Milos N. Mladenovic

Engineering Social Justice into Traffic Control for Self-Driving Vehicles?

Abstract The convergence of computing, sensing, and communication technology will soon permit large-scale deployment of self-driving vehicles. This will in turn permit a radical transformation of traffic control technology. This paper makes a case for the importance of addressing questions of social justice in this transformation, and sketches a preliminary framework for doing so. We explain how new forms of traffic control technology have potential implications for several dimensions of social justice, including safety, sustainability, privacy, efficiency, and equal access. Our central focus is on efficiency and equal access as desiderata for traffic control design. We explain the limitations of conventional traffic control in meeting these desiderata, and sketch a preliminary vision for a next-generation traffic control tailored to address better the demands of social justice. One component of this vision is cooperative, hierarchically distributed self-organization among vehicles. Another component of this vision is a priority system enabling selection of priority levels by the user for each vehicle trip in the network, based on the supporting structure of non-monetary credits.

Self-organizing control framework for driverless vehicles

Development of in-vehicle computer and sensing technology, along with short-range vehicle-to-vehicle communication has provided technological potential for large-scale deployment of autonomous vehicles. The issue of intersection control for these future driverless vehicles is one of the emerging research issues. Contrary to some of the previous research approaches, this paper is proposing a paradigm shift based upon self-organizing and cooperative control framework. Distributed vehicle intelligence has been used to calculate each vehicles approaching velocity. The control mechanism has been developed in an agent-based environment. Self-organizing agents trajectory adjustment bases upon a proposed priority principle. Testing of the system has proved its safety, user comfort, and efficiency functional requirements. Several recommendations for further research are presented.

The Case of Mobility as a Service: A Critical Reflection on Challenges for Urban Transport and Mobility Governance

This chapter provides a reflective critique of Mobility as a Service (MaaS), an emerging development seeking a role within the Smart Mobility paradigm. We assess a range of its future implications for urban policymakers in terms of governance and sustainability (i.e., social and environmental impacts). We begin by describing the origins of the MaaS concept, along with the features of precursor technologies and current early examples. We then reflect on the marketing of MaaS and use it to consider how we might anticipate some potentially less desirable aspects of the promoted business models. Finally, we discuss the implications for governance.

Expanding the Design Horizon for Self-Driving Vehicles: Distributing Benefits and Burdens

With over one billion vehicles in the world today, the motorized road vehicle is the pillar of modern society. Since the beginning of the 20th century, the automobile has revolutionized our spaces, practices, cultures, and identities through a complex matrix of technical, financial, economic, political, and social linkages. Visions of automobile use have always shaped its design, manufacture, and production. Now, motorized road transport is set to revolutionize our society once again on a huge scale. Recent technological developments in propulsion, telecommunications, sensing, and in-vehicle computing technology are expanding the range of vehicles? capabilities. A technological convergence is underway, moving towards self-driving vehicle (SDV) technology. These vehicles will utilize computational algorithms, sensors, and communication devices to automatically navigate a variety of environments with limited or no intervention from human drivers.

Priority-based intersection control framework for self-driving vehicles: Agent-based model development and evaluation

Development of in-vehicle computer and sensing technology, along with short-range vehicle-to-vehicle communication has provided technological potential for large-scale deployment of self-driving vehicles. The issue of intersection control for these future self-driving vehicles is one of the emerging research issues. Contrary to some of the previous research approaches, this paper is proposing a paradigm shift based upon cooperative self-organizing control framework with end-user responsibility. Distributed vehicle intelligence has been used to calculate each vehicles approaching velocity. The control mechanism has been developed in an agent-based environment. Self-organizing agents trajectory adjustment bases upon a proposed priority principle. Testing of the system has proved its safety, user comfort, and efficiency functional requirements. Several recommendations for further research are presented.

