Enide Solutions (Spain)

Abstract This paper presents a comprehensive market research study focused on identifying opportunities and barriers for the adoption of autonomous heavy-duty vehicles (AHDVs) in the logistics industry. The methodology employs a qualitative approach, utilizing workshops, questionnaires, interviews, and social media polls to collect primary and secondary data. The empirical findings highlight both the current landscape and the future trends in AHDVs, fleet management, and logistics. The study reveals the importance of safety, technological readiness, regulatory challenges, and infrastructure development as key barriers, while also showcasing potential benefits like increased safety, reduced costs, and improved efficiency. Furthermore, a quadrant analysis prioritizes these opportunities and barriers for strategic decision-making. The article concludes by discussing the implications of the findings and the broader context of autonomous vehicles in logistics.

In this paper, we showcase a testbed implementation of the cutting-edge architecture derived from the ongoing European project PoDIUM. This project is dedicated to advancing the implementation of Cooperative, Connected and Automated Mobility (CCAM) technology. The provided use case introduces a novel system designed to facilitate collaboration between vehicles, road users, and road operators, enabling the implementation of real-time traffic strategies to ensure safe and efficient traffic flow. The Physical and Digital Infrastructure (PDI) system integrates internal and external data to create a comprehensive perception of traffic conditions along road sections. Utilizing this information, the system generates potential scenarios and formulates traffic management strategies. The primary goal is to ensure the safe and efficient flow of traffic in mixed traffic conditions. The appropriate traffic control strategies are dynamically selected in real-time, utilising information obtained from connected vehicles (CVs) and vehicle detection through video cameras equipped with image recognition capabilities. These strategies are then communicated to Connected and Automated Vehicles (CAV), which autonomously adhere to them whenever feasible. Furthermore, the infrastructure facilitates the optimal dissemination of awareness and perception information among CVs in the area, thereby enhancing safety and coordination among them.

This article describes possible scenarios for wireless charged electric vehicles, as they are discussed within the UNPLUGGED project. It gives a brief introduction into wireless technology and explains the three possible implementation steps for charging electric vehicles: stationary, static en-route and dynamic en-route. Based on these scenarios the impact of wireless charging on future mobility, especially in urban environments is discussed.