Driver Information

The most recent applications sought to complement the driver’s ability by targeting such “hands-off, feet-off” driving systems (Fig. 1) as PATH (Partners for Advanced Transit and Highways) and PROMETHEUS (Program for European Traffic with Highest Efficiency and Unprecedented Safety).

For transportation, IT generally can be classified into four groups: Driver Information and Route Guidance, Traffic Flow and Parking Control, Public Transport and Fleet Management, and Automatic Debiting. Only the first item will be discussed in this article.

Driver Information and Route Guidance

Driver Information (DI) and Route Guidance (RG) systems help drivers navigate unfamiliar roads or find the quickest route. The information, especially that given by more advanced systems, consists of advice that drivers can accept or ignore, or a directive with which they are expected to comply. DI and RG can help them reduce or curtail poor route choice as well as excess distance and travel times. The most likely information requested is shortest recommended path, state of the road and weather conditions, unexpected incidents ahead, and the general traffic situation (to estimate travel time).

Disseminating Information

Roadside displays, consisting of fixed road signs and variable message signs, are the simplest DI systems (Fig. 2). The relevant technology is quite basic, as the goal is to give all drivers general information about existing roadway conditions. Variable message signs are used mainly on highways. In urban areas, they are particularly well-suited for providing information about roadway conditions and parking lot availability.

The second method, cellular-radio networks such as the Radio Data System-Traffic Message Channel (RDS-TMC) proposed by the European Broadcasting Union, enable digital information to be superimposed on normal VHF/FM broadcasts. Information can be filtered (drivers call up only what they need and when they need it), updated any time, and broadcast in different languages.

Also, there is no need to lay cables, as is the case with beacon-based RG techniques.

The third (and most sophisticated) method is the electronic RG system, which consists of in-vehicle units, roadside equipment, and control centers (Fig. 3 ). It is usually difficult to start installing the ground infrastructure before ensuring the wide use of onboard systems. Onboard equipment for dynamic navigation comprises a transceiver, a router with a display, a locator with sensors, dead-reckoning devices, and a map memory. The usual indicators of route selection criterion are shorter distance, minimum cost, less traffic, fewer stops, and greater safety. The result of route optimization is the recommendation of how to reach a destination from a given starting point. This can be done by calculating the optimum route for an origin-destination, and by determining the turning directions from the vehicle’s route and position.

Some Examples in Use

CARIN (CAR Information and Navigation System) is an autonomous (static) navigation system used in route planning and guidance. A simplified digital map, stored on a CD, shows the best route. It also offers verbal guidance via a speech synthesizer and gives general tourist information. Other in-vehicle equipment consists of a sensor (magnetic compass) and a navigation computer that carries out the main task. Data collection, in terms of positioning and directing, is implemented by the moving vehicle’s sensors. This information, updated every 3 seconds, is used for map-matching.

The system’s basic advantage is that it does not rely on any external sources, like expensive beacon infrastructures. The route planner algorithm determines the best route for minimizing travel time and distance. However, as CARIN cannot receive current network and traffic situation reports, it is being modernized so that it can receive external information via the car radio with the introduction of RDS-TMC. Moreover, in the future CARIN will offer a fully interactive traffic management opportunity using the European D-net telephone system.

TrafficMaster was one of the first in-vehicle information systems introduced. It was applied first to the M25 London orbital highway, and then to the whole UK highway network. Data is obtained through sensors installed on highway bridges. In case of congestion, messages (such as locations and types of traffic jams and average traffic speed) are generated and transmitted by the control center. The in-vehicle unit displays the current status of the roadway network covered by the sensors. This dissemination is performed minute-by-minute. enabling the driver to make convenient route choices.

In Euro-Scout, the driver enters a destination into a small in-vehicle computer. As the vehicle moves, the in-vehicle navigation equipment determines its position. Whenever it passes a beacon, the user receives the best route, generated by the central computer, for all destinations.

Communication is performed through a two-way infrared link. Beacons located next to the signal heads can use existing cables when they are mounted with traffic lights. Guided vehicles can measure link travel times, which are then returned to the central computer via the beacons in a so-called vehicle telegram. This information is updated continually by the center. The system, therefore, is characterized by its centralized feature: The main data process is carried out in the control office rather than in-vehicle units.

