Browse Topic: Transportation Systems
Recent advancements in electric vertical take-off and landing (eVTOL) aircraft and the broader advanced air mobility (AAM) movement have generated significant interest within and beyond the traditional aviation industry. Many new applications have been identified and are under development, with considerable potential for market growth and exciting potential. However, talent resources are the most critical parameters to make or break the AAM vision, and significantly more talent is needed than the traditional aviation industry is able to currently generate. One possible solution—leverage rapid advancements of artificial intelligence (AI) technology and the gaming industry to help attract, identify, educate, and encourage current and future generations to engage in various aspects of the AAM industry. Beyond Aviation: Embedded Gaming, Artificial Intelligence, Training, and Recruitment for the Advanced Air Mobility Industry discusses how the modern gaming population of 3.3 million
This project presents the development of an advanced Autonomous Mobile Robot (AMR) designed to autonomously lift and maneuver four-wheel drive vehicles into parking spaces without human intervention. By leveraging cutting-edge camera and sensor technologies, the AMR integrates LIDAR for precise distance measurements and obstacle detection, high-resolution cameras for capturing detailed images of the parking environment, and object recognition algorithms for accurately identifying and selecting available parking spaces. These integrated technologies enable the AMR to navigate complex parking lots, optimize space utilization, and provide seamless automated parking. The AMR autonomously detects free parking spaces, lifts the vehicle, and parks it with high precision, making the entire parking process autonomous and highly efficient. This project pushes the boundaries of autonomous vehicle technology, aiming to contribute significantly to smarter and more efficient urban mobility systems
Innovation often comes a piece at a time, but what happens when you put all those pieces together at once? That is precisely the question Shell is attempting to answer with its Starship initiative. Now in its third iteration, Starship 3.0 Natural Gas continues pushing the boundaries of efficiency and emissions reduction by employing all currently available technologies and engineering advancements. The Shell Starship initiative was first launched in 2018 with the aim of setting new benchmarks for the commercial road transport sector. The Starship 2.0 managed 254 ton-miles per gallon for freight ton efficiency (FTE), which is 3.5 times the North American average. Additionally, Starship 2.0 recorded fuel consumption of 10.8 mpg on a cross-country run, which according to Shell is nearly double the current fleet average in North America
ABSTRACT Seasonality plays a key role in altering the terrain of many military operating environments. Since seasonality has such a large impact on the terrain, it needs to be properly accounted for in vehicle dynamics models. This work outlines a variety of static and dynamic seasonal terrain conditions and their impacts on vehicle mobility in an austere region of Europe. Overall the vehicles performed the best in the dry season condition. The thaw season condition had the most drastic impact on mobility with all but the heavy tracked vehicle being almost completely NOGO in the region. Overall, the heavy tracked vehicle had the best performance in all terrain conditions. These results highlight the importance of incorporating seasonal impacts on terrain into NRMM or any vehicle dynamics model. Future work will focus on collecting more data to improve the empirical relationships between vehicles and seasonal terrain conditions, thereby allowing for more accurate speed predictions
ABSTRACT Currently, many small Army ground robots have mobility configurations containing tracks with sets of dual or quad flipper configurations. Many of these robots include the iRobot PackBot, Talon, and Dragon Runner. While the preceding robotic designs have allowed these robots to navigate over obstacles and across low traction environments, an increasing need for agile robotic platforms in complex environments involving subterranean and urban structure missions will be critical in the future. Therefore, a new mobility system for dismounted ground robots is being researched to aid in the exploration, mapping, and identification by targets of interest for dense urban environments. This paper discusses one possibility for a new small CRS-I sized ground robot mobility system that is inspired by the rocker-bogie designs of the Mars rover systems. Citation: Timothy Pietrzyk, Ty Valascho “Robotic Rocker-Bogie Mechanism Prototype”, In Proceedings of the Ground Vehicle Systems Engineering
ABSTRACT Over time, the National Institute of Standards and Technology (NIST) has refined the 4Dimension / Real-time Control System (4D/RCS) architecture for use in Unmanned Ground Vehicles (UGVs). This architecture, when applied to a fully autonomous vehicle designed for missions in urban environments, can greatly assist in the process of saving time and lives by creating a more intelligent vehicle that acts in a safer and more efficient manner. Southwest Research Institute (SwRI®) has undertaken the Southwest Safe Transport Initiative (SSTI) aimed at investigating the development and commercialization of vehicle autonomy as well as vehicle-based telemetry systems to improve active safety systems and autonomy. This paper will discuss the implementation of the 4D/RCS architecture to the SSTI autonomous vehicle, a 2006 Ford Explorer
