Can Unmanned Systems Technology Improve
Safety
and Efficiency in Automobiles
Stanley
D. Pebsworth
Embry
Riddle Aeronautical University
17
December 2017
Abstract
The purpose of this research was to
find whether Unmanned Systems technology enhances safety and efficiency of
automobiles. Due to the high number of
accidents reported by the Center for Disease Control (CDC), it is clear that
there are many deaths that are as a result of fatal road accidents.
Approximately a quarter of the total number of the deaths are caused by
distracted or inattentive drivers. The latter has caused premature deaths in the
U.S.A. Tesla, Ford Motor Company, and
General Motors are among companies whose collision avoidance systems are
reliable. This collision avoidance technology
has been implemented in various industries not limited to automotive, agriculture,
and aviation. This technology is
associated with a reduction of accidental deaths. Sample data was collected from the National
Transportation Safety Board (NTSB) and the National Highway Traffic Safety
Administration (NHTSA) to test the null hypothesis that unmanned systems
provide no increase in vehicle safety. The
sample collected was analyzed using a t-test to determine the validity of the
Null hypothesis. However, the findings
from the analysis showed that unmanned systems provide an increase in vehicle
safety, hence rejecting the null hypothesis that unmanned systems provide no
increase in vehicle safety.
Keywords: unmanned systems, highway
safety, transportation, accident claims, insurance
Can
Unmanned Systems Technology Improve Safety and Efficiency in Automobiles
Introduction
Unmanned systems
have been implemented in various sectors to reduce risk. Modern technology has incorporated unmanned
systems in the automotive industry to enhance safety. Use of unmanned systems technology has proved
to reduce the accidents that require quick decisions as well as precise
assessment (WHO, 2017). Unmanned technology
is not meant to remove the responsibility of the driver, but to assist the
driver in preventing imminent accidents.
Collision Avoidance Systems perform an assessment of the risk, plan the
prevention, and take measures that would mitigate the severity of the
accident. The technological differences
have made the companies develop Collision Avoidance Systems with varying
capabilities. However, the uniform
contribution of the technology in mitigating collision accidents is assured.
More than 1.25
million people lose their lives globally due to road accidents (WHO,
2017). In the United States, 33,736
people were reported dead from road accidents by Center for Disease Control
(CDC) (CDC, 2017). According to the
report from the National Highway Traffic Safety, most of the deaths of
individuals between 3 to 33 years of age are a result of traffic accidents (NHTSA,
2017). Fatalities have continued due to
inconsistent mitigation strategies. Technology
plays an important role in ensuring the safety of the road users. Collision Avoidance Systems are accurate in
computations and determination of the impending accident or danger. Through calculation of movement of objects,
the technology can predict a collision. Current
technology can alert the driver as well as help the driver to navigate the
vehicle to safety.
There are several
ways collision avoidance systems determine the probability of an accident
occurrence. Hence, a combination of
various types of alert systems used in the Collision Avoidance Systems assist
the driver and enhance consequent safety. Basic Collision Avoidance Systems only contain
audible alerts that warn the driver of an impending accident. In spite of the assistance the audible alert
system produces, the technology is not sufficient, and requirement of more
reliable technology is necessary. As a
result, braking technology was added to vehicles with Collision Avoidance
Systems. The latter boosted the safety
by initiating action when the driver fails to take any action. However, audible and braking systems have not
been effective in various situations leading to more research and development
of intelligent systems. Intelligent
systems have the ability to determine the accident, warn the driver, and if the
driver fails to act, the system determines the best action to take such as braking
or taking divertive steering action. Reviewing
current technology and analyzing respective data would help determine the
extent to which the unmanned systems reduce accidents.
Problem Statement
The problem under
investigation is how best the technology of unmanned systems can be applied to
automobiles to improve efficiency and safety on the roadways. Using the data provided by NHTSA and NTSB,
this project will find and evaluate the cause accidents. The latter will help in the formulation of the
application of unmanned systems and how utilization of the technology might
provide solutions to automobile accidents.
History
Unmanned systems
research and development has been ongoing for years, and determination to
develop better systems have been encouraging.
Researchers have been vigilantly studying the advancement of unmanned
technology for the last two decades. Notably,
the research conducted by military professionals and researchers remained in
the background for years. Surprisingly,
the field of unmanned technology is not new because it started during the
Second World War (Roberts & Sutton, 2013).
Social effects of
unmanned systems have been an issue of concern over the years. In spite of the significant steps taken
towards implementation of more intelligent systems, differences arise in
accordance to how the institutions view the technology. Organizations and researchers differ
regarding perception and the philosophical background on the unmanned systems. Consideration of the insertion of these
systems in high-risk environments would be appreciated. However, concerns have been whether humans are
endangered. In spite of the relationship
between unmanned systems and artificial intelligence, it is not meant to
replace the human and the role they play in operations. Advanced distributed systems, control
systems, and respective command are the areas that require future development
of concrete systems. Understanding of the technology and the role it plays will
aid the integration of the technology in various sectors not limited to the automotive
industry.
Collision
avoidance systems impact the security of pedestrians, drivers, and passengers
positively. As part of unmanned systems
and technology, it is evident that this creates value in life by reducing the
chances of accidents. The concept of
intelligent systems in the transportation sector is core in improving safety
and security. The safety and security of
vehicles, as well as their users, is guaranteed. Consequently, due to integrated systems in
Collision Avoidance Systems, energy is well utilized since it enhances and
sustains mobility. Reduced accidents
have both an environmental and economic impact since fuel and time are
utilized. However, it is common that
initially, society is reluctant to accept some of the changes due to worries
that are beyond the scope of implementers. Integrating collision avoidance systems is among
accepted options that guarantees effective transport. Public safety is guaranteed through a complete
intelligent infrastructure of the intelligent transport system. Collision avoidance systems improve emergency
management and advanced vehicle security which covers lateral, longitudinal,
and intersection collision avoidance.
Additionally, safety readiness, vision enhancement, and automated
vehicle operation are other benefits of unmanned technology. Reducing the notification time of police and
emergency management in the instance of an accident relieves the public from
possible death and unnecessary trauma. Due
to the ability of the systems to enhance transportation, improve mobility and
reduce congestion, environmental pollution, and risk the technology improves
the quality of life in all communities. In fact, the safety and security of the
existing infrastructure increases. The
reduction of crashes, fatalities, and injuries are some of the measures whose
levels are reduced in every efficient transport system.
Automated speed
control and crash avoidance systems are core in safety performance in the future.
