Browse Topic: Global positioning systems (GPS)

Items (708)
It is becoming increasingly common for bicyclists to record their rides using specialized bicycle computers and watches, the majority of which save the data they collect using the Flexible and Interoperable Data Transfer (.fit) Protocol. The contents of .fit files are stored in binary and thus not readily accessible to users, so the purpose of this paper is to demonstrate the differences induced by several common methods of analyzing .fit files. We used a Garmin Edge 830 bicycle computer with and without a wireless wheel speed sensor to record naturalistic ride data at 1 Hz. The .fit files were downloaded directly from the computer, uploaded to the chosen test platforms - Strava, Garmin Connect, and GoldenCheetah - and then exported to .gpx, .tcx and .csv formats. Those same .fit files were also parsed directly to .csv using the Garmin FIT Software Developer Kit (SDK) FitCSVTool utility. The data in those .csv files (henceforth referred to as “SDK data”) were then either directly
Sweet, DavidBretting, Gerald
Predictive performance simulation of a high-efficiency lightweight vehicle is performed through development of a multi-physics MATLAB Simulink model including advanced vehicle dynamics. The vehicle is put into a three-dimensional representation of the racetrack, including its dimensions, slope, banking, and adhesion coefficient along the model space, elaborated from the track GPS data points. The vehicle’s reference trajectory is not priorly provided to the model at the simulation start as, during run-time, a predictive Steering Angle Generation (SAG) algorithm based on Nonlinear Model Predictive Control (NMPC) computes the optimal steering angle input needed to drive the vehicle on the track within its limits. Computation is based on fast predictive simulations of a simplified version of dynamics modelling of the vehicle. Each single simulation exploits a different possible steering angle to be applied by the virtual driver, starting from the initial conditions given by the actual
De Carlo, MatteoManzone, Simonede Carvalho Pinheiro, HenriqueCarello, Massimiliana
Bicycle computers record and store kinematic and physiologic data that can be useful for forensic investigations of crashes. The utility of speed data from bicycle computers depends on the accurate synchronization of the speed data with either the recorded time or position, and the accuracy of the reported speed. The primary goals of this study were to quantify the temporal asynchrony and the error amplitudes in speed measurements recorded by a common bicycle computer over a wide area and over a long period. We acquired 96 hours of data at 1-second intervals simultaneously from three Garmin Edge 530 computers mounted to the same bicycle during road cycling in rural and urban environments. Each computer recorded speed data using a different method: two units were paired to two different external speed sensors and a third unit was not paired to any remote sensors and calculated its speed based on GPS data. We synchronized the units based on the speed signals and used one of the paired
Booth, Gabrielle R.Siegmund, Gunter P.
Accurate reconstruction of vehicle collisions is essential for understanding incident dynamics and informing safety improvements. Traditionally, vehicle speed from dashcam footage has been approximated by estimating the time duration and distance traveled as the vehicle passes between reference objects. This method limits the resolution of the speed profile to an average speed over given intervals and reduces the ability to determine moments of acceleration or deceleration. A more detailed speed profile can be calculated by solving for the vehicle’s position in each video frame; however, this method is time-consuming and can introduce spatial and temporal error and is often constrained by the availability of external trackable features in the surrounding environment. Motion tracking software, widely used in the visual effects industry to track camera positions, has been adopted by some collision reconstructionists for determining vehicle speed from video. This study examines the
Perera, NishanGriffiths, HarrisonPrentice, Greg
In cold and snowy areas, low-friction and non-uniform road surfaces make vehicle control complex. Manually driving a car becomes a labor-intensive process with higher risks. To explore the upper limits of vehicle motion on snow and ice, we use an existing aggressive autonomous algorithm as a testing tool. We built our 1:5 scaled test platform and proposed an RGBA-based cost map generation method to generate cost maps from either recorded GPS waypoints or manually designed waypoints. From the test results, the AutoRally software can be used on our test platform, which has the same wheelbase but different weights and actuators. Due to the different platforms, the maximum speed that the vehicle can reach is reduced by 1.38% and 2.26% at 6.0 m/s and 8.5 m/s target speeds. When tested on snow and ice surfaces, compared to the max speed on dirt (7.51 m/s), the maximum speed decreased by 48% and 53.9%, respectively. In addition to the significant performance degradation on snow and ice, the
Yang, YimingBos, Jeremy P.
