functional capabilities In particular, it describes dinerent generic AVI systems, their charac- teristics, and how AVI technology can be and has been applied to tolurevenue collection, access control, surveillance, and fleet management.
Key words: automatic vehicle identification, electronic toll collection, traffic management, road pricing.
A great deal of time, money, and effort has been devoted to determining the "relationship" between a vehicle and the highway, and this effort has taken
many different forms. First, there are automafic vehicle detection systems, which are designed to determine if any vehicle is present at a particular location at a particular time. Second, there are automatic vehicle location (AVL) systems, which are designed to determine the location of a particular vehicle (typically using long-range commu- nications) at a particular point in time. Finally, there are automatic vehicle identijica- tion (AVI) systems, which are designed to uniquely identify (typically using short- range communications) the vehicle that is located at a specific location at a particular time. ' Both the technologies used to achieve each of these different objectives and the uses of these technologies are quite different. In this paper we consider both the technology and the application of AVI.
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AVI was first introduced in the 1.960s for railroad cars (under the acronym ACIfor automatic car identification), but by the 1970s it had found its way to roadvehicles as well [Hauslen, 1977], [Foote, 1980,1981]. For example, in 1972 the PortAuthority of New York and New Jersey was funded by the FHWA to test fourdifferent AVI systems. These tests were conducted (using buses) on a ramp approaching the Port Authority Bus Terminal. Also around this time, the Golden Gate Bridge,Highway and Transportation District installed an AVI system on buses operated bythe district and the Southern California Rapid Transit District in Los Angeles testeda system for logging buses into and out of a parking/storage lot [Foote, 1981].
While the initial tests were quite positive, little became of them. This was, at leastin part, because the technology proved to be both unreliable and cumbersome (for aninteresting theoretical analysis see [Martin and Scott, 1992]). Though these initialstudies did result in more testing (e.g., in 1976 the New Jersey Turnpike Authoritybegan testing a microwavesystem and in 1978 the Port Authority of NY and NJ begantesting infrared and microwave systems on buses, cars, and vans using the LincolnTunnel), few if any systems were implemented on a large scale.
Now, however, the promise of integrated intelligent vehicle highway systems (IVHS)has again focused attention on AVI. Thus, the purpose of this paper is to reviewsome of the different approaches to AVI that have been proposed and developed andto describe some of the functional capabilities of these technologies. We begin with adescription of AVI technologies and the performance and capabilities of these technologies. Then, we describe different ways in which these technologies can be andhave been applied. Finally, we conclude with a brief discussion of the future of AVI.
AVI TECHNOLOGIES
There are currently between 15 and 20 different manufacturers of AVI equipmentand, not surprisingly, all of the systems are unique in some respect. Hence, it isimpossible for us to provide a comprehensive discussion and review of each. Instead,we will describe the characteristics of various generic systems. We begin with adiscussion of the hardware, then consider the typical performance and capabilities ofdifferent types of systems.
The Hardware
AVI systems have two major components, the in-vehicle unit (IVU or tag or transponder) and the roadside unit (or reader or interrogator), and a communications linkbetween them. In addition, almost all applications require a host computer and acommunications link connecting the reader and the host. However, since the technologies used in these last two components are not specific to AVI, we will not considerthem here.
One of the key distinguishing features of a particular AVI system is the portion ofthe electromagnetic spectrum it uses. Most existing systems transmit information as
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Table I. Microwave/RF Transmission Schemes (IVU to Reader)
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Power for Transmission
Power from IVU or Vehicle No Power from IVUNehicle
Continuous A -
Transmission
Type of Transmit on B DTransmission Interrogation
Reflection/ C EEcho
visible light, infrared radiation, microwaves, or radio waves. Each has its own advantages, disadvantages, and operating characteristics.
There are two different types of systems that operate in the range of visible light toinfrared. In the first, the IVU is a barcode (usually affixed to a side window) and thereader is typically a low power laser that creates a curtain of light using vertical orhorizontal scanning. As the IVU passes through the curtain the reflected light isreceived by the reader as an analog signal which is analyzed, decoded and convertedinto digital form [Hauslen, 1977], [Wrobel and Langston, 1990]. In the second, theIVU is a number plate (often the vehicle's license plate) and the reader is a CCDcamera (usually with a shutter time ranging between 1/500 to 1/15000 of a second)combined with an image processing unit (which includes memory, a microprocessorand a recognition algorithm)" These systems often also include a light source (eithercontinuous or stroboscopic) for night use. They can operate at various differentresolutions (i.e., the number of pixels in the image and the number of colors orshades of gray) and use any of a number of different recognition algorithms [Kanayama et al., 1991].