Several technologies not limited to
Collision Mitigation Braking (CMB), Forward Collision Warning (FWC), Forward
Collision Avoidance and Mitigation Systems (F-CAM) and Adaptive Cruise Control
(ACC) provide the foundations for future developments (Jermakian, 2012). The basis of Collision Mitigation Braking is
on assisting the driver with automatic braking.
The application of the force required to minimize the chances of hitting
a vehicle determines the action taken by the system. Notably, this technology does not help in braking
if the difference in speed between vehicles is less than 10 mph. As well, the CMB may not work if the driver
steers to avoid a collision. However,
when the CMB activates, the system brakes the vehicles automatically, and the
brake lights are turned on.
The sensor that
helps in radar functions on some vehicles is located on the front grille. If an obstructive object is placed on the
sensor, it stops working. This is
followed by the indication on the instrument panel indicating the CMB is
inactive. Every time the CMB is on, it
scans radar constantly through the sensor. Some of the issues that might lead to failure
in sensing include a heavy load that tilts the vehicle changing the sensors
field of view or modification on the suspension. At times failure to maintain proper tire
inflation as required may result in the same problem. The sense of a possible collision leads to
audible and visual alarm.
Current Technology
Fundamental Technology
The National
Highway Traffic Safety Administration (NHTSA) reported that there are
approximately 56,000 cases of accidents happening in the United States due to
drowsiness and fatigue (NHTSA, 2017). Adaptive
Cruise Control (ACC) is one of the initial technologies which improved driver
comfort. ACC is an essential control for
surface vehicles, especially on the road in maintaining a distance that is safe
for vehicles on the same road (Hong, Park, Yoo & Hwang, 2016). This technology does not use any satellites,
instead it uses information obtained from sensors onboard. ACC typically measures the distance of the
car preceding through radar. In the
event that a frontal vehicle appears, the system changes the vehicle’s speed to
control spacing. This is useful in
preventing a collision with the forward vehicle. Complex systems have been developed on the
fundamental principles of ACC. Collision
Avoidance Systems, as well as the vehicle Platooning strategy, reflect the ACC
application (Volpe National
Transportation Systems Center, 2017).
ACC has been used in the implementation of Advanced Driver Assistance
Systems (ADAS). In 2013, 29% of vehicles
used on the road possessed the ACC feature (WHO, 2017).
In spite of the
simplicity of development and implementation, ACC is not reliable in scenarios such
as when the preceding vehicle slows suddenly.
Therefore, this calls for inclusion of ADAS on vehicles with ACC to
boost the capability of the systems in boosting safety and efficiency of the
overall system. Advanced Driver
Assistance System improvements ensure that safety and traffic assistance has
been achieved. Collision Avoidance Systems
fall into the category that grants safety.
Other uses of the systems include traffic assistance as well as driving
comfort. Notably, the occurrence of
accidents involving drowsy drivers also exists therefore, the need to develop
systems that detect the drowsiness of a driver was necessary. Driver Drowsiness Detection (DDS) systems
would assist in preventing these accidents occurring due to drowsiness or
fatigue of the driver. The DDS system measure
the drowsiness of a particular driver by monitoring the steering pattern of the
driver against the steering input angle.
DDS improvement
would include future sensors to provide steering feedback to prevent an
accident caused by a fatigued driver. Importantly,
the sensor must accurately obtain information about the driver in relation to drowsing
and fatigue. Therefore, incorporating
Human-Machine Interface Technology to measure the level of driver drowsiness is
necessary for a reliable Driver Drowsiness Detection Systems.
When introduced, Collision
Avoidance Systems provided the highest level of safety in the family of ADAS. As a result, the National Highway Traffic
Safety Board made the feature mandatory in 2016 for all new vehicles (NAMIC, 2017).
These systems prevent a potential collision from happening. Path Tracking Strategies, Threat Assessment,
and Path Planning are the three sub-models contained in Collision Avoidance Systems
(NAMIC, 2017). Normally, the threat
assessment tool is used to measure the risk and correspondent metrics of the
collision. After the detection and
assessment of the risk factor, the information is passed to the system that
involves planning. Consequently, this
feeds the current trajectory planning relating to the vehicle. Mostly, when collision between vehicles is at
high speed; it is important to ensure precise selection of every strategy
involved in mitigating the risk. The
purpose of collision avoidance is determining the low-level selections of
navigation through respective controls such as brakes and steering actuators. Collisions are known to happen in many
instances especially where the vehicle needs to avoid a single vehicle, a long
bus, or multiple vehicles. Therefore, the
systems that would reduce threat is required to have embedded algorithms with
good path planning, threat assessment as well as path tracking strategies.
Lane departure
warning systems help the driver in maintaining the lane in the case of
drowsiness. Lane departure is an
indication of an irregular driving pattern. Hence, markings are required to be painted on
the road to keep the driver within the lane to avoid accidents. There are two approaches in lane keeping. One of the systems produces a visual, haptic
or audible warning when the driver departs the lane and the second system of
lane keeping overrides the input of the driver in case of
unresponsiveness. The major drawback of
the Lane Departure system is the dependency on the visibility of road markings.
Therefore, future research in the advancement
of image processing technology that would help process images of lane markings
during day and night visual fields is appropriate.
Intersection
assistant is used in urban centers where overcrowded intersections have been
prone to accidents. Intersection
assistance alerts the driver to cross traffic as well as pedestrians that may
step out between vehicles. The increased
urban population has led to increased cases of accidents. Mostly the accidents occur where a pedestrian
or an obstacle appear in front of a moving vehicle. Moving objects on the road are the main
causes of accidents due to the sudden obstruction avoidance required on the
driver. Vehicle-to-infrastructure mode
of communication would help reduce the accident rates through enhancement of
intersection assistant system. Intersection
assistant technology has been used in traffic light violations, wrong turnings,
and crossing-path collisions prevention.
Vehicular
communication system technology involves the network integration of vehicles
that assists in exchange of information with the environment through communication
nodes. The exchange of information is meant to ensure traffic information and
safety enhancement. Both vehicle to infrastructure
and vehicle to vehicle fall under vehicular communication. The latest developments in the
internet-of-vehicle, a segment of the Internet-of-Technology has triggered the
complex development of vehicular communication systems. Vehicle to X, where X represents the medium of
communication, help vehicles communicate effectively and exchange information
about their environments. Some of the
parameters that vehicles exchange includes the flow of traffic and the rate and
proximity of appearing vehicles that are beyond the visual range of the
driver. Vehicular communication
technology integration to the collision avoidance systems has been proven to
alert and warn the driver about the impending risks of accidents several
vehicles ahead (Volpe National
Transportation Systems Center, 2017).