The recent public release of the PPP-B2b service, along with advancements in multi-frequency and multi-GNSS systems, has opened up significant new opportunities for the development of Precise Point Positioning (PPP) technology. Utilizing the precise orbit and clock corrections provided by PPP-B2b and the increasing availability of multi-frequency signals, this paper introduces a novel tri-frequency, dual ionosphere-free PPP model based on PPP-B2b services. The model is designed with twelve unique tri-frequency combinations, tailored to various frequency choices, combination methodologies, and single/dual GNSS systems. Results from static positioning experiments indicate that the BDS-only tri-frequency dual ionosphere-free model offers substantial improvements over traditional models. Specifically, it achieves approximately a 25% increase in vertical accuracy and reduces convergence time by around 30% when compared to the BDS-only tri-frequency undifferenced uncombined model. This
Xu, DaweiGao, ChengfaXu, ZhenhaoZhan, KaidiGuo, Songlin
This study presents a method to evaluate the daily operation of traditional public transportation using multi-source data and rank transformation. In contrast with previous studies, we focuses on dynamic indicators generated during vehicle operation, while ignoring static indicators. This provides a better reference value for the daily operation management of public transport vehicles. Initially, we match on-board GPS data with network and stop coordinates to extract arrival and departure timetable. This helps us calculate dynamic operational metrics such as dwell time, arrival interval, and frequency of vehicle bunching and large interval. By integrating IC card data with arrival timetable, we can also estimate the number of people boarding at each stop and derive passenger arrival time, waiting time, and average waiting time. Finally, we developed a comprehensive dynamic evaluation method of public transportation performance, covering the three dimensions: bus stops, vehicles, and
Zhou, YangShao, YichangHan, ZhongyiYe, Zhirui
The exponential growth of the agribusiness market in Brazil combined with the high receptivity among farmers of new technological solutions has driven the study and implementation of high technology in the field. This work aimed to apply servo-assisted driving technology to enable autonomous mobility in an off-road sugarcane truck responsible for harvesting sugarcane. The technology consists of a conventional hydraulic steering with a motor, ECU and torque and angle sensors responsible for reading input data converted from GPS signals and previously recorded tracking lines. The motor responsible for replacing 100% of the physical force generated by the driver acts in accordance with the required torque demand, and the sensors combined with the ECU correct the course to meet the follow-up line through external communication ports. The accuracy of the system depends exclusively on the accuracy of the GPS signal, in this case reaching 2,5 cm, which is considered extremely high accuracy
Oliveira Santos Neto, AntídioLara, VanderleiSilva, EvertonDestro, DanielMoura, MárcioBorges, FelipeHaegele, Timo
There are certain situations when landing an Advanced Air Mobility (AAM) aircraft is required to be performed without assistance from GPS data. For example, AAM aircraft flying in an urban environment with tall buildings and narrow canyons may affect the ability of the AAM aircraft to effectively use GPS to access a landing area. Incorporating a vision-based navigation method, NASA Ames has developed a novel Alternative Position, Navigation, and Timing (APNT) solution for AAM aircraft in environments where GPS is not available.
A new scientific technique could significantly improve the reference frames that millions of people rely upon each day when using GPS navigation services, according to a recently published article in Radio Science.
