Browse Topic: Mobility
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Thor Industries introduced what it claims is the world's first extended-range Class A motorhome. The company claims the Embark by Entegra Coach offers up to 450 miles (725 km) of real-world driving range thanks to an integrated range extender. “Electrification will play a central role in the future of mobility, including RVing,” said Thor Industries president and CEO Bob Martin. “This first-of-its-kind electric Class A motorhome reinforces Thor's innovation leadership and offers unparalleled product differentiation for the Entegra Coach brand.”
The path toward carbon-neutral mobility represents one of the greatest cultural transformations in recent human history. Positioned between industrial heritage, emerging mobility technologies, and the energy supply sector are the users of 1.5 billion motor vehicles worldwide. Conflicting publications on raw material availability, energy efficiency, and the climate neutrality of propulsion systems have led to widespread uncertainty. This Illustrated Energy Primer provides a new foundation for orientation. It begins with a visual explanation of the basic concepts of energy and power, followed by illustrative comparisons of typical energy demands in vehicles and households. The focus then shifts to common types of energy generation systems. Using regional examples—from coal-fired power plants to wind farms, solar installations, and balcony solar panels—the guide provides clear and accessible performance benchmarks for energy production. Next, nine individual experience profiles highlight
The wing-in-ground effect (WIG) vehicle represents a significant advancement in aerodynamics and vehicle design, leveraging the ground effect phenomenon to enhance lift and reduce drag when flying close to the surface. This unique capability allows WIG vehicles to achieve higher payloads, longer range, and greater fuel efficiency compared to traditional aircraft, making them an attractive option for modern military and global disaster response applications. Wing-in-Ground Effect Vehicles: From Modern Military and Commercial Development to Global Disaster Response discusses future disaster response, logistics, and military applications for WIG vehicles, including the ongoing development of aerospace and transportation technology. Relavant advancements in materials and propulsion systems holds promise for further enhancing WIG performance and operational range. Additionally, cost-effective and powerful flight computers with various types of mission-enabling sensor suites from the
The U-Shift IV represents the latest evolution in modular urban mobility solutions, offering significant advancements over its predecessors. This innovative vehicle concept introduces a distinct separation between the drive module, known as the driveboard, and the transport capsules. The driveboard contains all the necessary components for autonomous driving, allowing it to operate independently. This separation not only enables versatile applications - such as easily swapping capsules for passenger or goods transportation - but also significantly improves the utilization of the driveboard. By allowing a single driveboard to be paired with different capsules, operational efficiency is maximized, enabling continuous deployment of driveboards while the individual capsules are in use. The primary focus of U-Shift IV was to obtain a permit for operating at the Federal Garden Show 2023. To achieve this goal, we built the vehicle around the specific requirements for semi-public road
The road network is a critical component of modern urban mobility systems, with signalized traffic intersections playing a pivotal role. Traditionally, traffic light phase timings and durations at intersections are designed by transportation engineers using historical traffic data. Some modern intersections employ trigger-based mechanisms to improve traffic flow; however, these systems often lack global awareness of traffic conditions across multiple intersections within a network. With the increasing availability of traffic data and advancements in machine learning, traffic light systems can be enhanced by modeling them as agents operating in an environment. This paper proposes a Reinforcement Learning (RL) based approach for multi-agent traffic light systems within a simulation environment. The simulation is calibrated using real-world traffic data, enabling RL agents to learn effective control strategies based on realistic scenarios. A key advantage of using a calibrated simulation
With many stakeholders involved, and major investments supporting it, the advancements in automated driving (AD) are undoubtedly there. Generally speaking, the motivation for advancing AD is driver convenience and road safety. Regarding the development of AD, original equipment manufacturers, technology start-ups, and AD systems developers have taken different approaches for automated vehicles (AVs). Some manufacturers are on the path toward stand-alone vehicles, mostly relying on onboard sensors and intelligence. On the other hand, the connected, cooperative, and automated mobility (CCAM) approach relies on additional communication and information exchange to ensure safe and secure operation. CCAM holds great potential to improve traffic management, road safety, equity, and convenience. In both approaches, there are increasingly large amounts of data generated and used for AD functions in perception, situational awareness, path prediction, and decision-making. The use of artificial
Letter from the Guest Editors
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