Traffic congestion
is a global problem and is among factors that contribute to collisions. Moreover, according to the Bureau of
Transport statistics of the United States, traffic congestion is responsible
for approximately 30% of carbon emissions that occur in the United States of
America (Volpe National Transportation
Systems Center, 2017). Vehicle
platooning is the current technology that aims at reducing traffic congestion. The technology aims at reducing fuel
consumption, improving mileage, as well as enhancing vehicle safety. Vehicle platooning technology involves
controlling vehicles through a computer system.
Platoon technology enables the vehicles to exchange information
regarding the surroundings which help them in cooperation and navigation. Vehicle platoon technology and a combination
of ADAS systems would help in producing a more reliable technology that would
help in mitigating cases of collision (Volpe
National Transportation Systems Center, 2017). A robust collision mitigation technology would
contain algorithms that rely on several technologies to assess the threat as
well as plan and determine accident avoidance strategies precisely. Notably, Platoon technology helps vehicles
plan lateral and longitudinal motion effectively. The major challenge facing vehicle platooning
implementation globally is the need to modify the current infrastructure.
Tesla Collision
Avoidance Systems
Tesla technology
has gained trust over several tests due to the measures taken to increase
safety. The Tesla system is one of the
most dependable autopilots. Defined by
model X, Model S, and Model 3, continuous enhancement of the system has made it
one of the best autopilot systems. Model
S’ features guarantee performance and safety of the Tesla customer. The Model S system is designed to be the most
exhilarating and safest on the road (Lambert, 2017). Autopilot capabilities are configured in a
way that highway driving is safe and stress-free. Adaptive lights have been integrated into the
model to ensure automation of the headlamps. Enhancement of the lighting system
boosts safety by improving visibility through 14 three-position LED lights that
turn dynamically.
Model X guarantees
safety, and is one of the best SUVs with safety integrated standard features. Moreover, the SUV contains adapted hardware
that provides visibility assistance beyond human capability. The vehicle contains eight surrounding cameras
that allow for 360-degree vision (Lambert, 2017). Additionally, twelve ultrasonic sensors are
integrated into the system to enable detection of environmental objects. The forward-facing radar aides in detecting
objects through fog, heavy rain, dust, and even beyond the car ahead. This helps in preventing collision accidents
since the vehicle provides increased awareness in all directions. The Model X achieves a 5-star rating in all
categories due to the ability to avoid accidents through its unmanned systems. Active safety of the Model X includes the most
advanced safety features not limited to side collision warning, automatic
emergency braking, autopilot driver assistance and lane departure warning. Notably, the Model X gets better every day due
to the ability of software updates that optimize sensor technology (Lambert,
2017). These updates occur when the
vehicle is connected to the Tesla server through an internet connection. Once connected, the server collects data from
the vehicle that both assists in refining software as well as updates current
software on the vehicle itself.
Driver assistance
components in Tesla cars guarantee security and prevent accidents. Radar technology, front-facing camera, and
ultrasonic sensors are fundamental in establishing a safe environment for the
car. Radar is used to assist in the
limited visual environment by detecting objects that may not be visually
seen. A front-facing camera provides
visual obstacle detection and is assisted by the radar in detecting object that
can be seen visually. Ultrasonic sensors
are used when in close proximity to an object.
Neither the radar nor visual systems can provide the level of accuracy
needed to avoid objects within five feet of the vehicle (Lambert, 2017). As well, lane departure assist, collision
avoidance assist, and speed assist are made using advanced unmanned technology.
Autopilot tech package is integrated
with the standard feature that ensures driver assistance in all realms. Vehicle
lane assist intervenes by providing steering adjustment when the vehicle shifts
from the appropriate lane unintentionally.
Ford Collision
Avoidance Systems
The rise in
fatalities of pedestrians and motorists have resulted in new technologies to
solve the problem. Ford’s new systems
use automatic braking and steering in the case of a collision risk. Therefore, these vehicles can avoid striking
pedestrians or obstacles. Development of
obstacle avoidance system has put Ford in an important position regarding innovations
to prevent accidents. Ford cars using these
systems can perform automatic braking as well as steering during collision
avoidance with other obstacles. The
instances in which this technology is used includes avoiding hitting a
pedestrian, slowing cars in the same lane ahead, or vehicles that have stopped
moving. The system alerts the driver of
an impending accident ahead. In the
instance that the driver acts slowly or fails to take any action, the automatic
system applies braking to avoid a collision. The Obstacle Avoidance-equipped Ford Focus has
been part of a project conducted by Ford consisting of 29 partners in the
consortium to ensure the creation of safety systems that would prevent an
imminent collision (Hayashi, Inomata, Fujishiro, Ouchi, Suzuki, & Nanami, 2013).
Continuity and
building block approach is what every customer of the company's vehicles has
experienced. The technology started with
warning features and assistance features including brake assistance,
cross-traffic warnings, lane-drift detection, active park assistance, and blind
spot monitoring. Preceding lane-drift
detection technology was lane-drift correction technology through anti-lock
hydraulic brake module pulsing. Current
technology now uses electric power steering for lane-drift correction as well
as collision mitigation through automatic braking. In spite of the bold steps taken by
technologists, there are limitations such as the steering torque that has not
been regulated by any agency. As well,
Ford needs more information regarding nature and infrastructural conditions
required to do engineering integration.
General
Motors Collision Avoidance Technology
General Motors
Company has been on the forefront in ensuring that its customers are safe
through continuous innovations.
Precision engineering in safety features the company has made display
General Motors attention to details. Some
major technologies used by the company include adaptive cruise control, active
tow, following distance indicator, forward collision alert, low-speed forward
automatic braking, front and rear parking assist, front pedestrian braking, and
front and rear parking assist. The
company has also implemented technologies such as lane keep warning with
departure warning, rear cross traffic alert, rear parking assist, safety alert
seat, and lane change alert with side blind zone alert.
Low speed forward
automatic braking system detects the proximity of the vehicle and the speed of
the moving vehicle. When the system
detects that the front-end collision is imminent, the system applies the brakes
automatically and reduce the collision severity (Riaz & Niazi, 2016). Actually, at low speed, the system prevents a
collision from occurring. Front and rear
parking is useful when the vehicle speed is below 5 mph. This assists the driver by alerting him or
her about objects that are near to the vehicle.
This prevents crashing into the nearby object or vehicle. Rear cross traffic alert is used when the
vehicle is moving in the reverse direction.
This technology helps the driver from crashing into objects approaching
left or right especially in a crowded driveway or parking space while avoiding
side obstructions.