A challenge of public transportation GPS data is the frequent utilization of monitoring systems with low sampling rates, primarily driven by the high costs associated with cellular data transmission of large datasets. Altitude data is often imprecise or not recorded at all in regions without large elevation changes. The low data quality limits the use of the data for further detailed investigations like a realistic energy consumption forecast for assessing the electrical grid load resulting from charging the vehicle fleet. Modern research often reconstructs speed data only, or uses additional GPS loggers, which is associated with increased costs in the vehicle fleet. The importance of precise and high-quality altitude data and specialized expertise in mountainous regions are frequently overlooked. This paper introduces an efficient new route matching method to reconstruct speed and respective road slope data of a GPS signal sampled at low frequency for a public transportation electric
Hitz, ArneKonzept, AnjaReick, BenediktRheinberger, Klaus
Radio frequency (RF) and microwave signals are integral carriers of information for technology that enriches our everyday life – cellular communication, automotive radar sensors, and GPS navigation, among others. At the heart of each system is a single-frequency RF or microwave source, the stability and spectral purity of which is critical. While these sources are designed to generate a signal at a precise frequency, in practice the exact frequency is blurred by phase noise, arising from component imperfections and environmental sensitivity, that compromises ultimate system-level performance.
In recent years, new technologies are being developed and applied to commercial vehicles. Such technologies support on development and implementation of new functions making these products safer, benefiting the society in general. One of the areas that can be mentioned is the vehicle safety. Among too many technologies, the emergency brake system is that one who came to support and assist drivers in critical situations that cannot be avoided. The Advanced Emergency Brake System, AEBS, consists of identifying other vehicles ahead, and, in case of detecting a risk of collision, automatically applies the service brakes to avoid accidents. The system works in situations when there is a sudden traffic stop, the vehicle is passing through intersections and when the driver distracts due to inappropriate use of mobile telephone devices. The aim of this work was to evaluate the emergency braking performance of a 6x4 tractor with a double semi-trailer, at flat asphalt. Both vehicles of
Dias, Eduardo MirandaRudek, ClaudemirTravaglia, Carlos Abflio PassosRodrigues, AndréBrito, Danilo
In the early 2010s, LightSquared, a multibillion-dollar startup promising to revolutionize cellular communications, declared bankruptcy. The company couldn't figure out how to prevent its signals from interfering with those of GPS systems. Now, Penn Engineers have developed a new tool that could prevent such problems from ever happening again: an adjustable filter that can successfully prevent interference, even in higher-frequency bands of the electromagnetic spectrum.
In the early 2010s, LightSquared, a multibillion-dollar startup promising to revolutionize cellular communications, declared bankruptcy. The company couldn’t figure out how to prevent its signals from interfering with those of GPS systems.
Digital mapping tools have become indispensable for road navigation. Applications like Waze and Google Maps harness the power of satellite imagery to provide precise visualization of GPS coordinates. The field advanced significantly in May 2023 with the introduction of dynamic 3D representations of the Earth. Companies such as Cesium now offer Unity3D and Unreal Engine Application Programming Interface that can be applied to geospatial applications. These images are no longer static and offer the opportunity to provide seamless continuous navigation. Driving simulation has been widely used for training and research. We investigate with this project the potential of this new geospatial database as a tool for scenario development to study manual and autonomous driving. We present an in-vehicle driving simulation integration that employs a real steering wheel and pedals from a stationary vehicle as controls. The visual experience is delivered through the Meta Quest Headset through an
Loeb, Helen S.Hernandez, JaimeLeibowitz, ChaseLoeb, BenjaminGuerra, ErickMangharam, Rahul
Bicycle computers record and store global position data that can be useful for forensic investigations. The goal of this study was to estimate the absolute error of the latitude and longitude positions recorded by a common bicycle computer over a wide range of riding conditions. We installed three Garmin Edge 530 computers on the handlebars of a bicycle and acquired 9 hours of static data and 96 hours (2214 km) of dynamic data using three different navigation modes (GPS, GPS+GLONASS, and GPS+Galileo satellite systems) and two geographic locations (Vancouver, BC, Canada and Orange County, CA, USA). We used the principle of error propagation to calculate the absolute error of this device from the relative errors between the three pairs of computers. During the static tests, we found 16 m to 108 m of drift during the first 4 min and 1.4 m to 5.0 m of drift during a subsequent 8 min period. During the dynamic tests, we found a 95th percentile absolute error for this device of ±8.04 m. This
Siegmund, Gunter P.Miller, Ian L.Booth, GabrielleLawrence, Jonathan M.
