Browse Topic: Traffic management
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
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 Leader-follower autonomous vehicle systems have a vast range of applications which can increase efficiency, reliability, and safety by only requiring one manned-vehicle to lead a fleet of unmanned followers. The proper estimation and duplication of a manned-vehicle’s path is a critical component of the ongoing development of convoying systems. Auburn University’s GAVLAB has developed a UWB-ranging based leader-follower GNC system which does not require an external GPS reference or communication between the vehicles in the convoy. Experimental results have shown path-duplication accuracy between 1-5 meters for following distances of 10 to 50 meters. Citation: K. Thompson, B. Jones, S. Martin, and D. Bevly, “GPS-Independent Autonomous Vehicle Convoying with UWB Ranging and Vehicle Models,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 16-18, 2022
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 The automotive and defense industries are going through a period of disruption with the advent of Connected and Automated Vehicles (CAV) driven primarily by innovations in affordable sensor technologies, drive-by-wire systems, and Artificial Intelligence-based decision support systems. One of the primary tools in the testing and validation of these systems is a comparison between virtual and physical-based simulations, which provides a low-cost, systems-approach testing of frequently occurring driving scenarios such as vehicle platooning and edge cases and sensor-spoofing in congested areas. Consequently, the project team developed a robotic vehicle platform—Scaled Testbed for Automated and Robotic Systems (STARS)—to be used for accelerated testing elements of Automated Driving Systems (ADS) including data acquisition through sensor-fusion practices typically observed in the field of robotics. This paper will highlight the implementation of STARS as a scaled testbed for rapid
ABSTRACT This paper presents Neya’s efforts in developing autonomous depot assembly and parking behaviors for the Ground Vehicle Systems Center’s (GVSC) Autonomous Ground Re-supply (AGR) program. Convoys are a prime target for the enemy, and therefore GVSC is making efforts to remove the human operators and make them autonomous. However, humans still have to manually drive multiple convoy vehicles to and from their depot parking locations before and after autonomous convoy operations – a time-consuming and laborious process. Neya systems was responsible for the design, development, and testing of the autonomous depot assembly and disassembly behaviors, enabling end-to-end autonomy for convoy operations. Our solution to the problem, including the concept of operations, design, as well as approaches towards testing and validation are described in detail
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 This paper presents two techniques for autonomous convoy operations, one based on the Ranger localization system and the other a path planning technique within the Robotic Technology Kernel called Vaquerito. The first solution, Ranger, is a high-precision localization system developed by Southwest Research Institute® (SwRI®) that uses an inexpensive downward-facing camera and a simple lighting and electronics package. It is easily integrated onto vehicle platforms of almost any size, making it ideal for heterogeneous convoys. The second solution, Vaquerito, is a human-centered path planning technique that takes a hand-drawn map of a route and matches it to the perceived environment in real time to follow a route known to the operator, but not to the vehicle. Citation: N. Alton, M. Bries, J. Hernandez, “Autonomous Convoy Operations in the Robotic Technology Kernel (RTK)”, In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI
Artificial Intelligence (AI) has emerged as a transformative force across various industries, revolutionizing processes and enhancing efficiency. In the automotive domain, AI's adaption has ushered in a new era of innovation and driving advancements across manufacturing, safety, and user experience. By leveraging AI technologies, the automotive industry is undergoing a significant transformation that is reshaping the way vehicles are manufactured, operated, and experienced. The benefits of AI-powered vehicles are not limited to their manufacturing, operation, and enhancing the user experience but also by integrating AI-powered vehicles with smart city infrastructure can unlock much more potential of the technology and can offer numerous advantages such as enhanced safety, efficiency, growth, and sustainability. Smart cities aim to create more livable, resilient, and inclusive communities by harnessing innovation through technologies like Internet of Things (IoT), devices, data
Traditional live testing of autonomous ground vehicles can be augmented through use of digital twins of the test environment, the vehicle mobility models, and the vehicle sensors. These digital twins combined with the autonomous software under test allow testers to inject faults, weather, obstacles, find edge case scenarios, and collect information to understand the decision making of the autonomous software under test. With this new capability, autonomous ground vehicles can now be tested in four stages. The first stage is testing the autonomous software using digital twins. In this stage with the help of a High-Performance Computer thousands of scenarios can be run. Once issues are communicated and addressed, stage two, hardware in the loop testing can begin. Hardware in the loop uses simulators that already exist to test systems such as autonomous convoys with a virtual leader and a live follower. Stage three employs a live virtual constructive approach by using one vehicle to test