General Motors has patented a seat that
contains safety alert and provides the driver with the option of haptic
seat-bottom and subsequent vibrations instead of the being subjected to crash
avoidance alerts that are audible. Lane
Change alert with side blind zone alert technology assists the driver in
avoiding crashing into a vehicle that is moving in a blind spot on the side (GM
Authority, 2017). Sometimes the vehicle
might be approaching the side blind spot rapidly, especially when changing the
lane. In such instances, the lane change
alert helps the driver to avoid a collision.
Lane keeps assisting with departure warning assist the driver by
engaging gentle steering as well as alerting driver on the attempted lane
departure. This helps the driver to
prevent accidents that happen from unintentional drifting or departure from the
lane. The Precise decision by the system
is made through checking whether turn signals are activated, and the driver has
not applied steering of vehicle. If the
signals are activated, the system will sense intentional lane change. Front pedestrian braking detects a direct
head-on collision between the pedestrian and the vehicle. When there are imminent chances of collision,
the system alerts the driver.
Consequently, if a fast response is required, the system engages
automatic braking. Forward collision
alert is used to detect collision to the front.
When there is a high chance of an accident, the system notifies the
driver to avoid a potential crash. This
system also alerts the driver when he is following a vehicle closely and past
an adjustable limit.
Adaptive cruise
control is one of the most popular collision avoidance systems. ACC is used to prevent accidents through
enhancement of cruise control. As a
result, a vehicle follows the detected car ahead automatically by the gap the
driver has selected without the need for the driver to adjust speed or brake
frequently.
General Motors
developed one of the most affordable collision warning systems. The systems based on a single camera at the
rearview mirror helps the driver to avoid the un-signaled lane departure, and
front-end crashes. General Motors uses
radar sensors and or cameras to implement this technology. Use of the digital camera on the collision
and avoidance systems has been one of the trending approaches. Multiple functions of the high-resolution
camera include looking for the shapes of vehicles and markings on the
lane. Software integrated to the system
examines every frame that is captured.
After the shape of a car is identified, the system calculates the
time-to-collision. Notably, the
integrated system uses directional change, speed, and sensors to determine when
to alert the driver. This technology also
determines how the accelerator and brakes should be applied.
The collision warning
system uses warnings and alerts that are audible as well as mounted visual
warning displays that inform the driver whether he or she is following a
vehicle too closely. When a collision is
imminent, the system alerts the driver if he or she is departing from the lane
or driving too close to another vehicle. On display, a vehicle ahead is
represented by a green vehicle or lanes as icons. Forward collision alerts flash red on the
display while an amber warning signals lane departure. Every warning is followed by a warning
chime. When the system predicts a
collision, the brakes of the vehicle pre-charged to ensure that the driver
reaches maximum braking quickly. The
major drawback of the system is that it can only operate if the camera eye is
unobstructed. The best feature is the
combination of four exposures to form a high-resolution image that is used for
analysis. Moreover, night time
recognition includes recognition of pairs of light moving together as an
indication of taillights.
Application of
Technology
An NHTSA report on
the benefits of Collision Avoidance Systems recommended implementation of the
technology on all vehicles to reduce the prevalence of fatalities related to
traffic accidents in the United States (NHTSA, 2017). Implementation should standardize the minimum
requirements of every CAS system in the industry. Therefore, assessment protocols, comparing
and testing, and requirement assessment is mandatory to approve dependable and
reliable systems. The latter implies
that NHTSA should document and publish all the acceptable Collision Avoidance
Systems in the industry. Manufacturers
and consumers ought to be granted incentives. Forward Collision Avoidance System should be a
necessity and compatible with all other technologies as a way of ensuring
reduction of the severity and frequency of crashes.
Evaluation of the
current systems and the prevalence on the commercial as well as passenger fleet
help in determining the appropriate strategies. This also helps in determining the methods of
installation of the systems on all vehicles. NHTSA’s responsibility of ensuring deployment
of collision avoidance technology has been challenged by compliance in a
diverse industry (NHTSA, 2017). However,
the organizations that produce the standards have been slow in developing the
criteria and standards that are comprehensive. Nevertheless, the criteria and classification
of the systems are yet to be delivered. Performance
standard tests should ensure that the vehicles meet the minimum operating level
of the respective system.
The minimum and
the lowest level of the system is the forward CAS. All systems should meet the minimum
performance standards of the approved system. Since the performance standards are developed
by government agencies or specialized organizations, NHTSA should collaborate
with the International Standardization Organization (ISO) or SAE to ensure
minimum standards are met by all technologies dispatched in the market (NHTSA,
2017). Notably, the same institutions
should be charged with the responsibility of developing assessment protocols. This refers to the process of evaluation to
ensure that the systems are efficient before installation on vehicles. It is after protocol development that the
systems are tested. Manufacturing
companies perform internal tests on the systems to ensure functionality and
meeting of the standards. Utilizing established
protocols of assessment will provide manufacturers with an opportunity to test
the effectiveness of the systems. Apart
from NHTSA, other agencies such as IIHS and ADAC can be used to conduct tests
since they are charged with transport safety. Tests conducted by transportation agencies
should be made available to the consumer (NHTSA, 2017).
Currently, only
one forward CAS technology exists. ISO
developed the CWS standards with performance requirements as well as the test
procedures. Development of the standards
should address interface design not limited to timing and modality of a
warning. The occurrence of false alarms
has been one of the problems prevalent on the substandard collision avoidance
systems. Therefore, the standards should
address the issue of false alarm and miss rate. After recommendations from the NTSB, NHTSA
developed assessment protocols as well as the partial performance standards to
be used in forwarding CWS evaluation in the passenger vehicle (NHTSA, 2017). However, the protocols were not satisfactory
because they only covered the evaluation of CWS technology and not the absolute
performance of the Forward Collision Avoidance System. The tests were used to determine the
effectiveness and the ability of the systems in detecting a conflict and
informing the driver. Consequently, the
test should evaluate the systems alert timing. In spite of the efforts to develop
comprehensive tests in accordance with human factors, issues such as modalities
of the warnings are yet to be examined. Also,
the partial assessment protocols and performance standards for the Forward
Collision Avoidance System only exist for passenger vehicles and have not been
assessed for commercial vehicles. In
spite of the failure by NHTSA to develop the performance standards and
assessment protocol, most manufacturers are adopting the forward CAS.
NTSA has been
working on the final stages of developing performance standards on autonomous
emergency braking systems. The AEB
assessments protocols were developed to test passenger vehicles. Development of the protocols of assessment has
gone through various iterations. An NHTSA
report on the AEB systems in passenger vehicles showed the result of the current
systems tested in 2015. Establishment of
the protocols and the standards assessment of AEB in commercial vehicles has
taken time. Commercial vehicles should reflect
the same procedures documented for passenger vehicles. IIHS protocols for AEB assessment on passenger
vehicles represent partial protocols since they cover a single scenario for
rear-end crashes. Additionally, the standard
takes a low velocity of only 25 mph (NHTSA, 2017). Even though the assessment provided by IIHS is
not sufficient, it is crucial in the future development of AEB test assessment
and protocols.