This paper addresses the issues of long-term signal loss in localization and cumulative drift in SLAM-based online mapping and localization in autonomous valet parking scenarios. A GPS, INS, and SLAM fusion localization framework is proposed, enabling centimeter-level localization with wide scene adaptability at multiple scales. The framework leverages the coupling of LiDAR and Inertial Measurement Unit (IMU) to create a point cloud map within the parking environment. The IMU pre-integration information is used to provide rough pose estimation for point cloud frames, and distortion correction, line and plane feature extraction are performed for pose estimation. The map is optimized and aligned with a global coordinate system during the mapping process, while a visual Bag-of-Words model is built to remove dynamic features. The fusion of prior map knowledge and various sensors is employed for in-scene localization, where a GPS-fusion Bag-of-Words model is used for vehicle pose
Chen, GuoyingWang, ZiangGao, ZhengYao, JunWang, Xinyu
RMIT University’s Arnan Mitchell and University of Adelaide’s Dr. Andy Boes led an international team to review lithium niobate’s capabilities and potential applications in the journal Science. The team is working to make navigation systems that help rovers drive on the Moon — where GPS is unable to work — later this decade.
A fundamentally different approach to wind estimation using unmanned aircraft than the vast majority of existing methods. This method uses no on-board flow sensor and does not attempt to estimate thrust or drag forces. Embry-Riddle Aeronautical University, Daytona Beach, Florida Traditionally, remotely piloted aircraft systems, or drones, have used onboard flow sensors to measure wind effects, producing in-flight metrics on which operators rely. Leveraging GPS instead, however, might provide more robust measurements, leading to safer, more efficient flights, according to Embry-Riddle Aeronautical University researchers. As most drones weigh less than 55 pounds, even mild gusts of wind can disrupt their flight, which makes finding creative solutions to monitor and predict hyperlocal weather conditions essential to flying without disruption or unplanned landings.
The safety of students during transportation on school buses is a paramount concern for both parents and schools. Although GPS (Global Positioning System) tracking systems are commonly used, they are limited in their ability to identify which students are on board. To ensure the safety and security of the students, this paper proposes a student authentication system based on facial recognition, people counter along with GPS vehicle tracking. This is intended to explore the advantages of these three technologies combined together for student authentication, the implementation process, and how it can improve the safety of school bus transportation.
Deshmukh, Kaustubh
Researchers have developed an algorithm that can “eavesdrop” on any signal from a satellite and use it to locate any point on Earth, much like GPS. The study represents the first time an algorithm was able to exploit signals broadcast by multi-constellation low-Earth orbit (LEO) satellites, namely Starlink, OneWeb, Orbcomm, and Iridium.
This recommended practice describes how to toughen a new or existing PNT system with the installation of inline GPS/GNSS jamming protection.
PNT Position, Navigation, and Timing
Northrop Grumman Woodland Hills, CA 224-200-7539
ABSTRACT Geotechnical site characterization is the process of collecting geophysical and geospatial characteristics about the surface and subsurface to create a 3-dimensional (3D) model. Current Robot Operating System (ROS) world models are designed primarily for navigation in unknown environments; however, they do not store the geotechnical characteristics requisite for environmental assessment, archaeology, construction engineering, or disaster response. The automotive industry is researching High Definition (HD) Maps, which contain more information and are currently being used by autonomous vehicles for ground truth localization, but they are static and primarily used for navigation in highly regulated infrastructure. Modern site characterization and HD mapping methods involve survey engineers working on-site followed by lengthy post processing. This research addresses the shortcomings for current world models and site characterization by introducing Site Model Geospatial System
Richards, Matthew E.Murphy, Kevin F.Toledo, Israel LopezSoylemezoglu, Ahmet
This SAE Aerospace Standard (AS) defines implementation requirements for the electrical interface between: a Aircraft carried miniature store carriage systems and miniature stores b Aircraft parent carriage and miniature stores c Surface-based launch systems and miniature stores The interface provides a common interfacing capability for the initialization and employment of smart miniature munitions and other miniature stores from the host systems. Physical, electrical, and logical (functional) aspects of the interface are addressed.