The deployment of autonomous urban buses brings with it the hope of addressing concerns associated with safety and aging drivers. However, issues related autonomous vehicle (AV) positioning and interactions with road users pose challenges to realizing these benefits. This report covers unsettled issues and potential solutions related to the operation of autonomous urban buses, including the crucial need for all-weather localization capabilities to ensure reliable navigation in diverse environmental conditions. Additionally, minimizing the gap between AVs and platforms during designated parking requires precise localization. Next-gen Urban Buses: Autonomy and Connectivity addresses the challenge of predicting the intentions of pedestrians, vehicles, and obstacles for appropriate responses, the detection of traffic police gestures to ensure compliance with traffic signals, and the optimization of traffic performance through urban platooning—including the need for advanced communication
This article offers an algorithmic solution for moving a homogeneous platoon of position-controlled vehicles on a curved path with varying speeds and in the presence of communication losses and delays. This article considers a trajectory-based platooning with the leader–following communication topology, where the lead vehicle communicates its reference position and orientation to each autonomous follower vehicle. A follower vehicle stores this communicated information for a specific period as a virtual trail of the lead vehicle starting from the lead vehicle’s initial position and orientation. An algorithm uses this trail to find the follower vehicle’s reference position and orientation on that trail, such that the follower vehicle maintains a constant distance from the lead vehicle. The proposed algorithm helps form a platoon where each vehicle can traverse a curve with varying speeds. In contrast, in the existing literature, most of the solutions for vehicle platooning on a curved
This research investigates platoon dispersion characteristics in mixed-traffic flow of autonomous and human-driven vehicles. It presents a cellular automata-based platoon dispersion model. The study’s key findings are as follows: platoon dispersion initially increases and then decreases with the rise in autonomous vehicle proportions. When the autonomous vehicle proportion is approaching 100%, platoon dispersion descends rapidly and is completely eliminated while the proportion is 100%. Compared to platoon consisting entirely of human-driven vehicles, the peak value of standard deviation of vehicle speed is 1.71 times and the travel time drops by 38.19% when the proportion is 1. Moreover, the lane-changing behavior enhances platoon speed, acceleration, and space utilization at micro- and macrolevels by optimizing space resource allocation within the platoon. The study employs a two-lane mixed-flow platoon dispersion model that assumes uniform vehicle characteristics and prioritizes
Urban Air Mobility (UAM) envisions heterogenous airborne entities like crewed and uncrewed passenger and cargo vehicles within, and between urban and rural environment. To achieve this, a paradigm shift to a cooperative operating environment similar to Extensible Traffic Management (xTM) is needed. This requires the blending of traditional Air Traffic Services (ATS) with the new generation UAM vehicles having their unique flight dynamics and handling characteristics. A hybrid environment needs to be established with enhanced shared situational awareness for all stakeholders, enabling equitable airspace access, minimizing risk, optimized airspace use, and providing flexible and adaptable airspace rules. This paper introduces a novel concept of distributed airspace management which would be apt for all kinds of operational scenarios perceived for UAM. The proposal is centered around the efficiency and safety in air space management being achieved by self-discipline. It utilizes
Truck platooning is an emerging technology that exploits the drag reduction experienced by bluff bodies moving together in close longitudinal proximity. The drag-reduction phenomenon is produced via two mechanisms: wake-effect drag reduction from leading vehicles, whereby a following vehicle operates in a region of lower apparent wind speed, thus reducing its drag; and base-drag reduction from following vehicles, whereby the high-pressure field forward of a closely-following vehicle will increase the base pressure of a leading vehicle, thus reducing its drag. This paper presents a physics-guided empirical model for calculating the drag-reduction benefits from truck platooning. The model provides a general framework from which the drag reduction of any vehicle in a heterogeneous truck platoon can be calculated, based on its isolated-vehicle drag-coefficient performance and limited geometric considerations. The model is adapted from others that predict the influence of inter-vehicle
India is a highly populous country. The traffic problems faced by the people here are not uncommon. The increase in traffic leads to increase in accidents, pollution, inconvenience and frustration. It also comes with costs of additional fuel and time. Though public transport is extensively available in India, still it isn't sufficient for the population of India. Especially in Metro cities, public transport services are often crowded. So, to travel peacefully people are opting for commuting in their own vehicles. And as a result, more vehicles are coming on roads. Other major reasons for increasing traffic are lack of proper implementation of traffic rules and traffic signals out of sync. In addition to city traffic, congestion is also seen on highways, mainly at toll plazas. Although implementation of FASTag has reduced it to some extent, some toll plazas still face traffic congestion issues. This paper provides an idea to ease the traffic problems in the city and on the highways too
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