Implementation of
the current standards and technology of Collision Avoidance System is taking
shape. However, the process has been
slow due to the developmental stages of assessment and protocols of testing the
manufactured systems against various scenarios.
NHTSA effort to make the forward CAS mandatory requirement in all
vehicles has met challenges. For
instance, the standards of all manufacturers differ, and there are no ultimate
general standards that either IIHS, NISB or NHTSA have delivered. However, partial deliveries of assessment
protocols have been met by various bodies on different parameters. A report by
NHTSA has emphasized the important role that unmanned systems, especially
Collision Avoidance Systems, play in mitigation of fatal accidents. In spite of the slow incorporation and
implementation of CAS, collaboration among various agencies is promising. Manufacturers and stakeholders demonstrate
great efforts on implementation of Collision avoidance systems. Besides General Motors, Tesla, and Ford Motor
Company, other companies such as Toyota have developed astounding systems. Collective deployment of the systems in all
vehicles will boost safety on the roads.
Critical Analysis
Unmanned System Design Configurations
The
designs used in unmanned systems are the basis for the safety and security they
provide. The collision avoidance system
uses models such as pedestrian detection where the system can see a person
crossing the road and alert the driver. The
automatic braking system is another factor utilized by this system to enhance
safety on the road. The unmanned system
technology is viable in increasing security on the road as well as reducing
deaths associated with automobiles. Besides,
the technology applies various sensors and signals which are easy to understand
for the path users to cooperate correctly. For instance, the braking systems work in
close collaboration with the pedestrian detectors making the car owner or
operator feel safe. The Insurance
Institute for Highway Safety recommends the use of these systems to reduce the
cost incurred after accidents. Therefore,
the unmanned systems technology is feasible in helping reduce damages caused by
inattentive drivers.
The
first design used in unmanned systems is the collision-avoidance system. The system aims at eliminating any chances of
a collision between the vehicle and other elements. The configurations applied include a
pre-crash safety with pedestrian avoidance assist. This system works by detecting both vehicles
and pedestrians near the road. It
signals the braking system which reduces the speed to about 40 kph (Villa,
Gonzalez, Miljievic, Ristovski & Morawska, 2016). The reduction in speed reduces the impact
energy of the collision as compared to the crash if the rate was maintained. Further, to improve on reducing impacts, the
vehicle may be equipped with a system that detects obstacles at a farther distance
allowing braking to be applied at a distance where the collision will not
occur. This design would ensure the
safety of pedestrians as well as people occupying the vehicle. The damage that would have been caused is
minimized by the utilization these configurations.
Another
collision avoidance system used in unmanned systems is the high-deceleration
automatic brake control technology which works to assist in reducing the impact
of the crash. To achieve this, the
system is configured with a deceleration feedback control algorithm. The sensors detect an object, and the signal
is sent to the pre-crash system Electronic Control Unit (ECU) which judges the
signal, and it alerts the braking system accordingly. To ensure that the driver is alert when this
is happening, he or she must avoid a collision before the time to collision is
reached, especially when the object is detected within a short distance. Evaluation of crash avoidance by an ordinary
driver compared to that of an automatic system show that the automated system
responds faster than the ordinary driver. However, the driver's response is the time to
collision demonstrating that overdependence to the system should be avoided
(Hayashi et al., 2013). This
configuration is feasible as it ensures no accidents occur and the damage
caused by the sudden reduction of speed is minimal.
The
next configuration of the unmanned system that makes them secure is the design
of millimeter wave radar horizontal position filter which helps to avoid delay
when making collision judgment. In the
case where there is no filter, the sensor will signal that a pedestrian is
crossing hence making the system respond with delay if the person passes fast. The filter works by detecting the change in
distance between the vehicle and the pedestrian, some horizontal changes, and
the speed of the pedestrian crossing. A signal is then sent to the collision
avoidance system by the position filter so that an assessment can be made as to
the probability of collision (Hayashi et al., 2013). The system works hand in hand with the fusion
algorithm. If the radar is used alone,
it will detect all objects that may not necessarily need crash avoidance. The radar lowers the detection threshold when a
pedestrian is detected, and raises this threshold when a vehicle is detected. For more efficiency and increased safety,
radar reflection fuses with a three-dimensional camera. The camera can detect the width and height of
the object detected making the response more effective. The combination of these configurations
improves the safety of pedestrians crossing the road with a higher percentage
compared to each configuration working alone. Hence, it is called the fusion algorithm.
Collision
avoidance systems use the collision judgment algorithm by increasing the
judgment collision probability not to cover the driver’s width by itself. The system works to enhance the effectiveness
of the speed reduction algorithm. It
helps the vehicle detect objects outside the driver’s area which could be
affected by a collision. It determines
the point of intersection between the driver and the pedestrian crossing the
road. The sensors determine the
particular time taken by the pedestrian and hence calculating the relative
course of the person crossing the road. The
configuration of this system is improved by increasing the accuracy which is
achieved by dividing the driver’s area into small segments where the collision
positions are distributed horizontally. A probable collision occurs when the threshold
value is less than the collision probability. Hence, the speed is reduced at a further
distance after determining the time to collisions. This configuration ensures high levels of
safety of road users.
Elemental
Components and their Appropriateness in Unmanned System Technology
The
elements of unmanned systems have various functions. The sensors help in detecting an object depending
on the configuration and scheme. For instance,
the blind spot detection system has sensors that work as the eyes assisting the
driver to stay alert in order to detect objects in their blind spots (State
Farm, 2017). In autonomous land
vehicles, identifying the objects near it is important to reduce damages. These vehicles have a sensor fitted with a
camera that can take an image within two seconds at high resolution. The driver is signaled so as to avoid the
crash. Sensors are appropriate as they
assist in detecting objects. These sensors are the basis of the unmanned system,
because if the object cannot be detected, the accident cannot be avoided.
A
camera is a major part of the unmanned system as well. Even though they can work with sensors alone,
the cameras help in obtaining more accurate information which the sensor might
ignore. Hence, for safety and efficient
application, the system must have a camera.
