Autonomous vehicles (AVs) should reduce traffic accidents, but they will sometimes have to choose between two evils, such as running over pedestrians or sacrificing themselves and their passenger to save the pedestrians. Defining the algorithms that will help AVs make these moral decisions is a formidable challenge. We found that participants in six Amazon Mechanical Turk studies approved of utilitarian AVs (that is, AVs that sacrifice their passengers for the greater good) and would like others to buy them, but they would themselves prefer to ride in AVs that protect their passengers at all costs. The study participants disapprove of enforcing utilitarian regulations for AVs and would be less willing to buy such an AV. Accordingly, regulating for utilitarian algorithms may paradoxically increase casualties by postponing the adoption of a safer technology.

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The social dilemma of autonomous vehicles

Safety critical systems involve the tight coupling between potentially conflicting control objectives and safety constraints. As a means of creating a formal framework for controlling systems of this form, and with a view toward automotive applications, this paper develops a methodology that allows safety conditions—expressed as control barrier functions —to be unified with performance objectives—expressed as control Lyapunov functions—in the context of real-time optimization-based controllers. Safety conditions are specified in terms of forward invariance of a set, and are verified via two novel generalizations of barrier functions; in each case, the existence of a barrier function satisfying Lyapunov-like conditions implies forward invariance of the set, and the relationship between these two classes of barrier functions is characterized. In addition, each of these formulations yields a notion of control barrier function (CBF), providing inequality constraints in the control input that, when satisfied, again imply forward invariance of the set. Through these constructions, CBFs can naturally be unified with control Lyapunov functions (CLFs) in the context of a quadratic program (QP); this allows for the achievement of control objectives (represented by CLFs) subject to conditions on the admissible states of the system (represented by CBFs). The mediation of safety and performance through a QP is demonstrated on adaptive cruise control and lane keeping, two automotive control problems that present both safety and performance considerations coupled with actuator bounds.

https://ieeexplore.ieee.org/ielaam/9/7993115/7782377-aam.pdf

Control Barrier Function Based Quadratic Programs for Safety Critical Systems

The introduction of connected and autonomous vehicles will bring changes to the highway driving environment. Connected vehicle technology provides real-time information about the surrounding traffic condition and the traffic management center’s decisions. Such information is expected to improve drivers’ efficiency, response, and comfort while enhancing safety and mobility. Connected vehicle technology can also further increase efficiency and reliability of autonomous vehicles, though these vehicles could be operated solely with their on-board sensors, without communication. While several studies have examined the possible effects of connected and autonomous vehicles on the driving environment, most of the modeling approaches in the literature do not distinguish between connectivity and automation, leaving many questions unanswered regarding the implications of different contemplated deployment scenarios. There is need for a comprehensive acceleration framework that distinguishes between these two technologies while modeling the new connected environment. This study presents a framework that utilizes different models with technology-appropriate assumptions to simulate different vehicle types with distinct communication capabilities. The stability analysis of the resulting traffic stream behavior using this framework is presented for different market penetration rates of connected and autonomous vehicles. The analysis reveals that connected and autonomous vehicles can improve string stability. Moreover, automation is found to be more effective in preventing shockwave formation and propagation under the model’s assumptions. In addition to stability, the effects of these technologies on throughput are explored, suggesting substantial potential throughput increases under certain penetration scenarios.

Influence of connected and autonomous vehicles on traffic flow stability and throughput

Intelligent vehicle cooperation based on reliable communication systems contributes not only to reducing traffic accidents but also to improving traffic flow. Adaptive cruise control (ACC) systems can gain enhanced performance by adding vehicle-vehicle wireless communication to provide additional information to augment range sensor data, leading to cooperative ACC (CACC). This paper presents the design, development, implementation, and testing of a CACC system. It consists of two controllers, one to manage the approaching maneuver to the leading vehicle and the other to regulate car-following once the vehicle joins the platoon. The system has been implemented on four production Infiniti M56s vehicles, and this paper details the results of experiments to validate the performance of the controller and its improvements with respect to the commercially available ACC system.

/pdf/cooperative-adaptive-cruise-control-in-real-traffic-35mggeon75.pdf

Cooperative Adaptive Cruise Control in Real Traffic Situations

The design of a cooperative adaptive cruise-control (CACC) system and its practical validation are presented. Focusing on the feasibility of implementation, a decentralized controller design with a limited communication structure is proposed (in this case, a wireless communication link with the nearest preceding vehicle only). A necessary and sufficient frequency-domain condition for string stability is derived, taking into account heterogeneous traffic, i.e., vehicles with possibly different characteristics. For a velocity-dependent intervehicle spacing policy, it is shown that the wireless communication link enables driving at small intervehicle distances, whereas string stability is guaranteed. For a constant velocity-independent intervehicle spacing, string stability cannot be guaranteed. To validate the theoretical results, experiments are performed with two CACC-equipped vehicles. Implementation of the CACC system, the string-stability characteristics of the practical setup, and experimental results are discussed, indicating the advantages of the design over standard adaptive-cruise-control functionality.

String-Stable CACC Design and Experimental Validation: A Frequency-Domain Approach

Cooperative adaptive cruise control (CACC) is an extension of ACC. In addition to measuring the distance to a predecessor, a vehicle can also exchange information with a predecessor by wireless communication. This enables a vehicle to follow its predecessor at a closer distance under tighter control. This paper focuses on the impact of CACC on traffic-flow characteristics. It uses the traffic-flow simulation model MIXIC that was specially designed to study the impact of intelligent vehicles on traffic flow. The authors study the impacts of CACC for a highway-merging scenario from four to three lanes. The results show an improvement of traffic-flow stability and a slight increase in traffic-flow efficiency compared with the merging scenario without equipped vehicles

/pdf/the-impact-of-cooperative-adaptive-cruise-control-on-traffic-4jhs8l466d.pdf

The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics

The COVID-19 pandemic has proven that extraordinary public health measures can pivot every aspect of society. Norms, politics, economics, and business practices rapidly responded to coordinated simultaneous policies worldwide. This begs the question of why such advancements have not yet been similarly executed to reduce the short- and long-term morbidity and mortality due to environmental destruction and climate change. This article reviews various reasons explaining the discrepancy between the policies of these two health threats, using a terror management theory lens. Exploring how anthropogenic climate change potentiated the contagion and outcomes of COVID-19, the environmental determinants of health deserve increased attention in public discourse. The industry-driven response to COVID-19 also has exacerbated preexisting health inequalities and vulnerabilities, suggesting that a just transition for climate change must not repeat some of the same mistakes taken in global pandemic measures. Finally, addressing emergency health harms in ways that create increased environmental health harms is deemed iatrogenic, displacing rather than truly treating disease. Thus, a planetary health model focused on multisolving health issues is recommended for the basis of addressing COVID-19 and other health disasters. 

https://doi.org/10.1016/j.joclim.2022.100152

R. Visser

Papers

The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics

Mobilizing COVID-19 level public health interventions for climate breakdown is necessary