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- All Subjects: engineering
- Creators: Berman, Spring
- Member of: Theses and Dissertations
- Resource Type: Text
- Status: Published
However, road driving at any reasonable speed involves some risks. Therefore, even with high-tech AV algorithms and sophisticated sensors, there may be unavoidable crashes due to imperfection of the AV systems, or unexpected encounters with wildlife, children and pedestrians. Whenever there is a risk involved, there is the need for an ethical decision to be made [33].
While ethical and moral decision-making in humans has long been studied by experts, the advent of artificial intelligence (AI) also calls for machine ethics. To study the different moral and ethical decisions made by humans, experts may use the Trolley Problem [34], which is a scenario where one must pull a switch near a trolley track to redirect the trolley to kill one person on the track or do nothing, which will result in the deaths of five people. While it is important to take into account the input of members of a society and perform studies to understand how humans crash during unavoidable accidents to help program moral and ethical decision-making into self-driving cars, using the classical trolley problem is not ideal, as it is unrealistic and does not represent moral situations that people face in the real world.
This work seeks to increase the realism of the classical trolley problem for use in studies on moral and ethical decision-making by simulating realistic driving conditions in an immersive virtual environment with unavoidable crash scenarios, to investigate how drivers crash during these scenarios. Chapter 1 gives an in-depth background into autonomous vehicles and relevant ethical and moral problems; Chapter 2 describes current state-of-the-art online tools and simulators that were developed to study moral decision-making during unavoidable crashes. Chapters 3 focuses on building the simulator and the design of the crash scenarios. Chapter 4 describes human subjects experiments that were conducted with the simulator and their results, and Chapter 5 provides conclusions and avenues for future work.
The built environment is responsible for a significant portion of global waste generation.
Construction and demolition (C&D) waste requires significant landfill areas and costs
billions of dollars. New business models that reduce this waste may prove to be financially
beneficial and generally more sustainable. One such model is referred to as the “Circular
Economy” (CE), which promotes the efficient use of materials to minimize waste
generation and raw material consumption. CE is achieved by maximizing the life of
materials and components and by reclaiming the typically wasted value at the end of their
life. This thesis identifies the potential opportunities for using CE in the built environment.
It first calculates the magnitude of C&D waste and its main streams, highlights the top
C&D materials based on weight and value using data from various regions, identifies the
top C&D materials’ current recycling and reuse rates, and finally estimates a potential
financial benefit of $3.7 billion from redirecting C&D waste using the CE concept in the
United States.
Although these commercial and research systems are still in testing, it is important to understand how AVs are being marketed to the general public and how they are perceived, so that one day they may be effectively adopted into everyday life. People do not want to see a car they do not trust on the same roads as them, so the questions are: why don’t people trust them, and how can companies and researchers improve the trustworthiness of the vehicles?
What should the control system bandwidth be vis--vis the flapping frequency (so that averaging the nonlinear system is valid)?
When is first order averaging sufficient? When is higher order averaging necessary?
When can wing mass be neglected and when does wing mass become critical to model?
This includes how and when the rules given can be tightened; i.e. made less conservative.