Cameras are necessary for the rear cross-traffic alert which works
through a warning in audio and visual form. In forward-collision warning and auto brake, a
camera-based system warns the driver of impending collisions through images
(Linkov, 2015). Further, the lane
departure warning also uses a camera alongside sensor to detect the lane
markers in order to assist in using the wrong lane. The driver is alerted when he or she gets to
the wrong road through audio or a vibration of the steering wheel (Linkov,
2015). Therefore, the camera is a
crucial component in the unmanned system aiming at ensuring safety and useful
application.
Limitations
and Constraints
The
application of unmanned systems requires design configurations that will ensure
safety and ease of implementation. The
use of the collision avoidance system has to apply designs that are easy to
configure, and drivers must be able to understand them. The algorithms should fuse various
configurations for better working of the whole machine. The vehicle should detect the objects and
respond accordingly without affecting the surroundings. For example, the fusing of the object detector
and the automatic brake control would assist in improving the response of the
vehicle to avoid a crash. The sensors
and cameras installed in the car help in providing visual and audio warnings. The driver must be alert to respond when the
system fails, and he or she should not be overconfident in the system since it
may become faulty. The limitations and
constraints facing installation and proper function of the components of the
unmanned systems should be eliminated and the operators informed if they exist.
Research Problem Investigation
Literature Review
Implementation and
deployment of a technology that prevents aircraft collision is proof that
collision avoidance systems save lives. If implemented on vehicles, both commercial
and non-commercial, these systems would enhance safety. In a James K. Kuchar and Ann C. Drumm article
on Collision Avoidance systems emphasis on the success of the technology in
reducing road accidents (2017), Traffic Alert and Collision Avoidance System
(TCAS) reduce midair collisions. TCAS
has been in place for a decade and has prevented the occurrence of catastrophic
accidents. The rate of deployment of the
system shows the unique position TCAS has in mitigating air-collisions
accidents. Notably, the technology has
been installed on more than 25,000 aircraft globally (Kuchar & Drumm,
2017).
Advisably, the
stakeholders of the automotive industry should borrow from TCAS to develop a
more reliable CAS (Kuchar & Drumm, 2017).
Considering that aircraft move at higher speeds than passenger vehicles,
TCAS borrowed mechanisms would be effective due to their fast processing speed
and higher-level algorithms required to avoid an impending collision in the
air.
There are several
components in the TCAS system that help in detection, threat assessment, and path
determination. Surveillance sensors are
used to gather information about an approaching intruder aircraft including the
velocity of the object as well as speed. The information passed is used by algorithms
to determine whether the threat of collision exists. Identification of threat results in
involvement of another set of algorithms that determine the most appropriate
response. If TCAS is installed on both
aircrafts, they communicate through a data link to ensure deconflicted
avoidance maneuvering. The systems are
used as advisories to the crews. Hence,
the crew should take avoidance measures provided by TCAS unless the maneuver
jeopardizes safety.
A research paper
entitled Vehicle Technologies to Improve Performance and Safety by Pratyush
Bhatia (n.d.), provides recommendation for the improvement of safety
technologies in vehicles after thorough study on the causes of accidents. Collision warning systems, night vision
systems, active vehicle control, warning and advice systems, onboard diagnostic
systems, automatic collision notification, automatic vehicle identification,
and cellular communications are among the technologies used to enhance vehicle
safety. Use of different types of
technology is crucial in mitigating risks in all dimensions. The paper examines the technologies and how
they assist in the reduction of fatalities, property damage, and injuries.
Bhatia’s research
is relevant due to the examination of current technology and the rate at which current
safety technologies reduce accidents. Consequently,
the research details these current technological features. Design specifications, costs, functions, and
performance are covered in the documentation. As well, the paper covers improvements of the
safety systems that have occurred over time and the projections of the next 20
years.
A study conducted
by the NHTSA indicates that 75% of all the crashes are as a result of driving
task errors and driver recognition errors represent 43.6% of those errors
(Bhushan, 2016). In some cases, the
driver fails to see the vehicle ahead due to inattention, an obstruction such
as road equipment, or the road geometry.
Errors related to driver decision account for 23.3% of crashes (Bhushan,
2016). Unsafe passing, driver
misjudgment, and excessive speed are related to driver decision error. Driver erratic actions including failure to
control the vehicle, the intentional running of a red light, and deliberate
driving account for 8.5% of all these accidents (Bhushan, 2016). The driver’s
psychological state not limited to the ill driver, sleepy driver, and drunk
driver accounts for 14% of all these accidents.
Other parameters covered in the research include vehicle defects,
reduced visibility, and road surface representing 2.5%, 0.1% and 8.0%
respectively (Bhushan, 2016).
Unmanned
systems are the digital applications that operate with the help of sensors and
do not require human labor. The systems
ensure safety through minimizing accidents as compared to dependency on human
effort alone. Their efficiency is
measured by how they make work easier as compared to other methods. In automobiles, unmanned systems are used to
reduce the number of crashes occurring on the road. The percentage of accidents provided by the
National Transportation Safety Board (NTSB) and the National Highway Traffic
Safety Administration (NHTSA) help in determining how efficient and safe
unmanned systems make the motor vehicle industry. Published work shows that when the driver
understands how the systems work, there is a high probability of achieving the
purpose of the systems. Other
institutions like the insurance and the highway administration are advocating
for mandatory installation of these systems.
Various
scholars have discussed how unmanned systems can be helpful in improving
security. Others have explained that
inattentive drivers contribute to the increase in the number of accidents. According to Woodrooffe, J., Blower, D.,
Flannagan, C. A., Bogard, S. E., Green, P. A., & Bao, S. (2013), future
generations may have a safer environment due to automation. The authors developed their idea through
research which aimed at estimating the safety advantages of the use of current
and future technologies such as Adaptive Cruise Control (ACC), Forward Collision
Avoidance, and Mitigation systems (F-CAM). The research showed that use of modern technology
systems that include unmanned systems have benefits such as reduction of
accidents that are caused by tracks, reduced impacts after collisions due to
the warnings before the crash, and elimination of crashes. Hence, unmanned systems improve safety and
ensure efficient automobiles.
Unmanned
Ground Vehicles (UGV) are used to transport loads at any distance without the
operation of a person. These systems are
activated when the environment is not suitable for human operation. Factors such as the hazardous environment,
strength required, size limitation, and the terrain may make an individual opt
for unmanned ground vehicles over human effort.
Considering these factors, it is safer to use the UGV than endangering
human lives in unbearable environments. Further,
unmanned vehicles used by the military in areas with high radiation, or where
heavy equipment is required play a vital role in ensuring the safety of soldiers.