Other systems operate in the microwave and radio frequency (RF) ranges (usuallybetween 120 kHz to 9.9 GHz). These systems are best classified according to the wayin which the IVU conveys information to the reader. Typically, the different systemsare referred to as either being active or passive. Unfortunately, however, these termshave not been used consistently in the past-while some authors use these terms todescribe the power source of the IVU, others use them to describe the IVU's transmission capabilities. To avoid confusion, we prefer not to use these terms at all andinstead use the scheme depicted in Table I (See Table I). That is, we categorize thesesystems based on the type of transmission and the source of power for the transmission from the IVU to the reader (as distinct from the source used to power localmemory).
IVUs in cell A of Table I transmit continuously using an internal power source(either a battery or the vehicle's electrical system). Thus, these IVUs must contain acomplete transmitter. IVUs in cell B of Table I only transmit when they are interrogated by the reader, but again they have their own power source and completetransmitter. In these cases, the interrogation beam can be either pulsed or continuouswave (CW) but pulsed beams are used most often. IVUs in cell D of Table I get their
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power from the interrogation beam (which must be CW but can be turned off if othermeans are used to detect the presence of a vehicle) and hence can only transmit wheninterrogated. The CW it receives is modulated [using either amplitude shift keying(ASK) or frequency shift keying (FSK) depending on the system] with an identification code and other information stored in memory. IVUs in cell E of Table I do notactually transmit a signal at all, but merely reflect the interrogation beam afterencoding it with an identifier (for example, a barcode created using metallic ink orwire can be used in a reflective microwave system [Constant, 1972]). A special class ofIVUs in cell E are those which make use of surface acoustical wave (SAW) technology. In these systems, the IVU on the vehicle is simply an antenna and a lithiumcrystal which, when activated, has an acoustical wave created across its surface. Thesignals (usually pulsed) received by the IVU antenna are encoded by the SAW deviceand then returned to the antenna. The amplitude modulation of the echo signal isdetected by the reader as the unique identifier of the IVU [Morgan, 1985]. Finally,IVUs in cell C of Table I reflect an interrogation beam after encoding it with anidentifier, however, the encoding process itself requires power from the IVU (e.g.,an internal battery is used to modulate the reflected signal).
Another key distinguishing feature of AVI systems is the placement of the readeror the reader's antenna. In all cases, the reader/antenna can either be located alongthe side of the facility or overhead (which requires a support structure). In addition,microwave and RF antennas can be buried in the pavement [Gravelle and Walker,1990]. RF and microwave systems also have the option of using two different antennas, one for inbound messages and one for outbound messages, or to use multipleantennas to accommodate multiple IVU locations.
The final important distinguishing feature of different AVI systems is the placement of the IVU. Of course, in many cases this is closely tied to the placement andtype of reader used. However, it is also important to differentiate between systemswhich use mounted IVUs and those which use hand-held IVUs.
Performance
It would be inappropriate in a paper of this kind to compare the performance ofdifferent specific systems. Fortunately, it is possible to provide some idea of howthese different approaches perform in general. To that end, the discussion that follows summarizes the findings of several studies [Covil, 1987], [Bergan et al., 1988],[Wrobel and Langston, 1990], [Center for Urban Transportation Research, 1990],[Hills and Blythe, 1990], [Blythe et al., 1991].
Optical/infrared systems that make use of a special IVU (e.g., a barcode as opposedto the vehicle's license plate) operate at vehicle speeds up to 55 mph, have a maximumrange of two (2) to ten (10) feet, and are very sensitive to the orientation of the IVU.Under good conditions, the reported accuracy of these systems is usually in the 99.5%to 99.9% range. Optical systems that use the vehicle's license plate as an IVU havesimilar characteristics but do not, as yet, perform as well. These systems are accurateabout 90% of the time during the day and only 65% of the time at night. In general,optical/infrared systems tend to be sensitive to both weather conditions and dirt.
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AUTOMATIC VEHICLE IDENTIFICATION 195
Microwave/RF systems tend to operate at much higher speeds (up to 180 mph)and much greater range (up to 250 ft). Their sensitivity to the orientation of the IVUvaries with the power source, the frequency, and the design of the antenna. Unpowered IVUs tend to be more: sensitive to their orientation and require a more powerfulinterrogation beam. Powered IVUs, on the other hand, are much less sensitive totheir orientation and require much lower powered transmissions. In general, averagepower requirements tend to range from 20mW to 300mW for powered IVUsandbetween 750mWand 2W for unpowered IVUs. These systems also report accuraciesof between 99.5% and 99.9% and have a life expectancy of between five (5) and ten(10) years. However, microwave/RF systems tend to suffer from interference problems (this is less true for microwave systems using circular polarization and forsystems with externally powered IVUs), and systems using inductive loops tend to besensitive to dirt, snow and ice on the road. SAW systems tend to be particularlysusceptible to noise because the echo signal is especially weak.
Capabilities
Just as different systems have different performance characteristics, they also havedifferent capabilities. We think it is important to differentiate systems based on thedirectionality and throughput of the transmission, the capacity of the IVU, the memoryaddressing scheme used, the programmability of the IVU, the security of the system,
, the portability of the IVU, and the multilane capabilities of the system ([Evans, 1990]contains a slightly different list). Each is considered more fully below.
