Automobile congestion in major
cities has become unacceptable, and advanced traffic management systems are
being built in many of these cities to measure traffic flow at intersections
(by some combination of magnetic loop detectors, optical sensors, and other
means), and regulate stoplights and message signs. These systems can also issue
advisories of accidents ahead by means of variable message signs or radio, and
give advice of alternative routings. In emergencies they can dispatch fire,
police, ambulances, or tow trucks, and in the case of tunnels can shut down
entering traffic completely if necessary. These systems are operated by a
combination of computers and humans from centralized control rooms. The
operators look at banks of video monitors which let them see the traffic flow
at different locations, and computer-graphic displays of maps, alarm windows,
and textual messages. The operators get advice from computer-based expert
systems, which suggest best responses based on measured inputs, and the
operator must decide whether to accept the computer’s advice, whether to seek further
information, and how to respond.
Smart Cruise Control
by
Eng.Ramy
Standard cruise control has a
major deficiency in that it knows nothing about vehicles ahead, and one can
easily collide with the rear end of another vehicle if not careful. In a smart
cruise control system a microwave or optical radar detects the presence of a
vehicle ahead and measures that distance. But there is a question of what to do
with this information. Just warn the driver with some visual or auditory alarm
(auditory is better because the driver does not have to be looking in the right
place)? Can a warning be too late to elicit braking, or surprise the driver so
that he brakes too suddenly and causes a rear-end accident to his own vehicle.
Should the computer automatically apply the brakes by some function of distance
to obstacle ahead, speed, and closing deceleration, If the computer did all the
braking would the driver become complacent and not pay attention, to the point
where a serious accident would occur if the radar failed to detect an obstacle,
say, a pedestrian or bicycle, or the computer failed to brake?
Should braking be some combination
of human and computer braking, and if so by what algorithm?
These are human factor questions
which are currently being researched.
It is interesting to note that
current developmental systems only decelerate and downshift, mostly because if
the vehicle manufacturers sell vehicles which claim to perform braking they
would be open to a new and worrisome area of litigation.
The same radar technology that can
warn the driver or help control the vehicle can also be applied to cars
overtaking from one side or the other. Another set of questions then arises as
to how and what to communicate to the driver and whether or not to trigger some
automatic control maneuver in certain cases.
Intelligent Highway Vehicles:Vehicle Guidance and Navigation Systems
by
Eng.Ramy
The combination of GPS (global
positioning system) satellites, high-density computer storage of map data,
electronic compass, synthetic speech synthesis, and computer-graphic displays
allows cars and trucks to know where they are located on the Earth to within
100 m or less, and can guide a driver to a programmed destination by a
combination of a map display and speech. Some human factor challenges are in
deciding how to configure the map (how much detail to present, whether to make
the map northup with a moving dot representing one’s own vehicle position or
current-heading-up and rapidly changing with every turn). The computer graphics
can also be used to show what turns to anticipate and which lane to get in.
Synthetic speech can reinforce these turn anticipations, can caution the driver
if he is perceived to be headed in the wrong direction or off course, and can
even guide him or her how to get back on course. An interesting question is
what the computer should say in each situation to get the driver’s attention, to
be understood quickly and unambiguously but without being an annoyance. Another
question is whether or not such systems will distract the driver’s attention
from the primary tasks, thereby reducing safety. The major vehicle
manufacturers have developed such systems, they have been evaluated for
reliability and human use, and they are beginning to be marketed in the United
States, Europe, and
Japan.
Air Traffic Control
by
Eng.Ramy
As demands for air travel continue
to increase, so do demands for air traffic control. Given what are currently
regarded as safe separation criteria, air space over major urban areas is
already saturated, so that simply adding more airports is not acceptable (in
addition to which residents do not want more airports, with their noise and
surface traffic). The need is to reduce separations in the air, and to land aircraft
closer together or on parallel runways simultaneously. This puts much greater
demands on air traffic controllers, particularly at the terminal area radar
control centers (TRACONs), where trained operators stare at blips on radar
screens and verbally guide pilots entering the terminal airspace from various
directions and altitudes into orderly descent and landing patterns with proper
separation between aircraft.
Currently, many changes are being
introduced into air traffic control which has profound implications for
human-machine interaction. Where previously communication between pilots and
air traffic controllers was entirely by voice, now digital communication
between aircraft and ground (a system called datalink) allows both more
and more reliable two-way communication, so that weather and runway and wind
information, clearances, etc. can be displayed to pilots visually. But pilots
are not so sure they want this additional technology. They fear the demise of
the “party line” of voice communications with which they are so familiar and
which permits all pilots in an area to listen in on each other’s conversations.
New aircraft-borne radars allow
pilots to detect air traffic in their own vicinity. Improved ground based radars
detect microbursts or wind shear which can easily put an aircraft out of control.