AS-1B Aircraft Store Integration Committee
While a majority of transportation and mobility solutions rely on in-vehicle sensors and the availability of the global positioning system (GPS) for absolute localization, alternate paradigms leveraging smart infrastructure have started becoming a viable solution for localization without needing GPS. However, the majority of approaches involving smart infrastructure require a means for wireless communication. In this article, we describe a novel method that can accurately localize the vehicle without using GPS and wireless communication by leveraging embedded digital and analog information on the roadside signage. The embedded information consists of a digital signature which can be used to cross-reference the ground truth (GT) location of the signage, as well as geometric information of the signage. This information is directly leveraged by on-vehicle sensors to generate absolute localization information. Specifically, the smart infrastructure consists of signage that is visible
Moosavi, SaminWeaver, AndrewGopalswamy, Swaminathan
The operational safety of Automated Driving System (ADS)-Operated Vehicles (AVs) are a rising concern with the deployment of AVs as prototypes being tested and also in commercial deployment. The robustness of safety evaluation systems is essential in determining the operational safety of AVs as they interact with human-driven vehicles. Extending upon earlier works of the Institute of Automated Mobility (IAM) that have explored the Operational Safety Assessment (OSA) metrics and infrastructure-based safety monitoring systems, in this work, we compare the performance of an infrastructure-based Light Detection And Ranging (LIDAR) system to an onboard vehicle-based LIDAR system in testing at the Maricopa County Department of Transportation SMARTDrive testbed in Anthem, Arizona. The sensor modalities are located in infrastructure and onboard the test vehicles, including LIDAR, cameras, a real-time differential GPS, and a drone with a camera. Bespoke localization and tracking algorithms are
Das, SiddharthRath, PrabinLu, DuoSmith, TylerWishart, JeffreyYu, Hongbin
The Daimler Detroit AssuranceⓇ 4.0 collision mitigation system is able to assist a driver in various aspects of safely operating their vehicle. One capability is the Active Brake Assist (ABA), which uses the Video Radar Decision Unit (VRDU) to communicate with the front bumper-mounted radar to provide information about potential hazards to the driver. The VRDU may warn the driver of potential hazards and apply partial or full braking, depending on the data being gathered and analyzed. The VRDU also records event data when an ABA event occurs. This data may be extracted from the VRDU using Detroit DiagnosticLink software. This paper presents an overview of the VRDU functionality and examines aspects of VRDU data such as the range and resolution of data elements, the synchronicity or timing of the recorded data, and application of the data for use in the analysis of crashes. Various tests were performed using a truck equipped with Detroit AssuranceⓇ 4.0 in a manner designed to trigger
Plant, DavidGrimes, WesleyCheek, TimothyAustin, TimothySteiner, JohnHiggins, BradleyLombardi, KristinaDiSogra, Matthew
First responders and traffic crash investigators collect and secure evidence necessary to determine the cause of a crash. As vehicles with advanced autonomous features become more common on the road, inevitably they will be involved in such incidents. Thus, traditional data collection requirements may need to be augmented to accommodate autonomous technology and the connectivity associated with autonomous and semi-autonomous driving features. The objective of this paper is to understand the data from a fielded autonomous system and to motivate the development of requirements for autonomous vehicle data collection. The issue of data ownership and access will be discussed. Additional complicating factors, such as cybersecurity concerns combined with a first responder’s legal authority, may pose challenges for traditional data collection. These additional challenges pose an opportunity to develop standardized event recording and embedded software verification processes to provide