In general, reflective systems (be they optical, RF, or microwave) offer only oneway communications (i.e., from the IVU to the reader). All other microwave/RFsystems offer the possibility of both one-way and two-way communication (be theyinternally or externally powered). The throughput of the different systems implemented to date varies a great deal.
The capacity of the: IVU can vary considerably as can the addressing scheme used.Current systems have a memory capacity ranging from 1 bit to over 64K bits. Bothsequential and random access memory (RAM) devices have been used, the formerbeing less powerful but also less costly.
Different communications and memory capabilities can be combined to yield different levels of programmability. Most systems can be either: programmed only bythe manufacturer (e.g., SAW systems), programmed once using special equipment(so-called write once, ready many or WORM systems), programmed many timesusing special equipment, or programmed by the reader (so-called read/write systems). In general, increasing the programmability of the system increases its flexibility but reduces its security. However, it may be possible to increase the security ofprogrammable systems using public key cryptographic techniques [Arazi, 1991].
These capabilities are now often used together to distinguish between three different types of systems. Type 1 systems can only transmit in one direction, can onlytransmit fixed information, and can only be programmed by the manufacturer. Type2 systems can transmit in both directions, can transmit some variable informationand can be programmed from the reader. Type 3 systems have all the features of Type
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2 systems and can, in addition, be reprogrammed using an on-board computer that islinked to or part of the IVU [Hill and Emmott, 1990].
Systems also differ in the degree to which they are portable. Systems that aresensitive to IVU location and orientation are, in general, less portable. In addition,the larger the IVU is the less portable it becomes. It is important to point out,however, that in many cases portability is sacrificed by design. Particularly, in manyapplications it is important to identify the vehicle and not the driver; hence the IVUis designed to be (more or less permanently) affixed to the vehicle"
Finally, systems differ in their ability to work across multiple lanes. Most AVIsystems were designed for single lane operation and, as a result, do not work wellacross multiple lanes. There are, however, exceptions. Systems have been implementedthat are able to use a single reader/antenna for multiple lanes. In addition, systemshave been implemented that use different readers/antennas for different lanes.
MAKING USE OF AVI
The functional capabilities of AVI are quite far-reaching. While the most talkedabout application is electronic tollirevenue collection, AVI can also be used for accesscontrol, surveillance, and fleet control. Each of these areas is discussed brieflybelow.
Electronic TolllRevenue Collection
The first toll road in the United States was the Lancaster Turnpike, constructed in1774. Since that time, tolls have been collected on a variety of roads, bridges andtunnels for a variety of different purposes, most notably to generate revenue forconstruction and maintenance (including resurfacing, restoration, rehabilitation, andreconstruction). Not surprisingly, a variety of different approaches to toll collectionhave been used since 1774. Some facilities are closed (i.e., all access and egress pointsare monitored), some are open (i.e., only main-line points are monitored), and someare partially closed. Further, some facilities charge in both directions while otherscharge in only one. In addition, the technology of toll collection has changed dramatically since 1774. Over the years we have seen the use of staffed cash-only tollstations, automated cash-and-token toll stations, pre-dated windscreen stickers, userdated or self-canceling stickers, and a variety of hybrid systems as well. AVI affordsseveral new possibilities (the legal and institutional aspects of which are discussed in[Gittings, 1987]), all of which are grouped under the heading electronic toll collection(which we will take to include other types of revenue collection such as parking fees,circuit and dwell-time charges at airports).
In general, electronic toll collection (ETC) systems can be classified as either animproved toll booth system, a non-stop toll booth system, or an at-speed collectionsystem. In the first, the toll is collected at a traditional-type station but the transaction is speeded by the use of ETC technology. Hence, each vehicle enters a toll boothor toll lane, comes to a complete stop, and then proceeds. In the second, the toll is
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AUTOMATIC VEHICLE IDENTIFICATION 197
collected at a traditional-type station but because ETC technology is being used thevehicle need not stop. In other words, the vehicle must enter a toll lane or toll boothbut need not stop to have the toll collected. In the final system, vehicles proceedthrough collection stations as if they were "normal" sections of the facility. That is,they need not enter special lanes, slow down, or take any action to have the tollcollected.
