{Alawadhi, M., Almazrouie, J., Kamil, M., & Khalil, K. A. (2020). A systematic literature review of the
factors influencing the adoption of autonomous driving. International Journal of System Assurance
Engineering and Management, 11(6), 1065–1082. https://doi.org/10.1007/s13198-020-00961-4
Abstract
A total of 14 factors were identified from 85 articles published in many journals.
These 14 factors can be sorted into 4 readiness categories:
1. Technology (vehicle technology, safety and ethics)
2. Infrastructure (communication, technology of roads and traffic signs and cost of
infrastructure
3. Legal (liability, privacy and cybersecurity)
4. Acceptance (consumer acceptance, marketing and advertising, cost of Avs and trust)
Stakeholders will need to work on these 4 areas to ensure successful mass adoption of Avs and
decrease the chance of failure.
On what is autonomous technology
The term “autonomous technology” is prevalent in various industries; it involves transforming the
capabilities of machinery and allowing it to play an independent role. The recent advancements in
the fields of computation and sensory technology have led to the emerging realization of
autonomous vehicle (AV) development.
From its use in manufacturing usage to its application in vehicles, autonomous technology is at the
center of global research, with emphasis attributed to the need to reduce risk and increase
reliability.
Importance/Advantages of AV
Transportation is considered as a means to prosperity for societies, although it poses some risks
and comes with external costs or externalities that are hidden and indirect costs that are imposed
on society such as traffic congestion, pollution, accidents and human casualties.
The literatures perceives AV technology as having the potential to substantially reduce many of
these existing negative externalities.
1. AVs are expected to reduce traffic congestion by increasing road throughput capacity
through more efficient vehicle operation and by reducing vehicle crashes
2. AVs are expected to reduce pollution by enabling the use of alternative fuels, to decrease
fuel consumption by improving driving efficiency, and to reduce accidents, as 90% of
accidents are the result of human error.
Other benefits
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Increasing accessibility and mobility and even improving land use
The concept behind AVs is to partially o fully replace human intervention with electronic and
mechanical devices, thus making the transport driverless.
Current context of Autonomous Tech
Today the use of autonomous technology is widespread, although it is restricted in the ways in which
it is applied. These include:
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Assistive parking
Cruise control
Emergency braking
Sensor usage
Cloud connect and cameras have played a positive role in improving the overall performance which
can be used in AVs.
Key components in AV classification
The Society of Automotive Engineers (SAE) has established a classification system to assess the level
of autonomy of driverless cars. In the SAE system, the level of autonomy is classified on a scale from
0 to 5, where 0 means the car’s systems may issue warnings, but there is no automatic control, and
five means the car is automatic with no human intervention required in any situation.
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Level 0: The car is totally controlled by the driver with no automatic intervention.
Level 1: One aspect of the car is automatic.
Level 2: The car has the ability to control steering and speed. Self-parking is an example of
this level, in which the driver still must control the steering.
Level 3: The car can take full control in decision-making, such as in overtaking slow-moving
vehicles.
Level 4: The car is automated enough to be self-driven in most situations, but if
circumstances are not suitable, the driver can take control.
Level 5: This is the maximum level of autonomy, in which no driver is needed, and the car is
driven robotically.
The most important components for this classification are:
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Technology: The level of technology used is one of the main components by which AVs are
classified
Human intervention: The level of human intervention needed in a car defines its
classification and how much autonomy it has.
Circumstances: The circumstances in which a car is enabled to work automatically or with
human intervention are also key components when classifying AVs
Technology readiness to adopt AVs
Since technology is the basis on which AVs are developed, these factors (vehicle technology, safety
and ethics) need to be effectively addressed in the implementation of AVs.
Vehicle technology is a very important factor which consists of many components like sensors,
radar, GPS and LIDAR.
AVs are expected to be safer than manual vehicles. They need to identify the current state of the
vehicle as well as the environment they are in. Moreover, ethics must be considered when
programming the AVs.
Vehicle Technology:
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Autonomous vehicles' knowledge consist of perception, planning and control function to
enable effective driving.
Tasks AVs are supposed to perform: Automatic braking, lane-keeping, adaptive cruise
control, imaging and detecting the are through which they move.
Many researchers have suggested approaches using camera sensors. However, the sensors
were found to be vulnerable to environmental conditions of rain, sunlight, shadow, and
intensity of light.
Path planning for AVs involves perception and detection of obstacles to reach the
destinations safely as well as to achieve path planning and motion control.
Real time intelligence is needed to be developed which can sense and interpret information
and take necessary actions in order to achieve smooth navigation.
Safety:
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Perception, planning, and development of AVs have seen many recent advances which
helped in improving functional capabilities as well as other features of AVs with several
advanced prototypes already running on streets.
AVs are required to respond in dynamic environments and need models and methods to
react in unpredictable situations as well as ensuring timely behavior in complex urban
scenarios.
Accurate perception is required for informed decision-making and current state-of-the-art
computer vision is still unable to achieve acceptable lowest error rates.
Infrastructure readiness to adopt AVs
Communication, technology of roads and traffic signs, and the cost of infrastructure are the main
factors to be considered in this category.
Infrastructure needs to be built to meet the new requirements of AVs.
Technology of roads and traffic signs need to have some upgrades to be compatible with AVs.
AVs require new laws that are suitable for the new situation.
User acceptance readiness to adopt AVs
Consumer acceptance, marketing and advertising, cost of AVs, and trust.