An increasing number of automated vehicles will pervade our traffic systems in the future. The absence of a human driver requires these vehicles to communicate to, and interact with other traffic participants, such as vulnerable road users (pedestrians, cyclists, and emerging mobility forms like eBikes or scooters), but potentially also drivers of manual vehicles. In this regard, various studies and concepts demonstrating so-called “external Human-Machine Interfaces” (eHMIs) have been presented in the past couple of years. Many of these works have investigated comparably simple scenarios, such as a single pedestrian aiming to cross the street when an automated vehicle is approaching. Although we still welcome such contributions, research in this area will have to take more complex situations into account. This drives the need for research addressing other situations involving groups of vulnerable road users and traffic participants, different scenarios including roundabouts or urban shared spaces, but also exploring the potential of communication and interaction beyond such classical situations to improve cooperation in traffic.

This book takes a look at fully automated, autonomous vehicles and discusses many open questions: How can autonomous vehicles be integrated into the current transportation system with diverse users and human drivers? Where do automated vehicles fall under current legal frameworks? What risks are associated with automation and how will society respond to these risks? How will the marketplace react to automated vehicles and what changes may be necessary for companies? Experts from Germany and the United States define key societal, engineering, and mobility issues related to the automation of vehicles. They discuss the decisions programmers of automated vehicles must make to enable vehicles to perceive their environment, interact with other road users, and choose actions that may have ethical consequences. The authors further identify expectations and concerns that will form the basis for individual and societal acceptance of autonomous driving. While the safety benefits of such vehicles are tremendous, the authors demonstrate that these benefits will only be achieved if vehicles have an appropriate safety concept at the heart of their design. Realizing the potential of automated vehicles to reorganize traffic and transform mobility of people and goods requires similar care in the design of vehicles and networks. By covering all of these topics, the book aims to provide a current, comprehensive, and scientifically sound treatment of the emerging field of “autonomous driving".

Handbook of Human Factors for Automated, Connected, and Intelligent Vehicles Subject Guide: Ergonomics & Human Factors Automobile crashes are the seventh leading cause of death worldwide, resulting in over 1.25 million deaths yearly. Automated, connected, and intelligent vehicles have the potential to reduce crashes significantly, while also reducing congestion, carbon emissions, and increasing accessibility. However, the transition could take decades. This new handbook serves a diverse community of stakeholders, including human factors researchers, transportation engineers, regulatory agencies, automobile manufacturers, fleet operators, driving instructors, vulnerable road users, and special populations. It provides information about the human driver, other road users, and human–automation interaction in a single, integrated compendium in order to ensure that automated, connected, and intelligent vehicles reach their full potential. Features Addresses four major transportation challenges—crashes, congestion, carbon emissions, and accessibility—from a human factors perspective Discusses the role of the human operator relevant to the design, regulation, and evaluation of automated, connected, and intelligent vehicles Offers a broad treatment of the critical issues and technological advances for the designing of transportation systems with the driver in mind Presents an understanding of the human factors issues that are central to the public acceptance of these automated, connected, and intelligent vehicles Leverages lessons from other domains in understanding human interactions with automation Sets the stage for future research by defining the space of unexplored questions

Human Factors in Intelligent Vehicles addresses issues related to the analysis of human factors in the design and evaluation of intelligent vehicles for a wide spectrum of applications and over different dimensions. To commemorate the 8th anniversary of the IEEE ITS Workshop on Human Factors (http: //hfiv.net) some recent works of authors active in the automotive human factors community have been collected in this book. Enclosed here are extended versions of papers and tutorials that were presented at the IEEE ITSS Workshop on "Human Factors in Intelligent Vehicles" and also included is additional deeper analysis along with detailed experimental and simulation results. The contributors cover autonomous vehicles as well as the frameworks for analyzing automation, modelling and methods for road users' interaction such as intelligent user interfaces, including brain-computer interfaces and simulation and analysis tools related to human factors.

Autonomous vehicle (AV) is becoming very popular due to technological evolution in autonomous transportation sector. It can be more reliable than human-controlled vehicle as it can detect pedestrians with high accuracy and control the vehicle precisely. One major disadvantage of the autonomous vehicle is that it cannot communicate with surrounding pedestrians and other road users like a traditional vehicle. Pedestrians tend to interact with human drivers before taking a crossing decision; but AV cannot use such communication mediums. As a result, it is necessary to understand how pedestrians will behave in a crossing scenario when an AV is present. To evaluate this complex interaction pattern, a simulation tool can be useful as it can generate realistic pedestrian motion models which are useful to design different AV algorithms. These motion models can also help to understand different perspectives from a pedestrian viewpoint and what factors are related to the safe interaction between AVs and pedestrians. It can also benefit autonomous vehicle designers: they can visualize pedestrian and vehicle trajectories, extract velocity and acceleration profile of both agents, test different autonomous vehicle planning algorithms and assess the traffic safety in severe traffic conflicts. This research work presents a rule-based social force model to simulate pedestrian trajectories during interaction with an autonomous vehicle. The social force model is then integrated with an autonomous vehicle control and planning algorithm for simulating the behavior of both pedestrian and vehicle in traffic conflicts by varying different parameters such as agent's initial speed, different vehicle sensor types (error percentage of pedestrian detection varies), different pedestrian types (risk-taking, cautious and distracted), et cetera Two types of crossing scenarios (crosswalk and roundabout) are used in this research work. The output of this simulation is the minimum distance that is accepted by a pedestrian during crossing. These minimum distances can be used to simulate more risky interaction scenarios to understand the effectiveness of autonomous vehicle planning algorithm while interacting with different types of pedestrians. Although AVs are expected to reduce traffic crashes, a finite element simulation model is developed to determine pedestrian risk injury criteria for both head and chest portion during unavoidable crashes. The finite element model uses side and frontal impact for pedestrian collision. Injury probability for both head and chest injuries are found higher for the frontal impact than the side impact collision.