The system has been introduced in Stuttgart by installing 130 beacon heads on traffic lights. A second system of 340 beacons is located in Berlin, and a third one is in Oakland county, Michigan, with 100 beacons and 1,000 equipped vehicles. Start-up costs are high, but in-vehicle equipment costs and the cost of increasing users are low.

In comparison, SOCRATES’ start-up costs are much lower, while the costs of equipping each vehicle and adding additional users are high. This system does have some weak points, though:

The routing algorithm does not take multi-destination users into account, the system is heavily dependent of roadside infrastructure, and a breakdown in the center may cause a system-wide failure.

SOCRATES (System Of Cellular RAdio for Traffic Efficiency and Safety), a two-way communication system, is based on the Global System for Mobile Communications (GSM) cellular radio network. SOCRATES measures the travel times of all guided vehicles from point to point, and uses this information to determine the best routes. In-vehicle units, an odometer, a compass for dead reckoning, and a map pass information to and from roadside units, which are connected to the central computer over telephone lines that allow medium-range communication.

The downlink from the base station to the vehicle is operated in a broadcast mode for disseminating traffic information. The uplink to the base station allows multiple access by floating cars in order to collect travel time patterns. The system’s main disadvantage is the cost of using the mobile phone network. However, a significant benefit is that using the cellular radio requires no additional infrastructure investment because of the introduction of GSM.

The Need for Such Systems

Transport enables socioeconomic relationships to be developed and sustained. This is clear in the continuous dependence on various means of transport to move goods and people. Neglecting transport would bring society to standstill, literally and metaphorically. The introduction of the car put personal transport on the top and increased the need for more roads. The greater the demand for individual mobility, and hence roads, the more complex road transport problems become.

The number of cars per mile of road grows daily. At the same time, lack of space, budgetary priorities, and environmental considerations restrict the extent to which new road construction and increased capacity can be undertaken. But people still want to travel as smoothly as possible.

Therefore, the central idea is that traffic information and communication systems will offer effective solutions-especially where physical changes to the existing infrastructure, such as constructing new links or widening roads, are almost impossible. Closer following distances between intelligent vehicles on automated highways will eventually increase road network capacity.

The Advantages of RG Systems

The main appeal of dynamic RC systems is their ability to recommend paths based on current traffic conditions. Recent research and systems development have focused mainly on dynamic RC systems, which are superior to static systems. Dynamic RC is particularly well-suited for tackling urban congestion, and has advantages over other technological measures, such as vehicle-actuated traffic signals or a system of dynamically updated VMS.

Drivers normally reach their destination by following a route based on previous experience, maps, street signs, and radio traffic bulletins. However, studies show that drivers are unable to select the shortest route, leading to some 6 to 8 percent errors. Preventing this by even static RG could save millions of dollars per year. Driver misperceptions, due to the absence or scanty amount of information about travel time and alternative routes, as well as about specific route incidents, lead to delay and wasted mileage. In Orlando, tourists driving RC-equipped vehicles made 30 percent fewer wrong turns and shortened their travel times by 20 percent, compared to drivers who used paper maps.

Research indicates that applying dynamic RG systems shows great potential for improving travel times, safety, and environmental effects. This is based on the assumption that more drivers will opt to use the services. Other benefits could include satisfaction derived from choosing the best route and being better informed, reduction in the total distance travelled, and incident detection and warning. The real benefit will depend largely on the quality of information provided. With more computing power becoming available and increased technological advancement, more high-quality information is available to drivers.

RG not only guides vehicles through unfamiliar areas, but also increases roadway safety. For example, research indicates that 60 percent of crashes at intersections, and about 30 percent of head-on collisions, could be avoided if drivers had an additional half-second to react. Systems like automatic collision notification (not readily available yet) immediately signal for help if a vehicle’s airbag deploys. In addition, drowsy-driver warning systems keep drivers from falling asleep at the wheel.