The vehicles only need the right
settings, and they can perform more efficiently than human effort. Advanced Teleoperator Technology works based
on the advanced, spatially-correspondent multi-sensory human/machine interface
and tests showed the effectiveness of the technology in operating remote
vehicles. The project helped the team
understand other benefits such as the effectiveness of stereo head-coupled
visual display systems, and isomorphic vehicle control at high speed. Therefore, the efficiency and safety of the
unmanned systems have proof.
Further research shows that various safety
institutions are advocating for mandatory installation of unmanned systems in
vehicles. Linkov (2015) explains that
the Insurance Institute for Highway safety has improved its safety evaluation
measures which include checking for the collision-avoidance system in vehicles.
The safety assessment aims at ensuring that
the number of accidents can be reduced letting insurance companies deal with
other types of accidents. The security
evaluation by the Insurance for Highway Safety include the provision of a
forward-collision warning system with automatic braking. The braking system must work efficiently
according to the track tests provided by the insurance institute. Another institute is the Federal National
Highway Traffic Safety Administration. The
board aims at making collision-avoidance systems mandatory in vehicles to ensure
safety and reduced accidents. Linkov
(2015) explains further that despite the high cost of the collision-avoidance
systems, their benefits outweigh the cost since the car owner will be safe and
the systems work efficiently without requiring frequent maintenance. Research conducted by the Insurance Institute
for Highway safety in 2009 showed a reduction in crashes by 7% for vehicles
using the forward-collision warning system and 15% for cars with automatic
braking (Linkov, 2015). Therefore,
vehicles using improved unmanned systems, the number of crashes could be reduced
further. Some of the unmanned systems
that are helpful in reducing accidents include rear cameras and parking assist,
drowsiness detection, lane departure warning, pedestrian detection, and rear
cross-traffic alert. All these systems
work to reduce accidents, and the alarms should have organized warnings so that
they do not irritate the driver making him or her disable them.
The
working principles determine safety and effectiveness of unmanned systems
recommended by various institutions. State
Farm (2017) explains some of the working principles of these systems and how
they ensure safety. The forward
collision warning alerts the driver when his or her car comes near a vehicle up
to a certain distance. If the vehicle
has an automatic braking system, it will stop and avoid a collision, hence
ensuring the safety of the passengers as well as mitigating damage. The adaptive headlights crash avoidance system
works by pointing in the direction of travel. The system assists where there are bends and
curves. State Farm (2017) explains that
vehicles with this application have reduced property damage claims by 10%
showing that it is an effective method of ensuring safety (Linkov, 2015). Blind spot detection systems have sensors that
alert the driver of an object in their blind spot. State Farm (2017) affirms that car owners with
this feature find it helpful as it has made them escape several near accident
events. Hence, car owners and drivers
must understand the working principle before they allow installation.
Accidents
caused by pedestrians who do not follow traffic rules are a significant cause
of high death rates. A pre-crash system
aimed at detecting vehicles and pedestrians is a form of an unmanned system
that should be installed in all vehicles. The pedestrian detection system as discussed
by Hayashi et al., (2013) show that a number of accidents, which mainly occur
at night, have reduced significantly since the vehicle can detect the
pedestrians even when the driver is incapable of seeing them. The pre-crash system has a high deceleration
brake control that reduces the speed by at least 40 kph reducing possible
damage caused by the collision. The
system also has a collision judgment and recognition application that assists
in signaling the brake to start timing earlier so that by the time the vehicle
reaches the pedestrian, its speed has reduced significantly. Therefore, according to Hayashi et al.,
(2013), this system is helpful in ensuring the safety of the pedestrians and
the drivers.
In
summary, these literature reviews have confirmed that unmanned systems are safe
and efficient for motor vehicles and they should be adopted and made mandatory
for all areas they apply. Further
research should be conducted to improve on sensors so that signals are more
efficient. The number of deaths has
reduced noticeably since these systems started to be applied in various areas
making vehicles safer. However, drivers
should still be attentive so in case of a failure of the systems to work, they
will be alert and able act accordingly.
Different theories
are used in the implementation of Collision Avoidance System. Application of tracking methodology and
decision-making are fundamental in designing an effective CAS. Bayesian approach is used to classify parameters
(Lampinen & Vehtari, 2011). Notably,
every parameter of interest is defined as a variable. Since sensors are crucial in the
implementation of the technology, tracking sensors are evaluated in details. Common automotive sensors should be evaluated
to test their effectiveness.
Tracking
applications in Collision Avoidance Systems utilize the extended Kalman filter
(EKF), Kalman filter (KF) and the Particle Filter (PF). Collision avoidance
includes tracking of several objects simultaneously. Multi-target tracking entails determining the
measurement and its respective track. This is referred to as the data association.
Forward Laser
Sensor incorporation in the development of collision avoidance systems provides
an alternative to automotive headway sensors. The laser is cost-effective and its usefulness
in intelligent cruise control and collision avoidance has been immense. Using current technology, the laser technology
is used in the development of multi-zone headway sensors. As well, these systems should not require
professional training for use. The
systems should embed human interface capabilities ensuring simplicity and
intuitiveness. Control inputs from the driver should also override current
control inputs.
Collision
avoidance systems design consist of the decision, obstacle detection,
communication, autonomous maneuvering, and communication model. Obstacle detection models have had continuous
improvements that increase the reliability of autonomous detection such as the Sick
LRS 1000. The LRS 1000 is the most used
laser with the ability to detect obstacles at more than 150 meters.
Vehicle position
is enhanced by the perception system equipment that must be arrayed in the area
of interest. After which, the presence
and the position of obstacles are determined and analyzed. Obstacle-free areas of the road are also
determined to where the vehicle can move without danger. A GPS receiver is used to perform position
calculations. However, in a significant
number of cases, GPS has failed to deliver the required precision. Therefore, an RTK DGPS Topcon GB receiver is
used to update the frequency of position calculations using the Russian and
American GPS satellites that generate accuracy to within one meter (USGS,
2017). The GPS receiver’s role is to
transmit coordinates to the computer. Finally,
the obstacles are placed in the digital map for analysis. Risk and movement calculations utilize the
laser scanner to ensure angle information. Consecutive positions are used to determine
the orientation of the vehicle.
The Decision model
avoids obstacles that are on a single carriageway road. Hence, the system detects the vehicles in the
same lane. The two considerations made
in such a case are braking the vehicle to reduce speed and avoid a crash or
turning the steering and overtake the obstacle. Notably, braking would cause a traffic
interruption. Therefore, it is ideal to
steer the wheel if there is not a vehicle approaching in the opposite
direction. The decision algorithm
chooses the best action based on the information of the surroundings. The surroundings include the road
characteristics and the obstacles detected which are included in the digital
map not limited to road and lane markings and visibility distance.
