Socio-Technical
Planning of Self Driving Vehicle Technology
Araya
Messa
Colorado Technical University
Instructor: Dr Cynthia Calongne
April-18, 2021
Socio-Technical Planning of Self
Driving Vehicle Technology
It has been observed and
learned that researchers, scholars, business organizations, etc. have been
utilizing technology in order to make their work more effective and increase
its performance. The interaction between humans and technology varies from simple
to that of very complex situations. There is unwind human aspiration to use
technology for their advantages. One example is the technology that enables
cars driverless that is expected to improve human life in transportation. In
this individual project, we will examine socio-technical plan in self-driving
technologies. We will cover the following sections that need to be covered in this
unit 4 and unit 5 individual projects.
1. Introduction
2. Scope
3. Purpose
4. Supporting Forces
5. Challenging Forces
6. Methods
7. Model
8. Analytical Plan
9. Anticipated Results
10. Conclusion
11. Areas of Future Research
12. References
1)
Introduction
In
Sociotechnical System Glossary (15 May 2020), the
term "sociotechnical system" is stated as "a system
incorporating humans and technology but with greater complexity". That can be, however, simplified as it is an engineered system that comprises a combination of
technical and human or natural elements. It integrates an
understanding of the social structures, rights, roles to apprise the design of
systems or approaches that encompass communities of people and technology
(Interaction Design Foundation, n/d). In this project I will be discussing
about the socio-technical aspects that self-driving vehicle technology will
have in respective to our automobility future.
2)
Scope
The objective
of technology is to integrate it into humanoid everyday tasks so that there
could be better productivity, safety, and economy. Artificial Intelligence, Machine
Learning, and Computer Vision are the technological advances that play at the
top here (Udacity India, 2018). Automated vehicles is one of the Computer
Vision implementation. So, arrival of all automated vehicle technology is an
emerging tech with the scope to transform the existing driver-based vehicles to
entirely self-driving road vehicles. This will have a huge impact in our future
transportation. The technology is not fully implemented yet though there are
auto companies that tested at least technological wise. How the transition will
take place is still under discussion. Its
analytical and empirical examination is not fully developed (Fraedrich et al., 2015). But when the technology is fully developed it
will have the following but not limited scopes (Coalition
for Future Mobility, n.d).
1.
Increased transportation Safety: This can be insured by significantly reducing number of car crashes on
roads, identifying driver behavior (reducing the destruction of impaired
driving, drug influenced driving, driving vehicle with unbelted occupants,
speedy driving and distraction), and reducing driver errors.
Figure 1: Road Safety (Source: Adapted from https://coalitionforfuturemobility.com/benefits-of-self-driving-vehicles/)
2.
Greater Independence: The technology can provide greater individual freedom specifically for
disabled people, seniors that would need special assistance.
3.
Saving Money: The technology
could save money by reducing crashing (less maintenance), costs of insurance,
medical bills related to crash injuries etc.
4.
More Productivity: One can save time by utilizing the very convenient including being the
vehicle able to park itself after dropping its occupants, users while in a vehicle can do their other activities such as checking
email without worrying about traffic environment, etc. that increase
productivity.
5.
Reduced Congestion: fully automated self-driving vehicles are designed to maintain a safe and
steady distance with ahead vehicles which enables to minimize number of stopping-and-going
frequencies which in turn can eliminate traffic congestion.
Figure 2: Road Congestion (Source:
Adapted from
https://coalitionforfuturemobility.com/benefits-of-self-driving-vehicles/)
3) Purpose
The purpose of this project is to assess various situations or
scenarios of fully automated vehicles as related to their sociotechnical setting
to see if there is any impact for our future transportation and mobility. Having
explained the details of possible sociotechnical scenarios, we will also
discuss how the technology may be implemented and transformed from conventional
transportation to automated or self-driving system. This project will:
·
presents a multi-level viewpoint
on automobility as an entwined sociotechnical scheme.
·
assess if there will be a fully transition
from traditional to fully self-driving system
·
describe on what self-driving is
meant, inspiration behind it, and where the technology is now in detail
·
discuss possible scenarios that
could implicate on future transportation
4)
Supporting Forces
The idea of developing self-driving vehicles
is driven by several forces some of which are societal or public safety forces,
economical forces, independence service force, and environmental force. These
can be discussed as follows:
·
Public safety force: According to Centers for Disease Control and Prevention (CDC) (2020), 1.35 million people are killed on roadways
around the world each year. Every single
day, it is reported nearly 3,700 people are died globally due crashes that
involve cars, trucks, buses, motorcycles, bicycles, or pedestrians. National
Safety Council (NSC) (2021) reported that in the USA a 24% spike in roadway
death rates is shown in 2020 which is the highest in 96 years. In addition to
that 42,060 people were believed to have died and 4.8 million people were
seriously injured. Crash injuries are labeled
as the eighth top causes of death worldwide for all age groups, and the first
top killer children and young people 5–29 years of age (CDC, 2020).