The Shape of Things To Come

The discussion so far has focused on the present state of intelligent transport systems. In-vehicle information systems provide information on road conditions and offer advice. They also can provide information about a city’s hotels, catering, theater, cinemas, and even the entire yellow pages. In-vehicle systems can function as hand-held car locators, whether in a busy parking lot or in the remote countryside.

The future of such systems already is taking shape. Dual-purpose and hand-held in-vehicle systems can be used as personal security guards that send a discrete message to a control center when a user is in danger. They could sound an alarm to scare off potential attackers and draw attention to oneself. They also could be built into a car’s security system to prevent theft and send messages in case of an accident.

Hands-free cars are being developed to navigate the road network by the use of a button relying on in-built computers. In addition, car prototypes are being developed that do not require roads-they will fly from origin to destination. All of these require intelligent navigation through a combination of computing and communication. The merging of computing and communication is the bedrock of a revolution to unify all technologies. Journeying intelligently will be at the forefront of this revolution.

Conclusion

Applying these systems, both vehicle- or network-based, depend heavily on the society’s living standards and the country’s economic level of development. Variable message signs and TMCs are the most convenient systems for developing countries, due to their simplicity and cheapness. A typical variable message sign only costs about $200,000, while more sophisticated systems requiring computer centers, roadside equipment like beacons and in-vehicle units, are more expensive. However, in cities with high traffic levels, authorities may consider establishing electronic navigation and information systems with the cooperation of private investors and vehicle manufacturers.

People tomorrow will be more mobile than ever. To provide better transportation systems for the twenty-first century requires the integration of people, vehicles, and network, as well as the improved safety and efficiency of transport systems. Therefore, dynamic DI systems should be able to offer improved mobility for travelers, reduced travel times and operation costs, reduced transportation infrastructure costs, improved highway safety, and reduced transportation energy consumption, transport-generated pollution, and noise.

References

• Barco Visual Systems. Traffic Technology International ‘98 (Feb/ March 1998): 18.
• Benz, D. “PROMETHEUS.” High Tech Report (April 1994).
• Catling, I. “SOCRATES.” Advanced Technology for Road Transport: IVHS and ATT. Ed. I. Catling. Boston: Artech House, 1994, 65-78.
• Georg, L. and F. Steinkohl. “Driver Assistance Concepts and Systems.” Traffic Technology International ‘98 (Oct-Nov. 1997): 66
• Hypower Inc. Traffic Technology International December ‘97 – January ‘98 (1997): 10.
• Intellimotion. Research Updates in Intelligent Transportation Systems. 6(4), (1997): 1.
• Jeffery, D. “Route Guidance and In-Vehicle Information Systems.” Information Technology Applications in Transport. Eds. P. Bonsall and M. C. H. Bell. Utrecht, The Netherlands, 1986, 319-51.
• Kontron Elektronik. Traffic Technology International ‘98 (Annual Review 1998): 232.
• Little, C. “The Intelligent Vehicle Initiative.” Public Roads (Sept.- Oct. 1997): 18-25.
• Siemens. The Power of Integration; Traffic Management; Driver Information. France: Siemens Automotive S.A., 1994.

The word ‘robot’ was first used in the 1922 play R.U.R. by the Czech playwright Karel Capek: the title is an acronym for Rossum’s Universal Robots which become so sophisticated that they take over the world. ‘Robot’ is compounded from the Czech words ‘robota’ or work, and ‘robotnik’ or serf (Capek. 1923).

The use of industrial robots, first clearly identified in the 1960s, along with computer aided design (CAD) and computed aided manufacturing (CAM) systems, characterizes the latest trends in the automation of the manufacturing process (Roth, 1983). These technologies arc leading industrial automation through another transition, the scope of which is still unknown.

Growth of the robotics market has slowed compared to the early 1980s. The use of industrial robots is at present concentrated in rather simple, repetitive tasks which do not to require high precision. However, manufacturing market analysis predicts that early next century industrial robots will become increasingly viable in applications which require more precision and sensory sophistication such as assembly tasks. The automotive industry, where robots have been economically justified since the 1970s, will continue to be the leading user. However, the major growth of the US robot population will occur in non-automotive industries.