Travel times and transfers in public transport: Comprehensive accessibility analysis based on Pareto-optimal journeys

Abstract Efficient public transport (PT) networks are vital for well-functioning and sustainable cities. Compared to other modes of transport, PT networks feature inherent systemic complexity due to their schedule-dependence and network organization. Because of this, efficient PT network planning and management calls for advanced modeling and analysis tools. These tools have to take into account how people use PT networks, including factors such as demand, accessibility, trip planning and navigability. From the PT user perspective, the common criteria for planning trips include waiting times to departure, journey durations, and the number of required transfers. However, waiting times and transfers have typically been neglected in PT accessibility studies and related decision-support tools. Here, we tackle this issue by introducing a decision-support framework for PT planners and managers, based on temporal networks methodology. This framework allows for computing pre-journey waiting times, journey durations, and number of required transfers for all Pareto-optimal journeys between any origin–destination pair, at all points in time. We visualize this information as a temporal distance profile, covering any given time interval. Based on such profiles, we define the best-case, mean, and worst-case measures for PT travel time and number of required PT vehicle boardings, and demonstrate their practical utility to PT planning through a series of accessibility case studies. By visualizing the computed measures on a map and studying their relationships by performing an all-to-all analysis between 7463 PT stops in the Helsinki metropolitan region, we show that each of the measures provides a different perspective on accessibility. To pave the way towards more comprehensive understanding of PT accessibility, we provide our methods and full analysis pipeline as free and open source software.

Driving the self-driving vehicle: Expanding the technological design horizon

Drawing perspectives from science and technology studies, philosophy of science, and literature from ethics and social justice, this paper examines the promises and challenges in the development of self-driving vehicle (SDV) technology. We start with the premise that the combination of different computing technologies embedded in SDVs is a powerful tool for efficiency in communications, information gathering, processing, and storage. However, by focusing on efficiency, SDVs provide a new mode of industrialized transportation whose users can only choose between transportation services, but have little or no say about the broader social implications of the technology. We argue that perspectives from social justice and ethics show that SDVs have implications beyond transportation, with profound consequences for users and societies. In particular, values such as privacy, security, and responsibility may be changed for good or bad, in both the short and long-term. The examination of these changes, while the technology is still under foundational development, is as urgent as it is needed.

Intersecting our mobilities: path dependence from manually-operated semaphore to self-driving vehicles?

Potential disruption stemming from self-driving vehicle (SDV) technology may change not just vehicles, but the foundations of our mobilities. As an example of analysing SDV technological development, this paper focuses on SDV intersection control. The starting premise is that technological development requires an understanding of previous developmental trajectories and potential future needs, rather than simply addressing present shortcomings. In order to investigate potential traps of technological path dependence, the paper examines the developmental trajectory of conventional traffic control technology. In addition, the paper contrasts stateof- the-research efforts for development of intersection control principles for SDVs. Finally, conclusive parallels are drawn for guiding the further development of SDV technology. Conclusions highlight the need for a wider deliberation and expansion of the criteria for foresight of mobility futures.

Improved decision-support making for selecting future traffic signal controllers using expert-knowledge acquisition

Transportation agencies are facing the decision-making problem while selecting traffic signal controller that corresponds to the needs of their future signal system. The complexity of this problem originates from the current level of controller standardization, market-driven competition, responsibility for long-term operation, and scale of investment. This paper presents an improvement of methodology and a decision-support system (DSS) for selecting traffic signal controllers. DSS bases upon Analytical Hierarchy Process, and is developed as an application in MS Excel. The main improvement is the component for expert knowledge acquisition for assignment of criteria weights. The graphical user interface and supporting analytical engine based on fuzzy logic are developed to enhance the expert knowledge acquisition. Paper presents application interface and analytical engine with an example. Possibilities for further research should provide potential for greater flexibility of this application to aid in decision-making for other equipment selection.

Socially sustainable control framework for self-driving vehicles

Considering an emerging technological potential for large-scale deployment of self-driving vehicles, there is a need to establish intersection control mechanism. Contrary to some of the previous research efforts, this paper is proposing an expanded design perspective that includes social sustainability. The approach for sustainable design focuses on the notion of social justice. The framework of social justice is developed through a system of priority levels and hierarchically decentralized control based on distributed vehicle intelligence. The control mechanism has been developed in an agent-based environment. Testing of the system has proved its safety, user comfort, efficiency, and delay distribution requirements. Several recommendations for further research are presented.