Rayno, MarsSpan, TraeBrown, WestonDaily, Jeremy
Technology is ever advancing in the world around us, and it is no different when it comes to data acquisition systems used in accident reconstruction. In 2016, the SAE publication “Data Acquisition Using Smart Phone Applications,” Neale et al. evaluated the accuracy of basic fitness applications in tracking position within the smart phone itself [1]. In 2018, a follow up publication “Mid-Range Data Acquisition Units Using GPS and Accelerometers” tested the Harry’s Lap TimerTM application for use in smart phones and compared the data to the Race Logic VBOX [2]. In this paper, another data acquisition system, the MoTeC C185, was tested. The MoTeC C185 data logger contains an internal 3-axis accelerometer and was also equipped with an external Syvecs 50Hz GPS Module with 6-axis accelerometer. A test vehicle was instrumented with the MoTeC C185, Race Logic VBOX, and Harry’s Lap TimerTM. Data collected by the MoTeC C185 was then compared to data collected by the other acquisition systems to
Danaher, DavidMcDonough, SeanDonaldson, DrewCochran, Reece
Recent Tesla models contain four integrated onboard cameras that serve the Autopilot and Self-Driving Capabilities of the vehicle and act as a dashcam by recording footage to a local USB drive. The purpose of this study is to analyze the footage recorded by the integrated cameras and determine its suitability for speed determinations of both the host vehicle and surrounding vehicles through photogrammetry analyses. The front and rear cameras of the test vehicle (2019 Tesla Model 3) were calibrated for focal length and lens distortion characteristics. Two types of tests were performed to determine host vehicle speed: constant-speed and acceleration. Several frames from each test were analyzed. The distance between camera locations was used to gather vehicle speed through a time distance analysis. These speeds were compared to those gathered via the onboard GPS instrumentation. Two additional types of tests were performed to determine surrounding vehicle speeds: a vehicle approaching
Molnar, Benjamin T.Peck, Louis R.
Practical applications of recently developed sensor fusion algorithms perform poorly in the real world due to a lack of proper evaluation during development. Existing evaluation metrics do not properly address a wide variety of testing scenarios. This issue can be addressed using proactive performance measurements such as the tools of resilience engineering theory rather than reactive performance measurements such as root mean square error. Resilience engineering is an established discipline for evaluating proactive performance on complex socio-technical systems which has been underutilized for automated vehicle development and evaluation. In this study, we use resilience engineering metrics to assess the performance of a sensor fusion algorithm for vehicle localization. A Kalman Filter is used to fuse GPS, IMU and LiDAR data for vehicle localization in the CARLA simulator. This vehicle localization algorithm was then evaluated using resilience engineering metrics in the simulated
Fanas Rojas, JohanKadav, ParthBrown, NicolasMeyer, RickBradley, ThomasAsher, Zachary
Position accuracy is the critical ask of all Global Navigation Satellite Systems (GNSS), but errors like reflection, refraction, signal noise, clock errors, and multipath degrade the range computation between the satellite and the receiver. Incorrect range computation leads to errors in the receiver position. So minimizing the error in the range calculation improves the position accuracy. The differential pseudo-range technique uses two receivers, one of which is positioned at a precisely known location to compute the range error and the other receiver uses this error to improve its position accuracy. This paper explains an experiment conducted at a reference point and other five points within the range from 60 m to 120 m away from the reference point. Computing the accurate positions for those five points using the reference station is the objective of this experiment. The location of the reference point is precisely known and was measured accurately by the Survey of India (SOI). The
Sundara, Ramesh RajuRaju, G.