Both types of radars pose challenges as to how best to warn the pilot and
provide guidance as to how to respond.
But they also pose a cultural
change in air traffic control, since heretofore pilots have been dependent upon
air traffic controllers to advise them of weather conditions and other air
traffic. Furthermore, because of the new weather and collision-avoidance
technology, there are current plans for radically altering the rules whereby
high-altitude commercial aircraft must stick to well-defined traffic lanes.
Instead, pilots will have great flexibility as to altitude (to find the most
favorable winds and therefore save fuel) and be able to take great-circle
routes straight to their destinations (also saving fuel). However, air traffic controllers
are not sure they want to give up the power they have had, becoming passive
observers and monitors, to function only in emergencies.
Supervisory Control
Supervisory control
may be defined by the analogy between a supervisor of subordinate staff in an organization
of people and the human overseer of a modern computer-mediated semiautomatic
control system. The supervisor gives human subordinates general instructions
which they in turn may translate into action. The supervisor of a
computer-controlled system does the same.
Defined strictly, supervisory
control means that one or more human operators are setting initial conditions
for, intermittently adjusting, and receiving high-level information from a
computer that itself closes a control loop in a well-defined process through
artificial sensors and effectors. For some time period the computer controls
the process automatically.
By a less strict
definition, supervisory control is used when a computer transforms human
operator commands to generate detailed control actions, or makes significant
transformations of measured data to produce integrated summary displays. In
this latter case the computer need not have the capability to commit actions
based upon new information from the environment, whereas in the first it
necessarily must. The two situations may appear similar to the human
supervisor, since the computer mediates both human outputs and human inputs,
and the supervisor is thus removed from detailed events at the low level.
FIGURE
6.1.2Direct manual control-loop analysis.
Supervisory control
system here the human operator issues commands to a human-interactive computer
capable of understanding high-level language and providing integrated summary
displays of process state information back to the operator. This computer,
typically located in a control room or cockpit or office near to the supervisor, in
turn communicates with at least one, and probably
many (hence the dotted lines), task-interactive computers,
located with the equipment they are controlling.
The task-interactive computers thus receive subgoal and conditional branching
information from the human-interactive computer. Using such information as
reference inputs, the task-interactive computers
serve to close low-level control loops between artificial sensors and
mechanical actuators;i.e., they accomplish the low-level automatic control.
The low-level task
typically operates at some physical distance from the human operator and his human-friendly
display-control computer. Therefore, the communication channels between
computers may be constrained by multiplexing, time delay, or limited bandwidth.
The task-interactive computer, of course, sends analog control signals to and
receives analog feedback signals from the controlled process, and the latter
does the same with the environment as it operates (vehicles moving relative to air,
sea, or earth, robots manipulating objects, process plants modifying products,
etc.).
Supervisory command and
feedback channels for process state information are shown in Figure 6.1.3 to
pass through the left side of the human-interactive computer. On the right side
are represented decisionaiding functions, with requests of the computer for
advice and displayed output of advice (from a database, expert system, or
simulation) to the operator. There are many new developments in computerbased decision
aids for planning, editing, monitoring, and failure detection being used as an
auxiliary part of operating dynamic systems. Reflection upon the nervous system
of higher animals reveals a similar kind of supervisory control wherein
commands are sent from the brain to local ganglia, and peripheral motor control
loops are then closed locally through receptors in the muscles, tendons, or
skin.
The brain, presumably,
does higher-level planning based on its own stored data and “mental models,” an
internalized expert system available to provide advice and permit trial
responses before commitment to actual response.
Theorizing about
supervisory control began as aircraft and spacecraft became partially
automated. It became evident that the human operator was being replaced by the
computer for direct control responsibility, and was moving to a new role of
monitor and goal-constraint setter. An added incentive was the U.S. space
program, which posed the problem of how a human operator on Earth could control
a manipulator
arm or vehicle on the moon through a 3-sec communication round-trip time delay.
The only solution which avoided instability
was to make the operator a supervisory controller communicating intermittently with a computer on the moon, which
in turn closed the control loop there. The rapid development
of microcomputers has forced a transition from manual control to supervisory
control in a variety of industrial and
military applications (Sheridan, 1992).
Let us now consider some examples
of human-machine interaction, particularly those which illustrate supervisory
control in its various forms. First, we consider three forms of vehicle
control, namely, control of modern aircraft, “intelligent” highway vehicles,
and high-speed trains, all of which have both human operators in the vehicles
as well as humans in centralized traffic-control centers. Second, we consider telerobots
for space, undersea, and medical applications.