Figure 3: Road Congestion (Source: Adapted from https://www.nytimes.com/2017/02/15/business/highway-traffic-safety.html)
So, introduction of autonomous vehicles would
improve public safety. Improvement has already been seen in driving safety because
of installing vehicles with such as vehicle cameras, stability control systems,
lane departure systems, etc. (Boudette, 2017). Based
on that study lane departure warning decreases rates of side swipe, single-vehicle,
and head-on crashes of all severe accidents by 11% and rates of injury crashes
by 21%. The autonomous vehicles are being designed with sophisticated
communication technologies, i.e, communications of vehicles to another vehicles
(V2V), vehicles to road infrastructures (V2I), vehicles to pedestrians (V2P),
and vehicles to cellular networks (V2N) (Casey, 2018). All these use cases are
called communication of vehicle to everything (V2X). Hence, V2X is expected to
improve transport safety significantly. National Highway Traffic Safety
Administration states that if V2X technologies are implemented, it would be
possibly to address 81 percent of light traffic crashes.
·
Economical forces: Based on CDC (2020), it is projected that deadly and non- deadly vehicle-crash
injuries will cause the world economy to need roughly $1.8 trillion by 2030.
The cost, the time we spend on driving without doing anything (that we could be
more productive when we entered into full autonomous driving system) all impact
our economic system. Introducing full
autonomous system would be able to save us in our economy.
· Independence service: driverless vehicles could also benefit our
vulnerable society such as people with disabilities, or people that lost mental
freedoms or seniors. Driverless cars would give service for those users to independently
utilize the technology (Sefanov, 2017).
· Environmental force: Some studies believe that self-driving vehicles are more environmental-friendly. Automotive industries would consider redesigning their vehicle production to consume optimum energy-saving systems such as by utilizing renewable energy sources. This could significantly contribute towards a greener future (Environment, n.d). Based on U.S. Department of Energy (DOE), autonomous vehicles could lower tbbhe current energy consumption rates by 90 to 200% (Environment, n.d). Also, driverless vehicles are designed to be much smaller size than the conventional ones which means they will take less fuel and energy, less parts (less plastic material) that all will be vital to reduce environmental pollution.
5)
Challenging Forces
As explained by Plumer (2016), there are 5 big challenges that self
driving might be faced with:
1. Adopting and controlling maps for autonomy cars is tough task
2. Challenging in multifaceted social communications (such as status of pedestrians standing at the edge of cross walk, feeling of road condition, etc.) that are hard for robots to know like we humans do
3. Hardship in unconditional or bad weather
4. Requiring to adopting policy or regulations before implementing the technology
5. Cybersecurity might be an issue
6)
Methods
That indicates though building an effective and perfective group
is not that straightforward, result on decision making from a collective idea
is most of the time so much effective. Once one has had a practical team who
can act optimally together, one needs to start making some group decisions
(Andrei, 2020). Group decision-making techniques are approaches for structuring
team members’ connections to improve the value of a collective decision by
minimizing roadblocks and barriers (“Group Decision-Making Techniques”,
n/d). The following are some of the popular group decision making techniques:
· Delphi Method known as “iterative
convergence”- that relies on the expertise of a team to
assist in coming to complex decisions.
· Brainstorming- each group members
need to generate thought ideas and they can use that brain storming ideas as
bases.
· Nominal Group Technique (NGT) -
the Nominal Group Technique is essentially a more structured form of
brainstorming.
· Ranking- this is based on participants’ ranking average scores
· Weighted Scoring - When applying this system to
one’s decision-making process, the assigned team must evaluate each item on the
list of solutions and assign criteria like Business Value, Costs, and Risks.
· Stepladder Technique: The stepladder
technique is a group decision-making strategy that staggers the entry of
members into a group and allows groups to form a final decision collaboratively
and collectively rather than having an outside party derive the group
decision (“Group Decision-Making Techniques”, n/d).
In
this socio-technical study of self-driving technology, two group decision
techniques can be alternatively utilized:
In the socio-technical plan of innovating robotics, two methods can be
used: Delphi Technique, and Nominal Group Technique. These could be practical
to adopt in a complex process such as sociotechnical plan. High level
professional members in the field probably live in different areas in which the
process of either Delphi technique or nominal group technique are convenient. The
Delphi technique provides a board of directors with a systematic, simplified
structure for generating, examining, and prioritizing ideas and solutions
(Direct Point, n/d). This is a technique that is highly needed for boards
tasked with making high level decisions. Decision-makers utilize a series of
questionnaires to extract ideas and solutions with an anonymous panel of
experts. The panel’s anonymity is upheld by a coordinator who merely serves as
a cooperator between the two groups (between decision-makers and anonymous
panel of experts). The coordinator can manage the questionnaire and cleans up
responses for clarity and relevancy before sending the responses to
decision-makers. Panelists could provide additional commentary on their own
responses and the responses of other members. Nominal Group Technique on the
other hand is a type of brainstorming (“Group Decision-Making Techniques”, n/d)
created to overcome several decision-making roadblocks. The highly structured
and task-focused nature of this strategy is thought to encourage the efficient
use of time by reducing the tendency for nonproductive departures and hostile
arguments. Like Delphi method, members may also experience an increased sense
of accountability and a decreased propensity for social loafing, because
members are required to publicly state their written ideas.
