Vulnerable road users and connected autonomous vehicles interaction: a survey

There is a group of users within the vehicular traffic ecosystem known as Vulnerable Road Users (VRUs). VRUs include pedestrians, cyclists, motorcyclists, among others. On the other hand, connected autonomous vehicles (CAVs) are a set of technologies that combines, on the one hand, communication technologies to stay always ubiquitous connected, and on the other hand, automated technologies to assist or replace the human driver during the driving process. Autonomous vehicles are being visualized as a viable alternative to solve road accidents providing a general safe environment for all the users on the road specifically to the most vulnerable. One of the problems facing autonomous vehicles is to generate mechanisms that facilitate their integration not only within the mobility environment, but also into the road society in a safe and efficient way. In this paper, we analyze and discuss how this integration can take place, reviewing the work that has been developed in recent years in each of the stages of the vehicle-human interaction, analyzing the challenges of vulnerable users and proposing solutions that contribute to solving these challenges.This work was partially funded by the Ministry of Economy, Industry, and Competitiveness of Spain under Grant: Supervision of drone fleet and optimization of commercial operations flight plans, PID2020-116377RB-C21.Peer ReviewedPostprint (published version

Implicit personalization in driving assistance: State-of-the-art and open issues

In recent decades, driving assistance systems have been evolving towards personalization for adapting to different drivers. With the consideration of driving preferences and driver characteristics, these systems become more acceptable and trustworthy. This article presents a survey on recent advances in implicit personalized driving assistance. We classify the collection of work into three main categories: 1) personalized Safe Driving Systems (SDS), 2) personalized Driver Monitoring Systems (DMS), and 3) personalized In-vehicle Information Systems (IVIS). For each category, we provide a comprehensive review of current applications and related techniques along with the discussion of industry status, benefits of personalization, application prospects, and future focal points. Both relevant driving datasets and open issues about personalized driving assistance are discussed to facilitate future research. By creating an organized categorization of the field, we hope that this survey could not only support future research and the development of new technologies for personalized driving assistance but also facilitate the application of these techniques within the driving automation community</h2

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Advanced Sensing and Control for Connected and Automated Vehicles

Connected and automated vehicles (CAVs) are a transformative technology that is expected to change and improve the safety and efficiency of mobility. As the main functional components of CAVs, advanced sensing technologies and control algorithms, which gather environmental information, process data, and control vehicle motion, are of great importance. The development of novel sensing technologies for CAVs has become a hotspot in recent years. Thanks to improved sensing technologies, CAVs are able to interpret sensory information to further detect obstacles, localize their positions, navigate themselves, and interact with other surrounding vehicles in the dynamic environment. Furthermore, leveraging computer vision and other sensing methods, in-cabin humans’ body activities, facial emotions, and even mental states can also be recognized. Therefore, the aim of this Special Issue has been to gather contributions that illustrate the interest in the sensing and control of CAVs

Implicit Personalization in Driving Assistance: State-of-the-Art and Open Issues

In recent decades, driving assistance systems have been evolving towards personalization for adapting to different drivers. With considering personal driving preferences and characteristics, these systems become more acceptable and trustworthy. This paper presents a survey of recent advances in implicit personalized driving assistance. We classify the collection of work into three main categories: 1) personalized Safe Driving Systems (SDS), 2) personalized Driver Monitoring Systems (DMS), and 3) personalized In-vehicle Information Systems (IVIS). For each category, we provide a comprehensive review of current applications and related techniques along with the discussion of industry status, gains of personalization, application prospects, and future focal points. Several existing driving datasets are summarized and open issues of personalized driving assistance are also suggested to facilitate future research. By creating an organized categorization of the field, this survey could not only support future research and the development of new technologies for personalized driving assistance but also facilitate the use of these techniques by researchers within the driving automation community

Constructing pedestrian-centric street mobility: Observation and simulation for design