ABSTRACT To improve robustness of autonomous vehicles, deployments have evolved from a single intelligent system to a combination of several within a platoon. Platooning vehicles move together as a unit, communicating with each other to navigate the changing environment safely. While the technology is robust, there is a large dependence on data collection and communication. Issues with sensors or communication systems can cause significant problems for the system. There are several uncertainties that impact a system’s fidelity. Small errors in data accuracy can lead to system failure under certain circumstances. We define stale data as a perturbation within a system that causes it to repetitively rely on old data from external data sources (e.g. other cars in the platoon). This paper conducts a fault injection campaign to analyze the impact of stale data in a platooning model, where stale data occurs in the car’s communication and/or perception system. The fault injection campaign
ABSTRACT The application of advanced FEV Automotive Smart Vehicle© methods and technologies while maintaining functional safety compliance and how it applies to similar features, requirements and capabilities across the fleet of DoD combat and tactical vehicles will be discussed. The requirement of technologies for DoD autonomous ground vehicle including leader follower, automated convoy operations, and intelligent applique kit’ are common to those specified in the automotive industries. Intelligent vehicles can be advanced and implemented in an expeditious manner through FEV Smart Vehicle technologies, techniques and methodologies while maintain compliance to required functional safety. The application and impact of ISO 26262 (2011) as well as Mil-Std. 882(E) to the implementation of the advanced technologies and techniques in support of full operational vehicle autonomy can hinder development. Leveraging the FEV Automotive Smart Vehicle reduces the time and cost for safety compliant
ABSTRACT In this paper, we will present the results of our efforts developing the Autonomy Kit for the Tank Automotive Research Development and Engineering Center’s (TARDEC) Autonomous Ground Resupply (AGR) Sustainment Operations (SO) program. Robotic Research, LLC was responsible for the design, build, and implementation of the “Autonomy Kit” for the AGR SO. The Autonomy Kit is designed to be a fault-tolerant, vehicle-agnostic applique kit that provides the hardware and software needed to perform higher-level autonomous driving and planning functions. In the first Increment, the main focus was developing a “Leader/Follower” capability, where a manned “Leader” vehicle could perform a mission with a number of unmanned “Followers” reproducing its trajectory, maintaining convoy constraints, and avoiding obstacles in the path
ABSTRACT The concept of Autonomous Vehicles ultimately generating an “order of magnitude” potential increase in the duty or usage cycle of a vehicle needs to be addressed in terms of impact on the reliability domain. Voice of the customer data indicates current passenger vehicle usage cycles are typically very low, 5% or less. Meaning, out of a 24 hour day, perhaps the average vehicle is actually driven only 70 minutes or less. Therefore, approximately 95% of the day, the vehicles lay dormant in an unused state. Within the context of future fully mature Autonomous Vehicle environment involving structured car sharing, the daily vehicle usage rate could grow to 95% or more
ABSTRACT The Army has identified an operational need for a Robotic Convoy capability for its tactical vehicle fleets. The Department of Defense (DoD), with a fleet of over several hundred thousand tactical vehicles, must identify an approach with supporting technology and supply base to procure and support a Robotic Convoy solution at the lowest possible cost. While cost is a key driver, the selected system approach must be proven and robust to ensure the safety of our soldiers and the supply chain. An effective approach is to integrate and adapt the advanced automotive technologies, components and suppliers currently delivering advanced safety technologies into the automotive market. These advanced automotive technologies merged with DoD robotics enhancements in tactical behaviors, autonomous driving, command & control and unmanned systems collaboration will advance the operational utility of robotic convoy application in manned and unmanned modes. Figure 1 Military Application The
ABSTRACT This work investigates the effects of obstacle uncertainty on the speed, distance, and feasibility of a planned traversal path. Simulation results for artificial and real-world environments are used to numerically quantify how geometric uncertainty within a map affects path traversal cost. A significant outcome of this research is the discovery of a relationship between increasing uncertainty and path cost. As obstacle uncertainty increases, previously planned routes can become infeasible as they effectively become blocked off due to uncertainty in the obstacle geometry. This paper illustrates a method that can serve to increase the speed, simplicity, and reliability of path planning, while allowing uncertainty to be included in the mobility analysis. Citation: S. Tau, S. Brennan, K. Reichard, J. Pentzer, D. Gorsich, “The Effects of Obstacle Dimensional Uncertainty on Path Planning in Cluttered Environments”, In Proceedings of the Ground Vehicle Systems Engineering and
ABSTRACT The Internet of Things (IoT) is a system of systems (SoS) in every sense of the definition. A.P. Sage and others list five common SoS characteristics: operational independence of the individual systems, managerial independence, geographical distribution, emergent behavior and evolutionary development or independent life cycles. Typical examples include smart houses, the electric grid, and so-called smart cities. With military systems increasingly making use of IoT techniques in the upgrade, development and implementation of systems, IoT is becoming a critical factor. The future of IoT success is dependent on the application of solid Systems Engineering and Model Based Systems Engineering (MBSE) principals. Without MBSE, the complexity involved in the design, development, and deployment of IoT systems would consume both system and operational providers. IoT systems cannot be built in a vacuum and their success will only be realized through application of modern day systems