7)
Models
As one of the human freedoms, humans have the
right to move to and transportation in different modes plays a huge role in our
human societies. Technology plays in the advancement of transportation so that
we move in conveniently, comfortably, and timely manner. Usually the
integration of human brain and machines work effectively. For instance, there
are automobile manufacturers that believe fully automated vehicles could be
less effective and maintainable than the one performed by humans and machines
together. This tells us that there is any escape of human task but rather
integration technology and human (Hancock,
et al., 2019) which can be represented as in Figure 4.
Figure 4: A contrast between the rates of progress in capability
of humans and machines over the recent industrialized epoch (Source: Adapted
from https://www.pnas.org/content/116/16/7684)
In a sociotechnical model, there three
different elements or approaches: Technology
approach, people approach, and the socio-technical approach (Tasmin, 2010). The integration between human and
technology in automated vehicle driving may be represented as the model usually
known as Knowledge Management (KM) model. This interwoven model is explained by
Tasmin (2010) and has three components.
·
Infoculture- this includes social culture and organizational background to share knowledge
·
Infrastructure- this comprises all the technology adopted and
·
Infostructure- this consists of all the protocols, policies, and means to measure.
The socio-technical approaches provide tools,
devices, and knowledge to transform inputs (integrations) into innovation
capability or performance. This is clearly put in Figure 5 below.
Figure 5: Sociotechnical Model (Source: Adapted from https://www.researchgate.net/publication/266491558_Applicability_of_Socio-Technical_Model_STM_in_Working_System_of_Modern_Organizations)
The integrability between society and
technology can be also be represented as Figure 6 below (Tasmin, 2010). The intersection between the sociology and
technology is to represent the sociotechnical interaction which may need to
study further.
Figure 6: Interactional
overlapping between Sociology and Technology (Source: Adapted from
https://www.researchgate.net/publication/266491558_Applicability_of_Socio-Technical_Model_STM_in_Working_System_of_Modern_Organizations)
8)
Analytical
Plan
The analytical plan in sociotechnical systems
can be explained with multi-level perspective (MLP) (Fraedrich et al., 2015) to show how sociological elements are integrated in a
sociotechnical process. Such interactions are the combination of not only
development, production, and modification of a sociotechnical system, but there
include different perceptions, interests, values and norms, strategies, preferences,
resources, etc. In automated driving technology for example it is not that
technology that brings the sociotechnical changes but that incorporate other complex
social factors and their intentions. All these factors transform societal
environment into another form of existence.
Therefore, Fraedrich
et al. (2015) presented the MLP to display such complex change. MLP
consists of three analytical levels:
·
Regime- This explains
elements such as societal functions and values,
practices, regulations, influential routines, social groups, material
and organizational resources, cultural meaning, behavioral standards, etc.,
·
Landscape- this is a
subset of a ‘regime’ that describes aspects and characteristics of a system that
is could not be easily changed such as demographic change, spatial structures,
etc.
·
Niche- these are
also derived from a ‘regime’ that can be defined as secured spaces in the
sociotechnical scheme. This are sub sociotechnical systems that may comprise
local practices, specific technologies, and individual agents.
The analytical trio of the MLP is significant
approach to understand a change in a sociotechnical system: that is a change
that does not happen overnight instead it is a process that evolve gradually.
MLP in automobile technology may be represented as in Figure 7 below.
Figure 7: Multi-Level Perspective on automobility (Source:
Adapted from https://elib.dlr.de/99435/1/Fraedrich_Beiker_Lenz_2015_EurJFuturesRes_3-1.pdf)
In our future transportation in terms of automated
driving dynamics, three possible scenarios would be mentioned listed (Fraedrich
et al., 2015):
·
Evolution- this is the path itself that is the process of transportation evolution
from conventional transportation system to that of fully automated (driverless)
driving technology
·
Revolution- This the integrating of other agencies other than transportation systems
such internet
·
Transformation: This transforming personal mobility either to public transportation with
the automated techs or integrate the automating technology to the personal
mobility systems
Moreover, these scenarios are anticipated in
terms of transportation development, however, other possible scenarios may be emerged
in the future as the future is a future with a tone of uncertainties.