ETC systems can also be classified based on the payment policy. In general, thereare two different types of payment policies: credit-based and debit-based. In a creditsystem, facility use is recorded and the users of the facility pay at some future pointin time. In a debit system, users must pre-pay for the use of the facility and theirunexpended balance is reduced each time the facility is used. Both credit and debitsystems can be operated in a variety of ways. Credit systems can bill users on aperiodic basis (e.g., monthly) or transfer funds from a specified account electronically. Debit systems can be based on a device in each vehicle (e.g., an electronic"debit card" that can have its balance increased at a payment station---either aseparate facility or a full-service toll lane), a central facility-specific account (e.g.,each customer deposits money in an account that is administered by the facility),or general purpose savings account (e.g., funds are electronically transferredfrom the user's checking account). Of course, depending on the payment processused, the ETC system will either need to determine if a vehicle has a valid accountor billing number, if the account has sufficient funds, or if the on-board "debitcard" has sufficient funds. In the case where the IVU is connected to a "debit card"it is not really necessary to identify the vehicle unless the remaining balance isinsufficient.
Implementations One of the earliest large-scale ETC test programs was conductedin Hong Kong in the early 1980s. Each vehicle in the program was equipped with an(unpowered) electronic number plate (ENP) which was interrogated (and powered)using a multi-lane loop array buried beneath the road at specific toll stations. Driverswere billed for their road use on a monthly basis. The pilot program ran for eight (8)months between 1983 and 1985 and included approximately 2,500 vehicles (1,300government vehicles, 700 buses, and the remainder private cars) and 18 toll sites. Thesystem correctly identified more than 99% of fitted vehicles crossing a toll site, lessthan 1 in 10mil. identifications were erroneous, and collection stations had a meantime between failure of greater than six (6) months [Catling and Harbord, 1985].
ETC is now being used in a variety of different forms in a variety of differentplaces around the world. For example, ETC has been used on: the Lincoln Tunnel inNew York since 1986 (for buses); the Crescent City Connection Bridge in NewOrleans since 1989; the Dallas North Tollway in Texas since 1989; the Lake Pontchartrain Causeway in New Orleans since 1990; the ACESA Highway in Barcelona,Spain since 1990; the ESCOTA Highway in Antibes, France since 1990; theAutostrada in Italy Milan to Naples since 1990; the Oslo, Norway Toll Ringsince 1990; the Oklahoma Turnpike since 1991; and the E-470 in Denver since 1991.These systems have, thus far, been fairly well-received. Just to give some idea,approximately 33,000 IVUs have been issued for the North Dallas Tollway, 100,000IVUs have been issued for the Oklahoma Turnpike (accounting for 32% of total
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DAVID BERNSTEIN and AMMAR Y. KANAAN
daily traffic), 1,600 IVUs have been issued for E-470 (accounting for 43% of total daily traffic), and 18,000 IVUs have been issued for the Autostrada S.P.A. in Italy. These systems use a variety of different technologies.
Benefits There are many reasons for the interest in ETC. One of the most impor- tant is cost savings (to the toll facility). Traditional toll collection operations are generally quite labor intensive. Indeed, labor costs can account for as much as 80% of total collection expenses in ticket systems [Applied Economics, 19721, and toll collection costs ranged from 15-19% of total operating costs on the Pennsylvania Turnpike, New York State Thruway, and New Jersey Turnpike in 1985 (based on their Annual Reports). It is generally believed that ETC can signilicantly reduce these costs and increase the revenue percentage by reducing handling costs, increas- ing security, and reducing the number of violations, but it is important to realize that some additional costs may be incurred (e.g., the cost of monthly billing). In addition, pre-paid (i.e., debit) systems allow the toll authority to capture the float (i.e., earn additional interest on the pre-paid balances). The cost of installing ETC (per lane) is generally estimated at between 33% and 50% of the cost of a mechanical coin collec- tion system [Hensher, 19911.
Another important reason for the interest in ETC is time savings (for drivers). In general, it is believed that ETC will significantly reduce the queues at toll booths/ barriers by increasing the service rate of the system, even if the system does not make use of at-speed collection [Lin and Hoang, 19911. However, this assumes that the total demand for the system is constant and that the queues will not simply be shifted to a downstream bottleneck, and neither of these assumptions need necessar- ily hold. First, observe that any initial decrease in travel times is likely to make any given route more attractive relative to both other routes and other modes. Hence, ETC is likely to induce additional demand. Second, in some instances the queues at toll boothslbarriers perform a metering function that actually improves downstream traffic movements. It is also important to point out that ETC may result in addi- tional time being spent elsewhere, for example, at prepayment stations and reconcil- ing monthly statements. However, these time costs are unlikely to outweigh the (ini- tial) time savings from ETC because users are unlikely to prepay on a daily basis (hence the total number of people queuing per day will decrease), because there will probably be many more prepayment stations, and because statements are reconciled infrequently.
Also note that, even if drivers do not realize any time savings, the toll authority will see an increase in throughput, and this is often perceived as a benefit in and of itself. In addition, to the extent that ETC can reduce the time spent queuing, it can also reduce the emissions during queuing (and deceleration and acceleration) [Ardekanis and Torres, 19911, [Peseky and Marin, 19901, [Willis, 19901.