Decision algorithm
calculates the distance that ensures calculation of the minimum distance that
helps in deciding the safest action. When the best action is braking, the
calculation to decelerate to acquire the speed same as that of the obstacle is
performed. If the appropriate decision is overtaking, the algorithm calculates
the required time and speed to use on the path of another vehicle and its
applicability depending on the obstacles detected on the map.
Risk assessment
results in the decision regarding the action to avoid collision through various
options. Autonomous maneuvering module
assists the driver in performing the right action. If the driver fails to take the right action,
the automatic control executes the maneuver command. As a result, the maneuver control takes the
right action. Therefore, the obstacle detection
algorithm layered at the highest-level, and vehicle control is the lowest
level. The low-level layer receives a
command from the high-level layer. In
most collision avoidance systems, reduction of speed is the main action. However, on many occasions, braking is not the
right action. Hence, some scenarios
require that the vehicle controls take charge of the steering wheel to evade
collisions.
The described
design has been implemented on the testbed vehicle Citroen C3 Pluriel whose
accelerator, steering, and brakes are automated and ready for control by the
collision avoidance system onboard. As
well, the vehicle contains a throttle that is electronically actuated. Throttle position is controlled by the central
engine unit using the received signal from the position of the accelerator
pedal. Assisting the driver is done by bypassing
the electrical signal emanating from the pedal.
The communication
module functions when there are vehicles moving in proximity to collision
avoidance systems installed vehicles. This module communicates to vehicles moving near
CAS installed vehicles. Emergency
maneuver is enabled by the automatic ADAS. GPS signal, speed, and identifier are used to
validate the message confidence. All vehicles
are synchronized ensuring latency performance using GPS timing. Hence, the vehicle receives the emergency
signal indicated by the interface, and the driver is alerted of the risk
scenario. Moreover, the driver would
have more time to take the appropriate action.
Communication
between vehicles will be formed on network mesh devices. A vehicle Ad-hoc Network will be created to
support routing of information between vehicles. Vehicle to vehicle communication will depend
on an operating system using the IEEE 802.15.4 standard to establish and access
the network at 2.4 GHz (Paiva & Fontes, 2014). The wireless network will be created on the
physical link and physical level through routing that forms a mesh protocol. The network platform will support the required
protocols and standards to ensure functionality.
Recommendations
Collision
Avoidance Systems reduce driver error related accidents. Some issues prevent full implementation not
limited to infrastructure, laws, and regulations. Deployment of CAS systems should be
implemented on all automobiles. While a
vehicle with CAS system contributes greatly to the reduction of accidents,
those without the systems reduce the effectiveness of CAS. Hence, all vehicles should have these systems
to ensure there are no ineffective vehicles on the roads. The NHTSA should develop policies guiding the
manufacturers to equip vehicles with collision avoidance systems. One of the challenges that face execution of
unmanned systems technology in automobiles is lack of a controlling agency. In spite of NTSB and NHTSA efforts to develop
standards and protocols to test the CAS systems in the market, defining
criteria and minimum requirements have been a challenge. For instance, passenger vehicle standards and
protocols have been developed while those of commercial fleets have not. Moreover, there is no specific agency of
standardization in the industry to ensure standardized generation of Collision
Avoidance Systems.
Dependability of
CAS systems has been questioned due to various accidents that have happened in
spite of CAS presence. However,
infrastructure could be one of the causes of these accidents. Notably, driver error avoidance through driver
assistance system does not guarantee accident-free roads. Improvement of road infrastructure would help
in demonstrating the real capability of CAS. Unmanned systems technology is not effective
on roads that do not meet specifications required not limited to the size of
the road and lane markings.
Network
communication has been critical to the implementation of intelligent
systems. Besides GPS, research on using
network nodes for vehicular communication should be implemented in standard
Collision Avoidance Systems as in Vehicle Platoon technology (Drummond &
Huff, 2015). The benefit is helping the
communication modules of different CAS systems to communicate. Effective communication results in
well-calculated threat assessment and avoidance plan (Volpe National Transportation Systems Center, 2017). Sensors coverage is limited due to the
projection that would be interrupted by traffic congestion and environmental
factors. Sensors alone cannot determine
the topography of the useable area. Hence,
in the case of collision avoidance, there are risks of incomprehensive
decisions. This is the reason Tesla CAS
has environmental learning capabilities. Permanent obstacles are scanned and maintained
for future references as shared with other Tesla vehicles after an update. Therefore, it is advisable that collision
avoidance systems are embedded with intelligent robotic systems for future risk
mitigation.
Instead of
dependency on the real-time sensor recording, network communication should be
used to help different vehicles to communicate. The communication should be capable of learning
from vehicles on the same route to alert the driver. As well, the network communication should
allow vehicles to exchange GPS information on their location. Notwithstanding, communication between vehicles
in proximity would ensure that there are cooperative mechanisms of mitigating
impending accidents. Vehicles should
communicate their GPS location, their plan or decision the systems are taking,
and respective signals to closer vehicles which will ensure that collision
avoidance is not chaotic and will reduce the chances of casualty.
Conclusion
Unmanned Systems
Technology improves the efficiency and safety of automobiles. Since most accidents are a result of driver
error, providing the driver with automatic assistance would reduce the number
of accidents. Ford Motor Company,
General Motors, and Tesla are among the companies that have been using Collision
Avoidance Systems. Deployment and
installation of CAS systems have contributed to the reduction of accidents. Various technologies have been used to achieve
reliable and dependent safety systems. Audible
systems alone are not as efficient as both audible and self-braking systems. After review, the research has shown a reduced
number of accidents caused by the distracted drivers upon the use of Collision
Avoidance Systems.
After analysis of
the current technology, Tesla, Ford Motor Company, and General Motor’s vehicles
have been preferred due to their safety features. The technology influences the community and
environment in positive ways. Socially,
people accept the system because it reduces frequent death rates by reducing
the occurrence of fatal accidents. The
research has also communicated the designs, concepts, and theories used by General
Motors, Tesla, and Ford Motor Company. Implementation
of Collision Avoidance Systems should be made mandatory by the NHTSA. Data from the National Highway Traffic Safety
Administration (NHTSA) and National Transportation Safety Board (NTSB), shows
that driver error related accidents are frequent. As a result, implementation of dependable
driver assistance systems would reduce the occurrence of these accidents. Finally, through data and critical analysis of
the functionality of the collision avoidance systems, the problem addressed in
this research, “can unmanned systems technology improve safety and efficiency
in automobiles,” it is clear that the systems enhance road safety and
efficiency. A test of proportions has
proven that vehicles without Collision Avoidance Systems cause more accidents
than those with Collision Avoidance Systems.
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