ABSTRACT Off-road autonomous navigation poses a challenging problem, as the surrounding terrain is usually unknown, the support surface the vehicle must traverse cannot be considered flat, and environmental features (such as vegetation and water) make it difficult to estimate the support surface elevation. This paper will focus on Robotic Research’s suite of off-road autonomous planning and obstacle avoidance tools. Specifically, this paper will provide an overview of our terrain detection system, which utilizes advanced LADAR processing techniques to provide an estimate of the surface. Additionally, it will describe the kino-dynamic off-road planner which can, in real-time, calculate the optimal route, taking into account the support surface, obstacles sensed in the environment, and more. Finally, the paper will explore how these technologies have been applied to a wide variety of different robotic applications
ABSTRACT U.S. Army Combat Capabilities Development Command (CCDC) Ground Vehicle Systems Center (GVSC) has been managing and developing a variety of autonomous systems throughout its existence. Two of the most important from the past decade include the Autonomous Mobility Appliqué System (AMAS) developed by Lockheed Martin Corporation (LMC) and the Robotic Technology Kernel (RTK) developed by GVSC in collaboration with DCS Corp and Southwest Research Institute (SwRI). Rather than continuing to develop and maintain two separate autonomous software systems, GVSC has decided to integrate any capabilities that were unique to AMAS into RTK and devote efforts to developing RTK going forward. The goal of integrating AMAS into RTK is to leverage the best features of each system. The process of this integration involves multiple steps. This paper describes the historical and current efforts involved in the integration of AMAS into RTK. Citation: D. Pirozzo, J.P. Hecker, A. Dickinson, T
ABSTRACT The Product Director Light Tactical Vehicles (PdD LTV) is responsible for the Army’s High Mobility Multipurpose Wheeled Vehicle (HMMWV) family of vehicles. Due to the large number of variants found throughout the Army plus the continued need for their service into the foreseeable future, the Army has conducted extensive depot recapitalization programs and continues to explore modernization options to sustain enduring requirements. Because competing performance requirements exist and budget constraints demand careful design choices, PdD LTV commissioned the development of a Whole System Trades Analysis Tool (WSTAT) specified for the HMMWV family of vehicles to help gain an analytic understanding of the key performance, cost, risk, and growth tradeoffs inherent within their potential designs. The WSTAT provides a holistic framework for modeling and understanding these tradeoffs. In this paper, the overarching WSTAT methodology is presented along with the specific implementation
ABSTRACT Evolving requirements for combat vehicles to provide increased mission capability and/or crew safety necessitate the addition of components and add-on armor to currently-fielded vehicles. These new requirements result in increased weight and increased electrical needs, which result in reduced mobility. The APD is built from the ground up to optimize a powertrain solution using cutting-edge technology specifically designed for harsh military environments, for use in both vehicle retrofits and new vehicle designs. The APD combines an efficient 1000 hp engine, transmission, integrated starter generator, thermal management system, and lithium-ion batteries to maximize powerpack power density. The APD was designed for a 45-60 ton combat vehicle, but designing for scalability, reconfigurability, and using modern techniques and technology has allowed the APD to greatly improve the capability and flexibility of the powerpack and the technology can be applied to heavier or lighter
ABSTRACT GS Engineering has developed technology to advance the sensory perception of autonomous systems. The Automatic Terrain Detection System (ATDS) is a technology that provides real time terrain detection. Vehicles deployed with ATDS have been able to yield improved mobility, automation of systems, and reduced fuel consumption. ATDS has been integrated into the MK23 MTVR, M1151 HMMWV for the ONR Predictive Adaptive Mobility (PAM) program, and into the Autonomous Ground Re-supply (AGR) by-wire kit for the Oshkosh Defense Palletized Load System (PLS). The ATDS is built upon proven sensors running integrated processing to replace or enhance existing vehicle systems. Citation: D. Subert, A. Diepen, K. Hubert, “Automatic Terrain Detection”, In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 13-15, 2019
ABSTRACT Military personnel involved in convoy operations are often required to complete multiple tasks within tightly constrained timeframes, based on limited or time-sensitive information. Current simulations are often lacking in fidelity with regard to team interaction and automated agent behavior; particularly problematic areas include responses to obstacles, threats, and other changes in conditions. More flexible simulations are needed to support decision making and train military personnel to adapt to the dynamic environments in which convoys regularly operate. A hierarchical task analysis approach is currently being used to identify and describe the many tasks required for effective convoy operations. The task decomposition resulting from the task analysis provides greater opportunity for determining decision points and potential errors. The results of the task analysis will provide guidance for the development of more targeted simulations for training and model evaluation from
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