Finally, many accidents occur at toll stations because of the need to decelerate, accelerate, and change lanes [Brown, 19811, [Thompson and Vincent, 19861. It is generally believed that ETC can significantly reduce the number of accidents at toll stations and that this represents a substantial benefit. However, it is important to recognize that toll stations with multiple payment methods may result in increases in lane-changing and hence more accidents.
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AUTOMATIC VEHICLE IDENTIFICATION 199
,Creative Applications ETC also offers the opportunity to implement a variety of creative policies and programs. Given the above discussion of the time value of money and the reduction in collection costs, it is easy to see how the toll agency can benefit from a debit system. However, if the agency is willing to forego these benefits, it can make ETC more attractive to users by offering discount tolls. Indeed, this practice has been widely used to attract drivers to ETC (for a general discussion of the initial demand for ETC see [Kanaan, 19921).
In addition, ETC offers the opportunity to implement differential pricing of many kinds, perhaps the most important of which is congestion pricing (though differential pricing can also be used for weight or damage based tolls [Newberry, 19881 or to increase toll revenues [Bernstein and Muller, 19931). The basic idea behind conges- tion pricing is quite straightforward, though often misunderstood. First, in the absence of tolls, the capacity at a bottleneck is allocated based on the queuing delays incurred. This results in a loss to society. However this loss can be recouped, at no cost to the driver, by imposing a time varying toll pickrey, 1963, 1967, 19681, [Arnott et a]., 19901. Second, in the absence of tolls, more people will drive than is socially optimal and they will overcrowd some routes because they are basing their decisions on their own perceived cost and not on the social marginal cost. The efficiency of the transportation system can thus be improved by imposing different uniform (i.e., time invariant) tolls on different links. Of course, in the absence of ETC congestion, pricing cannot really be implemented because the collection of the toll itself causes delays. ETC, on the other hand, offers the opportunity of collect- ing tolls without resulting in additional delays. Hence, ETC enables congestion pricing.
Finally, it is worth pointing out that ETC also makes it relatively easy to issue unrestricted travel passes (much like those that are issued by many commuter rail lines). Unfortunately, the impacts of these types of passes are not well under- stood.
Access Control
There are a variety of situations in which it is necessary to control access to a transportation facility. In almost all of these cases, AVI can be used to streamline the process.
One of the most notable applications of AVI in access control is in airport ground operations. Many major airports have a significant problem managing commer- cial vehicles (e.g., buses, limousines, taxis). In particular, they need to control which vehicles are allowed where and they need to restrict access to uninsured vehicles and unlicensed vehicles. For example, AVI can be used to allow taxis access only to specific taxi pools and it can be used to prevent unauthorized operators from enter- ing the airport.
The other big application of AVI to access control is heavy vehicle control. Such systems combine weigh-in-motion equipment with AVI to automatically weigh vehi- cles, identify overweight vehicles, and control their access.
Though these are the two biggest applications, access control is and can be used in
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200 DAVID BERNSTEIN and AMMAR Y. KANAAN
other circumstances as well. For example, during construction and maintenance, particular construction vehicles often have access to particular facilities. This can be easily implemented using AVI. As another example, emergency vehicles (e.g., police, ambulance) often have access to special facilities (U-turn facilities, ramps) and AVI can be used to automatically provide access to these vehicles and deny access to others.
Implementations Airport ground access control systems are currently in place at a variety of locations including the Metropolitan Airport Commission in Minneapolis- St. Paul, the Orlando International Airport, and the San Francisco International Airport [Covil et al., 19871, [Marmorstein, 19911.
Heavy vehicle access control has also been implemented at a variety of different locations. For example, as part of the Oregon weigh-in-motion project, AVI technol- ogy is being used on a 310 mile stretch of 1-5 in Oregon [Henion and Koos, 19871, the Heavy Vehicle Electronic License Plate (HELP) program [Davies et al., 1989b1, [Hill and Emmott (1990)l is using AVI, and the 1-40 system in West Memphis, Arkansas uses an AVI system for heavy vehicles [Wrobel and Langston, 19901.
Benefits There are several advantages of using AVI for airport ground a,ccess con- trol. First, it tends to reduce ground congestion by limiting access when the airport is overcrowded. Second, AVI seems to lead to a more equitable assignment of taxis to trips. Third, it reduces the level of voice trallic in the radio network. Finally, by providing more efficient control, it reduces the need for additional staff during the peak period.
There are also several advantages of using AVI for heavy vehicle control, particu- larly when combined with weigh-in-motion technology. First, and most importantly, it significantly reduces the time spent at weigh stations, which improves freight trans- port generally (i.e., reduces travel times, increases reliability, increases driver satis- faction). Second, it reduces the cost of operating weigh stations. Finally, it reduces the number of overweight vehicles on the highway network and, as a result, reduces the amount of damage done to roads.
