Thursday, May 13, 2021

Futuring and Innovation Unit 4 IP and Unit 5 IP

 

 

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

 

 

 

Futuring and Innovation Unit 4 IP and Unit 5 IP

    Socio-Technical Planning of Self Driving Vehicle Technology Araya Messa Colorado Technical University Instructor:   Dr Cynthia C...