9)
Anticipated Results
The anticipated results in the sociotechnical
plan of self-driving would be complex. After researching the already developed
and under continuous testing self-driving vehicles such as by Google, Uber,
Tesla, etc., introduction of automated technology looks to have a promise to improve public safety, increase societal productivity,
and give service independence especially for disabled people, seniors, probably
those that do not hold any license etc.
The sociotechnical changes of automated
technology are a process that evolves slowly and we will probably see no escape
of human task though the role of human assistantship to machine would be
greatly minimized. So, the definition of
sociotechnical aspect here will be more the machine guided service-and its
function to benefit human relationship.
10)
Conclusion
The socio-technical model plan for
self-driving vehicular technology is complex. When viewing at the
human-technology dynamic interaction development, it can be concluded that it
is a gradual process especially in this car automation technology. However,
when implemented it would bring a significant contribution to improve public
safety, increase societal productivity, and give service independence especially
for disabled people, seniors, probably those that do not hold any license etc.
Utilization of technology by society displays the advancement of technology
guided human life. This interaction can easily be modeled using available socio-technical
model (STM). The evolving of this interaction or whether technology and human
tasks can be seen separately to effectively perform any intended task need to
be further studied.
11)
Areas of Future Research
In the sociotechnical system of self-driving vehicles-human interaction, the
following need be further studied:
1.
The integration between sociology and technology (sociotechnical
interaction) need to be studied further. Will technology illuminate the human
task in the human-technology integration? For example, will robotted vehicles
will replace all things human brain would see on the transportation system,
i.e. at all conditions (bad road system, weather condition, vehicle-to
everything communication, etc.)? This needs to be studied in the future.
2. The scenarios that were proposed here (Evolution, Revolution and Transformation) may not be the only scenarios that could be seen in the future. So, further study would be recommended here.
References:
1.
Fraedrich et al., 2015. Transition pathways to fully
automated driving and its implications for the sociotechnical
system of automobility. https://elib.dlr.de/99435/1/Fraedrich_Beiker_Lenz_2015_EurJFuturesRes_3- 1.pdf.....self dr
2. Coalition For Future Mobility (n.d). Highly automated technologies, often
called self-driving cars, promise a range
of potential benefits
https://coalitionforfuturemobility.com/benefits-of-self-driving-vehicles/
3. Udacity, India, (2018). Scope of
Self-Driving cars in India.
https://medium.com/@UdacityINDIA/scope-of-self-driving-cars-in-india- 5dff321436b#:~:text=It%20has%20video%20cameras%20installed,of%20roads%20and %20lane%20markings.
4. CDC, (2020). Road Traffic Injuries
and Deaths—A Global Problem. https://www.cdc.gov/injury/features/global-road-safety/index.html
5. NSC, (2021). Motor Vehicle Deaths in
2020 Estimated to be Highest in 13 Years, Despite Dramatic Drops in Miles Driven. https://www.nsc.org/newsroom/motor-vehicle-deaths-2020- estimated-to-be- highest#:~:text=Itasca%2C%20IL%20%E2%80%93%20For%20the%20first,frequently%20 because%20of%20the%20pandemic
6. Boudette, N., (2017). U.S. Traffic
Deaths Rise for a Second Straight Year. https://www.nytimes.com/2017/02/15/business/highway-traffic-safety.html
7. Casey, J., (2018). The future of
autonomous vehicles. https://www.roadtraffic- technology.com/comment/future-autonomous-vehicles/.
8.
Sefanov, E.
(2017). The Driving Force Behind Autonomous and Connected Vehicles. https://blogs.perficient.com/2017/11/01/the-driving-force-behind-autonomous-and- connected-vehicles/
9. Environment, (n.d). Will self-driving
vehicles be eco-friendly?. https://www.environment.co.za/eco-green-living/will-self-driving-vehicles-be-eco- friendly.html#:~:text=Overall%20%E2%80%93%20driverless%20vehicles%20will%20be,it %20is%20to%20the%20environment.
10. Plumer, B., (2016). 5 big challenges
that self-driving cars still have to overcome. https://www.vox.com/2016/4/21/11447838/self-driving-cars-challenges-obstacles.
11. Hancock, P., et al. (2019). On the
future of transportation in an era of automated and autonomous vehicles. Proceedings of the National Academy
of Sciences Apr 2019, 116 (16) 7684-7691; https://www.pnas.org/content/116/16/7684
12. Tasmin, R., et al., (2010).
Applicability of Socio-Technical Model (STM) in Working System of Modern Organizations. Journal of
Techno-Social. 2. https://www.researchgate.net/publication/266491558_Applicability_of_Socio- Technical_Model_STM_in_Working_System_of_Modern_Organizations