There are three principal components to the research presented in this thesis: a video-observation study of pedestrian behaviours and interactions with traffic, leading to the development of an agent-based digital simulation, and demonstrating the potential of this simulation for designing pedestrian-centric interventions in the streetscape. The long-term objective is to devise streetscapes that responsively adapt to the needs of pedestrians. Since the advent of car culture in the late 1930s, the approaches to street design have prioritised efficient motorised traffic flow, restricting walking and neglecting the pedestrian point of view. In recent years, however, a growing interest in making urban spaces more pedestrian-friendly has emerged, popularising concepts such as walkability, shared space, and traffic calming. These approaches aim to promote active travel and reduce car dependency in order to mitigate congestion, pollution, accidents and other harms. Urban studies have concentrated primarily on pedestrian-only zones and utilised spatial features as a way to reach pedestrian-friendly streets. Meanwhile, transport studies have tended to approach the street from a throughput and vehicle-oriented stance. Despite these endeavours, pedestrian-oriented approaches appear to lack systematic consideration of pedestrian behaviours as they interact with motor vehicles and street infrastructure. My PhD research differs from prior studies by focusing on these behaviours and interactions to support a pedestrian-oriented street mobility system. The current design of streets communicates to pedestrians via its structures and signs, such as barriers, crossings, and lights, while its capacity to respond and adapt is minimal. In contrast, this thesis argues that, since the street environment is inherently dynamic, we should analyse its dynamics and design the street to be responsive. Through responsiveness, my aim is to increase the convenience of pedestrian movement whilst creating a safe experience. This PhD asks the question 'how to design a pedestrian-centric street system that dynamically manages street mobility?'. The research takes a practice-based and reflective approach, designing agent-based simulations based on a qualitative observational study. Designing a simulation accomplishes two things: 1) it creates a space for implementing and evaluating possible design interventions, and 2) it prompts new insights into the behavioural processes of pedestrians. My research has followed an iterative cycle in line with second-order cybernetics: in two feedback loops, the first study informed the second study while the second informed the first. The video observation of street behaviours particularly explored pedestrian decision and interaction processes, identifying pedestrians’ own observational strategies and their varying levels of risk-taking. These aspects are reflected in the simulation. The first chapter introduces the pedestrian issues on the street and sets out the key concepts in pedestrian-centric street design. The second chapter examines the literature and existing practice that addresses pedestrian and vehicle interactions on the street. Chapter three sets out the theoretical framework and the following chapter describes the methodology. The three subsequent chapters present the following studies: (1) understanding the context by conducting qualitative video observation in a real street environment to observe and document the relations between streets, pedestrians and vehicles; (2) creating an artificial pedestrian society for simulation purposes, using agent-based modelling, both to refine the understanding developed through video analysis and to create a platform for experimentation; (3) design and implementation of prototype responsive interventions within the simulation, focusing on localised changes in the environment to empower pedestrians. The last chapter reflects on these projects by discussing the research contributions in terms of methods, techniques, and practices. The methodological innovation includes combining qualitative and computational tools as well as the use of simulation and video analysis in an iterative and reflexive cycle. Theoretical contributions include evaluating streets through pedestrian dynamics, creating a taxonomy of existing pedestrian interventions according to their spatial and temporal impacts, and rethinking the street as a responsive environment. The practical component advances the technical state of the art by expanding the capabilities of pedestrian agents when negotiating with vehicles and making crossing decisions and demonstrates the potential for designing novel interventions in the streetscape, including those that respond to pedestrian behaviour. The last chapter, also, emphasises the role of reflective design practice and the place of simulation within it

Sex Work on Campus

Sex Work On Campus examines the experiences of college students engaged in sex work and sparks dialogue about the ways educators might develop a deeper appreciation for—and praxis of—equity and justice on campus. Analysing a study conducted with seven college student sex workers, the book focuses on sex work histories, student motivations and how power (or lack thereof) associated with social identity shapes experiences of student sex work. It examines what these students learn because of sex work, and what college and university leaders can do to support them. These findings are combined in tandem with analysis of current research, popular culture, sex work rights movements, and exploration of legal contexts. This fresh and important writing is suitable for students and scholars in sexuality studies, gender studies, sociology, and education

Human-Centric Machine Vision

Recently, the algorithms for the processing of the visual information have greatly evolved, providing efficient and effective solutions to cope with the variability and the complexity of real-world environments. These achievements yield to the development of Machine Vision systems that overcome the typical industrial applications, where the environments are controlled and the tasks are very specific, towards the use of innovative solutions to face with everyday needs of people. The Human-Centric Machine Vision can help to solve the problems raised by the needs of our society, e.g. security and safety, health care, medical imaging, and human machine interface. In such applications it is necessary to handle changing, unpredictable and complex situations, and to take care of the presence of humans

Sex Work on Campus

Sex Work On Campus examines the experiences of college students engaged in sex work and sparks dialogue about the ways educators might develop a deeper appreciation for—and praxis of—equity and justice on campus. Analysing a study conducted with seven college student sex workers, the book focuses on sex work histories, student motivations and how power (or lack thereof) associated with social identity shapes experiences of student sex work. It examines what these students learn because of sex work, and what college and university leaders can do to support them. These findings are combined in tandem with analysis of current research, popular culture, sex work rights movements, and exploration of legal contexts. This fresh and important writing is suitable for students and scholars in sexuality studies, gender studies, sociology, and education