Creative Applications Of course, access control can be implemented without AVI technology. However, AVI makes it possible to design very flexible variable access control strategies. For example, upon entering the airport grounds a taxi may be assigned to a specific pool (i.e., the pool they can enter changes each time they enter the airport). An AVI system can easily record this information and control access. Such a system could also be extended to include time requirements (e.g., minimum and maximum stay requirements) that are difficult to monitor without AVI.
Surveillance
AVI can be an important component of an integrated highway surveillance system. In particular, observe that the majority of sensors (i.e., traditional inductive loops, fiber-optic pressure sensors, ultrasonic detectors, and radar detectors) are merely
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presence detectors. As such, they can only be used to count vehicles at a particular point and determine their (instantaneous) velocity at that point. More sophisticated sensors (i.e., processed videolmachine vision) can also be used to calculate densities over a section of road [Michalopouloq 19911, [Cypers et a]., 19901. AVI systems can be used to augment these other technologies in that AVI can be used to monitor point-to-point travel limes.
It is also important to note that AVI can be used for surveillance at other types of transportation facilities and other modes as well. For example, some airports are using AVI to monitor schedule adherence for shuttle buses. As another example, these types of systems are being used to track transit vehicles (as they pass pre-specified readers) in order to predict travel times and control the system in real-time.
Benefifs Point-to-point data can be very useful in a great many situations. In partic- ular, these data can improve traffic prediction and thereby improve the performance of advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS). In addition, they can be used directly in automated incident detec- tion (AID) [Hallenbeck, 19921. Rather than attempting to infer point-to-point travel times from other data [Liu and Sen, 19921, these data can be measured directly. The measured point-to-point travel times can also be used to estimate space mean speeds using, for example, filtering techniques.
implementations The concept of using a "vehicle as a probe" is currently being tested as part of the Pathfinder project in Los Angeles, the TRAVTEK project in Orlando, and the ADVANCE project in Chicago. It is too soon to comment on the success or failure of these efforts.
Fleet Control
When we discussed the surveillance applications of AVI, we alluded to ways in which the information collected can be used in real time, to manage traffic and vehicle fleets (e.g., commercial vehicles, transit vehicles). However, it is important to also recognize that AVI can be used to control a fleet of vehicles in other ways as well. In fact, as we mentioned in the introduction, the first application of AVI tech- nology was to fleet control in the railroad industry. These same types of ideas can be applied to highway vehicle fleets as well. AVI can be used to identify vehicles when they enter and exit garages, when they are repaired, when they are fueled, etc.. As another example, AVI can be used to monitor the locations of construction vehicles (during construction and maintenance projects) and hence can be used to manage the fleet of vehicles more efficiently.
Benefits AVI can significantly reduce the cost of collecting data about the vehicle fleet. These data can then be used to improve operations in a variety of different ways including preemptive. maintenance and vehicle allocation (i.e., the allocation of vehicles in a garage to drivers).
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202 DAVID BERNSTEIN and AMMAR Y. KANAAN
Implementations The MBTA (in eastern Massachusetts) provides a good example of this type of application of AVI. They are using AVI technology to control their automobile and truck fleet and will (shortly) be using this technology to control their bus fleet as well. Vehicles are automatically checked into and out of garages, and AVI is used (in conjunction with vehicle performance monitoring equipment) to automat- ically obtain data on fuel consumption, miles driven, etc.
CONCLUSION
Though it has had some trouble getting off the ground, it is clear that automatic vehicle identification is here to stay. The technology works and it is starting to be accepted both by transportation agencies and the public. It thus seems certain that AVI will play a major role in integrated intelligent vehicle highway systems. Nonethe- less, a great deal of work still remains.
First, the technology itself still has room for improvement. There is still room to increase the accuracy of the existing systems, to increase the durability of the sys- tems, to reduce the cost of both the readers and the IVUs, and to improve the operation of the systems across multiple lanes of traflic. All of these improvements will result in increased usage.
In addition, more work needs to be done to understand the potential uses of AVI technology within the context of integrated IVHS, and the impacts of these different applications. For example, more work needs to be done to fully understand: the impacts of differential pricing programs on the route and departure-time choices of commuters on general networks [Bernstein et al., 19921, [Friesz et a]., 19931, the use of AVI in traflic prediction (and hence in providing information, conducting traffic management, and detecting incidents), the ways in which AVI can improve manage- ment and operations of vehicle fleets, and methods of performing the metering function that many people believe is now performed by existing toll collection systems.
Perhaps most importantly, however, we need to consider the question of standard- ization. In the 1970s, it was argued that the costs of standardization far outweighed the benefits [Hauslen, 19771. At the time, it seemed appropriate to use different technologies for different purposes because it avoided "overkill" (i.e., a system that is too powerful for its intended purpose). However, it seems that we must address this issue again, in light of integrated IVHS. For one thing, there appear to be economies of scale associated with standardization, particularly in the management of tollways [Hensher, 19911. In addition, the increasingly regional and inter-regional nature of both private and commercial travel almost requires standardization-people will probably be unwilling to have more than one IVU (for a variety of different reasons) and different systems are likely to interfere with each other in unexpected ways. Thus, we must applaud the efforts towards standardization being made by the group of agencies in the New York-New Jersey-Pennsylvania region and the New England ETTM Group. We hope such efforts will continue, and that the move towards national standards will succeed.