2. Robot classes and characteristics

Robots can be classified in many ways. To establish a generic classification system, we shall refer to dimensions or degrees of freedom or DOF.

The DOF of a mechanical system refers to the number of physical axes through which motion can occur. In robotics, DOF can often be equated with the number of joints in the robot.

Typical present-day industrial robots have from one to six-DOF, although more are certainly possible. For example, a wrist can be made more flexible by adding rotation to the twisting already in that joint. Similarly, a fourth DOF can be added to the shoulder, where the arm joins the base to allow additional rotation of the arm. Industrial robots are also classified by the mechanical configuration of the individual elements of the arm and actuators. Theses classifications are: rectangular class (X,Y,Z): cylindrical class (R,?,Z): spherical class (R,?,?); and jointed class (?1,?1,?). This classification begins with simple movements in a rectangular co-ordinate system such as the x-y co-ordinate system.

3. World’s robot population

More than 610.000 industrial robots are now at work according to a new annual publication by the secretariat of the United Nations Economic Commission for Europe (UN/ECE) and the International Federation of Robotics (IFR).

The world’s robot population grew by about 6% in 1993 compared with 8% the year before. These growth rates fall significantly short of those of 16-23% recorded in the booming late 1980s and early 1990s. However, in view of the deep recession which commenced at the end of 1990 in robot-using countries and resulted in large reductions in investment and industrial employment, growth in the robot stock of 6%-8% is still quite impressive. 

Japan accounts for more than half of the world robot stock. However, the net increase in Japanese robot stock fell sharply in both 1992 and 1993. In 1993, the net increase in the robot stock was only about a third of the record year 1990, underscoring the depth of the Japanese recession.

With 325 robots for every 10.000 persons employed in manufacturing, Japan has by far the world’s highest robot density followed by Singapore with 109, Sweden with 73, Italy with 70 and Germany with 62. As a result of falling employment in the manufacturing industry in 1992-1993, robot density increased rapidly in many countries even though the robot stock increased only modestly.

In most countries, welding is the predominant application area for robots, particularly for major motor vehicle producing countries, accounting for more than 20% of the total robot stock. In a few countries machining was the largest application area. Assembly was the largest application area in Japan, accounting for 40% of the total stock of robots. It is worth noting that in Japan assembly accounted for 50% of the net increase in stock while welding only had a share of 9%.After a solid recovery in 1994, the robot market is forecast to boom in the period up to 1998. Based on macroeconomics forecast of the development of world economics the UN/ECE and IFR forecast that the world stock of industrial robots will increase from some 610,000 units at the end of 1993 to over 830.000 units at the end of 1997. As the number of personnel employed in industry is falling, the density of robots measured as the number of robots per 10.000 workers will continue to surge. In terms of units, shipments are estimated to increase from about 54.000 units in 1993 to over 103,000 units in 1997.

While the robot market was expected to be somewhat hesitant in Japan in 1994 and 1995, it was expected to boom in the United States, Western Europe and the dynamic Asian economies. If growth and world trade gain momentum as predicted from 1995, the prospects for the robotics business seem extremely bright.

The potential for expansion of robotics is enormous. If other industrialized countries were to approach the robot densities of Japan and if industry in general were to reach only half the robot density of the motor vehicle sector, the robot stock would increase manifold, and this is not counting the potential for robots in the service industries. The following example gives an illustration of the potential: if industry in France and the United Kingdom were to achieve a robot density half that of the motor vehicle industry in those countries, the robot stock would more than double; if it reached half the density of the Japanese motor vehicle industry, the robot stock in those countries would increase more than 20 times.

4. Summary

The emphasis in this article has been on industrial robots and techniques currently used in that environment. The future of robotics depends on improvements in many technologies to reduce cost and increase the range of performance so that robots become effective in more environments. These technologies include motors, actuators, contact sensors, non contact sensors, mechanisms, lubrication, electronics, computers and artificial intelligence.

References 

• CAPEK. K. (1923) R.U.R.. Samuel French. London.
• ROTH. B. (1983) Principles of Automation, in Future Directions in Manufacturing Technology, based on the Unilever Research and Engineering Division Symposium held at Port Sunlight, April 1983. Unilever Research. UK