Direct Manual Control
by
Eng.Ramy
In the 1940s aircraft
designers appreciated the need to characterize the transfer function of the
human pilot in terms of a differential equation. Indeed, this is necessary for
any vehicle or controlled physical process for which the human is the
controller, see Figure 6.1.2. In this case both the human operator H and the physical
process P lie in the closed loop (where H and P are
Laplace transforms of the component transfer functions), and the HP combination
determines whether the closed-loop is inherently stable (i.e., the closed loop
characteristic equation 1+HP = 0 has only negative real roots).
In addition to the
stability criterion are the criteria of rapid response of process state x
to a desired or reference state r with minimum overshoot, zero “steady-state
error” between r and output x, and reduction to near zero of the
effects of any disturbance input d. (The latter effects are determined
by the closed-loop transfer functions x=HP/(1+ HP)r+
1/(1+ HP)d
, where if the
magnitude of
H is
large enough
HP /(1+
HP) approaches unity and 1/(1+ HP) approaches 0. Unhappily, there
are ingredients of
H which
produce delays in combination with magnitude and thereby can cause instability.
Therefore, H must
be chosen carefully by the human for any given P.)
Research to
characterize the pilot in these terms resulted in the discovery that the human
adapts to a wide variety of physical processes so as to make HP=K(1/s)(e–sT). In
other words, the human adjusts H to make
HP constant.
The term K is an overall amplitude or gain, (1/ s) is the Laplace
transform of an integrator, and ( e-sT) is
a delay T long (the latter time delay being an unavoidable property of
the nervous system). Parameters
K and
T vary modestly in a predictable way as a function of the physical process
and the input to the control system. This model is now widely accepted and
used, not only in engineering aircraft control systems, but also in designing
automobiles, ships, nuclear and chemical plants, and a host of other
dynamic systemsŲ²
Human-Machine Interaction
by
Eng.Ramy
Over the years machines of all
kinds have been improved and made more reliable. However, machines typically
operate as components of larger systems, such as transportation systems,
communication systems, manufacturing systems, defense systems, health care
systems, and so on. While many aspects of such systems can be and have been
automated, the human operator is retained in many cases. This may be because of
economics, tradition, cost, or (most likely) capabilities of the human to
perceive patterns of information and weigh subtle factors in making control
decisions which the machine cannot match.
Although the public as well as
those responsible for system operation usually demand that there be a human
operator, “human error” is a major reason for system failure. And aside from
prevention of error, getting the best performance out
of the system means that human and machine must be working together effectively — be properly “impedance matched.”
Therefore, the performance capabilities of the human
relative to those of the machine must be taken into account in system design.
Efforts to “optimize”
the human-machine interaction are meaningless in the mathematical sense of optimization,
since most important interactions between human and machine cannot be reduced
to a mathematical form, and the objective function (defining what is good) is
not easily obtained in any given context. For this reason, engineering the
human-machine interaction, much as in management or medicine, remains an art
more than a science, based on laboratory experiments and practical experience.
In the broadest sense,
engineering the human-machine interface includes all of ergonomics or human
factors engineering, and goes well beyond design of displays and control
devices. Ergonomics includes not only questions of sensory physiology, whether
or not the operator can see the displays or hear the auditory warnings, but
also questions of biomechanics
, how the body moves,
and whether or not the operator can reach and apply proper force to the
controls. It further includes the fields of operator selection and training,
human performance under stress, human factors in maintenance, and many other aspects
of the relation of the human to technology. This section focuses primarily on
human-machine interaction in control of systems.
The human-machine
interactions in control are considered in terms of Figure
6.1.1. In Figure 6.1.1a the human directly controls the machine; i.e.,
the control loop to the machine is closed through the physical sensors,
displays, human senses (visual, auditory, tactile), brain, human muscles,
control devices, and machine actuators. Figure 6.1.1b illustrates what has come
to be called a supervisory control system , wherein the human
intermittently instructs a computer as to goals, constraints, and procedures,
then turns a task over to the computer to perform automatic control for some
period of time.
Displays and control devices can
be analogic (movement signal directions and extent of control action, isomorphic
with the world, such as an automobile steering wheel or computer mouse
controls, or a moving needle or pictorial display element). Or they can be symbolic
(dedicated buttons or generalpurpose keyboard controls, icons, or alarm light
displays). In normal human discourse we use both speech (symbolic) and gestures
(analogic) and on paper we write alphanumeric text (symbolic) and draw pictures
(analogic). The system designer must decide which type of displays or controls
best suits a particular application, and/or what mix to use. The designer must
be aware of important criteria such as whether or not, for a proposed design,
changes in the displays and controls caused by the human operator correspond in
a natural and common-sense way to “more” or “less” of some variable as expected
by that operator and correspond to cultural norms (such as reading from left to
right in western countries), and whether or not the movement of the display
elements correspond geometrically to movements of the controls.
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