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ACKNOWLEDGMENTS
This research was sponsored, in part, by a grant from the Mitsui Corporation. The authors would like to thank an anonymous referee for helpful comments on an earlier draft of this paper.
REFERENCES
Applied Economics, "An Economic Evaluation of Toll Financing for Highways," International Bank for Reconst~ction and Development (The World Bank), Washington, 1972.
Arazi, B., "Vehicular Implementation of Public Key Cryptographic Techniques," IEEE Transactions on Vehicular Technology, 40, 646-653, 1991.
Ardekanis, S. and Torres, F., "Economic Evaluation of Toll Plaza Operations," presented at the Annual Meetings of the Transportation Research Board, 1991.
Arnott, R., de Palma, A. and Lindsey. R., "Economics of a Bottleneck," Journal of Urban Economics,27, 1 1 1-130, 1990.
Bergan, A.T., et al., "Electronic License Plate Technology: Automatic Vehicle Location and Identifica- tion," ITE Compendium of Technical Papers, 372-377, 1988.
Bernstein, D., el al.. "Solving a Variational Inequality Formulation of the Simultaneous Route and Depar- ture-Time Choice Equilibrium Problem," presented at the Regional Science Association North Ameri- can Meetings, 1992.
Bernstein. D. and Muller, J., "The Competing Short-Run Objectives of Peak Period Road Pricing," pre- sented at the Annual Meetings of the Transportation Research Board, 1993.
Blythe, P.T., et al., "A Short-Range Road to Vehicle Microwave Communications Link for Automatic Debiting and Other RTI Services," Proceedings of the DRIVE Conference, 1, 248-268, 1991.
Brown, R., "A Method for Determining the Accident Potential of an Intersection," Traffic Engineering and Control, 1981.
Calling, I. and Harbord, B.J., "Electronic Road Pricing in Hong Kong: The Technology," Traffic Engi- neering and Control, 26, 608-617, 1985.
Center for Urban Transportation Research, "Analysis of Automatic Vehicle Identification Technology and its Potential Application on the Florida Turnpike," University of South Florida Technical Report, 1990.
Constant, J.N., "Microwave Automatic Vehicle ldentification (MAVI) System," Proceedings of the 23rd IEEE Vehicular Technology Conference, 23-63, 1972.
Covil, J.L., Cooney, T.A. and Marlin, PC.. "New Uses of Automatic Vehicle Identification Systems in Highway Transportation," ITE Compendium of Technical Papers, 209-213, 1987.
Cypers, et al., "CCATS: The Image Processing-Based Traffic Sensor," Traffic Engineering and Control, 371-378, 1990.
Davies P., Hill, C. and Emmott, N., "Automatic Vehicle ldentification to Support Driver lnformation Systems" Proceedings of the 1st IEEE Vehicle Navigation and Information Systems Conference, A31- A35, I989a.
Davies, P., el al., "The Heavy Vehicle Electronic License Plate (HELP) Programme," Proceedings of the 20th International Symposium on Automotive Technology and Automation, 2, 1164-1 173, 1989b.
Davies, P., Sommerville, F. and Ayland, N., "Automated Toll Collection in Virginia," Proceedings of the 20th International Symposium on Automotive Technology and Automation, 2, 1305-1315. 1989c.
Evans S.M., "Radio Frequency ldentification Systems: Industry and Applications Overview," presented at the IBTTA International Symposium on AVI Technology for Toll Collection, 1990.
Foote, R.S., "Automatic Vehicle Identification: Tests and Applications in the Late 1970'$" IEEE Transac- tions on Vehicular Technology, VT-29,226-229, 1980.
Foote, R.S., "Prospects for Non-Stop Toll Collection Using Automatic Vehicle Identification." Traffic Quarterly, 35,445460, 1981. -
-
Friesz, T.L., el al., "A Variational Inequality Formulation of the Dynamic Network User Equilibrium Problem." O~erations Research. 41, 1993.
Gittings, G.,' ''some Financial, ~co'nomic, and Social Policy Issues Associated with Toll Finance," Trans- portation Research Record, 1107, 20-30, 1987.
Gravelle. K. and Walker, C., "Technical Requirements for EKective Applications of Automatic Vehicle ldentification (AVI) Technology to Highway Systems," 1990.
Dow
nloa
ded
by [
Que
ensl
and
Uni
vers
ity o
f T
echn
olog
y] a
t 06:
29 1
3 O
ctob
er 2
014
204 DAVID BERNSTEIN and AMMAR Y. KANAAN
Hallenbeck, M., "Use of Automatic Vehicle ldentification Techniques for Measuring Traffic Performance and Performing Incident Detection," Draft Final Report for the Washington State Transportation Commission. 1992.
