Autonomous Vehicles for Smart and Sustainable Cities: An In-Depth Exploration of Privacy and Cybersecurity Implications

Lim, Hazel Si Min; Taeihagh, Araz

doi:10.3390/en11051062

Cited by 143 publications

(66 citation statements)

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“…The implementation of vehicles at Levels 4 and 5 is now possible due to rapid technological advancements in hardware and software systems-sensor-fusion technology and computer vision allow the vehicle to detect, trace and manoeuvre safely around obstacles and under a wide range of environmental conditions [42,43]; High-performance computing enables the vehicle to process vast amounts of data to understand its environment and make spontaneous driving decisions; and communication technologies enable the vehicle to exchange information with and learn from other vehicles [44,45]. Given the accelerating technological developments and roll-out of AV trials, AV technology is expected to advance rapidly and surpass human capabilities over time [38].…”

Section: Avsmentioning

confidence: 99%

“…The notion of sustainable cities emerged in the 1990s [52] and while various definitions of the term exist, sustainability may be understood as a state in which a city's social, economic and environmental needs can be met while ensuring the overall system's self-sufficiency and continuous improvement [45,53]. Thus, sustainability entails the simultaneous attainment of economic sustainability through increased efficiency and economic growth, social sustainability through improved equity and public well-being, and environmental sustainability through the smart use of resources [53,54].…”

Section: Algorithmic Decision-making In Avs For Smart and Sustainablementioning

confidence: 99%

“…At Level 3 (conditional automation), the vehicle can perform all dynamic driving Sustainability 2019, 11, 5791 3 of 28 tasks such as steering, acceleration, and monitoring the environment, but the human driver is required to resume control occasionally [39,40]. Vehicles classified under Levels 4 and 5 of autonomy are considered highly and fully autonomous respectively as they can engage in all the driving tasks without human intervention [41].The implementation of vehicles at Levels 4 and 5 is now possible due to rapid technological advancements in hardware and software systems-sensor-fusion technology and computer vision allow the vehicle to detect, trace and manoeuvre safely around obstacles and under a wide range of environmental conditions [42,43]; High-performance computing enables the vehicle to process vast amounts of data to understand its environment and make spontaneous driving decisions; and communication technologies enable the vehicle to exchange information with and learn from other vehicles [44,45]. Given the accelerating technological developments and roll-out of AV trials, AV technology is expected to advance rapidly and surpass human capabilities over time [38].…”

mentioning

confidence: 99%

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Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities

Lim

Taeihagh

2019

Sustainability

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Autonomous Vehicles (AVs) are increasingly embraced around the world to advance smart mobility and more broadly, smart, and sustainable cities. Algorithms form the basis of decision-making in AVs, allowing them to perform driving tasks autonomously, efficiently, and more safely than human drivers and offering various economic, social, and environmental benefits. However, algorithmic decision-making in AVs can also introduce new issues that create new safety risks and perpetuate discrimination. We identify bias, ethics, and perverse incentives as key ethical issues in the AV algorithms' decision-making that can create new safety risks and discriminatory outcomes. Technical issues in the AVs' perception, decision-making and control algorithms, limitations of existing AV testing and verification methods, and cybersecurity vulnerabilities can also undermine the performance of the AV system. This article investigates the ethical and technical concerns surrounding algorithmic decision-making in AVs by exploring how driving decisions can perpetuate discrimination and create new safety risks for the public. We discuss steps taken to address these issues, highlight the existing research gaps and the need to mitigate these issues through the design of AV's algorithms and of policies and regulations to fully realise AVs' benefits for smart and sustainable cities.Sustainability 2019, 11, 5791 2 of 28 surroundings and algorithms that process the data, make, and execute driving decisions through the vehicle's actuators. The quality of data retrieved by the AV's sensors is critical for decision-making [21], and the efficiency, precision and reliability of decision-making algorithms allows AVs to surpass the typical human driver in performing driving tasks [22]. A major component in AVs is machine-learning (ML) [23] algorithms that continuously learn and adapt to new information, which is essential for responding to unexpected situations and providing on-demand transportation services [24]. Algorithms' independence from human input and ML's data-driven nature allows AVs to significantly reduce or eliminate human errors that have been responsible for 90% of road fatalities, such as speeding, alcohol impairment, distractions and induced fear [25,26].However, an overemphasis on technological solutions alone for economic development could risk neglecting social and environmental considerations and thus hinder true "smartness" [27]. Scholars have cautioned against rushing to develop smart mobility solutions such as AVs without being prepared to manage their potential "negative externalities" [1,28]. In particular, issues in algorithmic decision-making in AVs can have undesirable effects on safety and equity. Firstly, data mining processes in AVs are susceptible to biases that lead algorithms to prioritise the safety of certain groups of road users over others and thus, perpetuate discrimination [29,30]. Secondly, many scholars stress the need to design algorithms with ethical considerations to ensure that AVs make ethical driving dec...

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Section: Avsmentioning

confidence: 99%

Section: Algorithmic Decision-making In Avs For Smart and Sustainablementioning

confidence: 99%

mentioning

confidence: 99%

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Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities

Lim

Taeihagh

2019

Sustainability

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“…Unauthorised private data sharing, hacking and cyberterrorism are threats that could be easily associated with a less effective protection system for CAVs. Insufficient cybersecurity of CAVs can also expose a nation's critical infrastructure to cyber threats that can disrupt the delivery of critical services and have a detrimental impact on the entire society's wellbeing (Lim and Taeihagh, 2018). People may need to be convinced that CAVs provide a safe and secure environment that at the same time respects their privacy before they are to fully embrace them.…”

Section: Myth Five: Physical or Cyber Threats Are Smaller Barriers Thmentioning

confidence: 99%

Examining the myths of connected and autonomous vehicles: analysing the pathway to a driverless mobility paradigm

Dani

Nikitas

Njoya

2019

IJATM

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Connected and autonomous vehicles (CAVs) could become the most powerful mobility intervention in the history of human race; possibly greater than the conception of the wheel itself or the shift from horse-carriages to automobiles. Despite CAVs' likely traffic safety, economic, environmental, social inclusion and network performance benefits their full-scale implementation may not be as predictable, uncomplicated, acceptable and risk-free as it is often communicated by a large share of automotive industries, policy-makers and transport experts. Framing an 'unproven', 'disruptive' and 'life-changing' intervention, primarily based on its competitive advantages over today's conventional automobile technologies, may create misconceptions, overreaching expectations and room for errors that societies need to be cautious about. This article 'tests' eleven myths referring to an overly optimistic CAVs' development and adoption timeline. This approach highlights unresolved issues that need to be addressed before an inescapable CAV-based mobility paradigm transition takes place and provides relevant policy recommendations of how to achieve that.

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“…Autonomous vehicles may radically challenge the way cities are used and designed, reducing the need for private car ownership, accelerating the shift to electric propulsion and halving the number of private passenger vehicles (Milakis et al, 2017). Conversely they may enable super-commuting, release pent up demand for car use and increase emissions and traffic congestion (Lim and Taeihagh, 2018). Cities are where future technologies are being developed and tested, with often mixed results for sustainability (Cugurullo, 2016).…”

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confidence: 99%

Governing Cities for Sustainability: A Research Agenda and Invitation

Evans

2019

Front. Sustain. Cities

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Eighty-five per cent of humanity-some nine billion people-will live in cities by the end of this century (OECD Publishing, 2015). While uncertainty surrounds any attempt to look this far into the future, an unquestionable consequence of this oft quoted statistic is that securing the sustainability of our planet is increasingly an urban challenge. Environmental protection, green economic growth, social equality, clean energy, decarbonization, mobility, and health are all best addressed in cities (Short, 2017;Bai et al., 2018). If cities can become sustainable, then we will have gone a long way to fixing many of the problems that we and our fellow species face. The question of course is how to do this. While we now know what the core problems and many of their solutions are, change is not happening at anywhere near the scale and pace required. Cities need to rapidly curb greenhouse gas emissions, reinvent their economies, and address growing inequalities, all in the face of obdurate infrastructures and buildings, huge demographic shifts, rapidly evolving technologies and hostile funding conditions.As the practice of organizing collective action to steer society toward specific shared goals (Kooiman, 1993), governance is critical in enabling cities to address these challenges. Governments, communities, NGOs, private companies, utilities, universities, unions, and others are realizing the need to work collectively to respond to the pace, scale and scope of urban change. UN Habitat recognizes that working with cities is the best way to address global challenges (Parnell, 2016;Acuto, 2018), while the OECD Publishing (2015) highlights that good governance is particularly crucial in cities due to their density of connections and role as key drivers of development. The focus of governance on who is involved in making decisions and what kinds of knowledge gets to count fundamentally frames what is and is not possible in cities, and by extension enables us to understand how they might be reconfigured to make more sustainable actions possible. Governance underpins the UN Sustainable Development Goals through the enabling goal 17 on strengthening partnerships, while cities have emerged as leaders in the field of climate action through networks such as the C40 Cities Climate Leadership Group, which connects 90 of the world's most influential cities, representing more than 650 million people and one quarter of the global economy. The importance of cities to the sustainability agenda is further heightened by the resurgence of populist national governments around the world that are apathetic or openly hostile to the environmental agenda. The future sustainability of humankind, in both the mundane sense of how day-to-day existence will be for the majority of us to the viability of the planet itself, will be shaped in and by cities. Understanding cities and how they can be governed in more innovative, inclusive and effective ways is now a global sustainability priority in ways that it has not been before.The Governance and Cities s...

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Autonomous Vehicles for Smart and Sustainable Cities: An In-Depth Exploration of Privacy and Cybersecurity Implications

Cited by 143 publications

References 58 publications

Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities

Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities

Examining the myths of connected and autonomous vehicles: analysing the pathway to a driverless mobility paradigm

Governing Cities for Sustainability: A Research Agenda and Invitation

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