Hauslen, R.A., "The Promise of Automatic Vehicle Identification," IEEE Transactions on Vehicular Technology, VT-26. 30-38, 1977.
Henion, L. and Koos, B., "Technology and the Heavy-Vehicle Electronic License Plate Program: Potential Use for Government and Industry," Transportation Research Record, 1107, 46-50, 1987.
Hensher, D.A., "Electronic Toll Collection," Transportation Research, 25A, 9-16, 1991. Hill, C. and Emmott, N., "Research and Development of Automated Vehicle Identification for the Cres-
cent Demonstration Project," Proceedings of the 22nd International Symposium on Automotive Tech- nology and Automation, 1, 303-310, 1990.
Hills, P.J. and Blythe, P.T., "A System for the Non-Stop Automatic Debiting of Vehicles," Proceedings of the 22nd International Symposium on Automotive Technology and Automation, 1, 287-294. 1990.
Kanaan. A,, "An Economic/Financial Analysis of Implementing Electronic Toll Collection and TratTic Management Systems," M.S.T. Thesis, Massachusetts Institute of Technology, 1992.
Kanayama, K., el al., "Development of Vehicle-License Number Recognition System Using Real-Time lmage Processing and its Application to Travel Time Measurement," Proceedings of the 41st IEEE Vehicular Technology Conference, 798-804, 1991.
Larsen, O.I., "The Toll Ring in Bergen, Norway-The First Year of Operation," Traffic Engineering and Control, 29, 216-222, 1988.
Lin, J. and Hoang. L.T., "Tollsim: A Simulation Model for the Evaluation of ETTM Systems in Florida," ITE Compendium of Technical Papers, 351-355, 1991.
Liu, N. and Sen, A,, "Time Series Analysis of Expressway Traffic Data and Its Implications for Dynamic Route Guidance Systems," presented at the Regional Science Association North American Meetings, 1992.
Martin. B. and Scott, P., "Automatic Vehicle Identification: A Test of Theories of Technology," Science, Technology, and Human Values, 17,485-505, 1992.
Marmorstein. L., "The Development of Strategies for Using Transponder Technology in Advanced Traffic Management Systems," M.S.T. Thesis, Massachusetts Institute of Technology, 1991.
Michalopoulos, P.G., "Incident Detection Through Video lmage Processing," Proceedings of the Confer- ence on Applications of Advanced Technologies in Transportation Engineering, 11 1-1 15, 1991.
Morgan, D.P., "Surface-Wave Devices for Signal Processing," Elsevier Science Publishing, Amsterdam, 19x5
Newberry, D., "Road Damage Externalities and Road User Charges," Econometrica, 56, 295-316, 1988. Peseky, L. and Marin, A,, "An Evaluation of the Effects of Automatic Vehicle ldentification on Air
Quality Emissions at a Toll Plaza." presented at The IBTTA International Symposium on AVI Tech- nology for Toll Collection, 1990.
Reitz, D.J., "Automatic Vehicle ldentification Technology and Applications," Proceedings of the 35th IEEE Vehicular Technology Conference, 285-291, 1985.
Sommerville. F., "Applications of Automatic Vehicle Identification Technology," Transport Reviews, I I, 173-191, 1991.
Thompson, R.G. and Vincent, E.N., "Assessing the Traffic and Economic Benefits of the West Gate Bridge Toll Removal," Proceedings of the Australian Road Research Board Conference, 14, 1986.
Thompson, T.. "Road Use Charging-The Current State of Technology," Traffic Engineering and Con- trol, 31, 526-532, 1990.
Vickrey, W., "Congestion Charges and Welfare," Journal of Transport Economics and Policy, 2, 107-1 18, 1968.
Vickrey, W., "Optimization of Trallic and Facilities," Journal of Transport Economics and Policy, 1, 123- 136, 1967.
Vickrey, W., "Pricing in Urban and Suburban Transport," American Economic Review, 53,452465. 1963. Walker, C.M. and Brockelsby, W.K., "Automatic Vehicle ldentification (AVI) Technology Design Consid-
erations for Highway Applications," Proceedings of the 41st IEEE Vehicular Technology Conference, 805-811, 1991.
Willis, D.K., "IVHS Technologies, Promising Palliatives or Popular Poppycock," Transportation Quarterly, 44, 1990.
Wrobel, J.A. and Langston, M.C., "Automatic Vehicle ldentification at Weigh Stations Using Bar Code Readers," presented at the IBTTA International Symposium on AVI Technology for Toll Collection, 1oon .,,".
Yim, Y., "Consumer Responses to Advanced Automotive Electronics: ETC System-User Survey," Pre- sented at The Annual TRB Meeting, Washington, D.C., 1992.
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Que
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y] a
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