Visual Place Recognition (VPR) excels at providing a good location prior for autonomous vehicles to initialize the map-based visual SLAM system, especially when the environment changes after a long term. Condition change and viewpoint change, which influences features extracted from images, are two of the major challenges in recognizing a visited place. Existing VPR methods focus on developing the robustness of global feature to address them but ignore the benefits that local feature can auxiliarily offer. Therefore, we introduce a novel hierarchical place recognition method with both global and local features deriving from homologous VLAD to improve the VPR performance. Our model is weak supervised by GPS label and we design a fine-tuning strategy with a coupled triplet loss to make the model more suitable for extracting local features. In our proposed hierarchical architecture, we firstly rank the database to get top candidates via global features and then we propose a modified DTW
Fang, KaiLi, ZexingWang, Yafei
Historically, whenever the automotive solutions’ state of art reaches a saturation level, the integration of new verticals of technology has always raised new opportunities to innovate, enhance and optimize automotive solutions. The predictive powertrain solutions using connectivity elements (e.g., navigation unit, e-Horizon or cloud-based services) are one of such areas of huge interest in automotive industry. The prior knowledge of trip destination and its route characteristics has potential to make prediction of powertrain modes or events in certain order and therefore it can add value in various application areas such as optimized energy management, lower fuel consumption, superior safety and comfort, etc. However, when it comes to a point of commercializing such real applications with predictive function solutions, there could be various challenges such as micro-controller limitations, connectivity infrastructure limitations in varied geographical locations, cost sensitivity in
Golgar, SamratDhruv, Dhavaljin, Chen
Nowadays, real-world emissions and consumption behaviour of Light Duty (LDV) and Heavy Duty (HDV) vehicles are key factors in achieving greenhouse gas (GHG) targets. With the introduction of EURO VI in 2013 there were already low emission levels and real fuel consumption of new HDV vehicles. Furthermore, the available public literature regarding fuel consumption of European HDV vehicles is not very extensive. Hence, the development of an experimental activity related to HDVs real consumption measurement and the subsequent data analysis can be considered in this field. To this end, the fuel consumption data of four rear-loader garbage Diesel trucks, managed by a multiservice company in the Southern Italy, were collected during real use. Vehicles in pairs have different technical characteristics (i.e. engine capacity and maximum load capacity of the garbage). In this paper, we describe the methodology implemented to analyze the complete set of data (collected through questionnaires) from
Della Ragione, LiviaMeccariello, GiovanniPrati, Maria Vittoria
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.
Thompson, KyleJones, BenMartin, ScottBevly, David
ABSTRACT Many significant advances have been made in autonomous vehicle technology over the recent decades. This includes platooning of heavy trucks. As such, many institutions have created their own version of the basic platooning platform. This includes the California PATH program [1], Japan’s “Energy ITS” project [2], and Auburn University’sCACC Platform [3]. One thing these platforms have in common is a strong dependence on GPS based localization solutions. Issues arise when the platoon navigates into challenging environments, including rural areas with foliage which might block receptions, or more populated areas which might present urban canyon effects. Recent research focus has shifted to handling these situations through the use of alternative sensors, including cameras. The perception method proposed in this paper utilizes the You Only Look Once (YOLO) real-time object detection algorithm in order to bound the lead vehicle using both RGB and IR cameras. Range and bearing are
Flegel, TylerChen, HowardBevly, David
Many Connected and Automated Vehicle (CAV) applications assume that highly accurate positioning is always available. However, this is not the case in many real-life situations (e.g., when a satellite-based navigation system is used for positioning in urban canyons). Furthermore, very little research has been conducted to evaluate the impacts of position accuracy on CAV applications at the traffic level. The objective of this article is to investigate the positioning errors that could be tolerated by a sample of CAV applications. Toward this end, we (1) perform a general analysis of the positioning requirements of selected safety-, mobility- and environmental-focused applications and (2) examine in greater detail the effect of positioning errors on two representative CAV applications, Eco-Approach and Departure at Signalized Intersections (EAD) and High-Speed Differential Warning (HSDW). The results of (1) indicate that lane-level positioning accuracy is sufficient to enable most CAV
Williams, NigelDarian, Parisa BorhaniWu, GuoyuanClosas, PauBarth, Matthew
While stereo cameras and computer vision guide Deere's “limited release” 8R autonomous tractor, Bear Flag's lidar tech will augment future machines. Q&A with Deere's Joe Liefer John Deere got “really serious” about autonomy in 2019, according to Joe Liefer, senior product manager of autonomy at John Deere Intelligent Solutions Group. Three years later - after forming an in-house development team and acquiring some tech-startup expertise - the machinery maker revealed a fully autonomous tractor at CES 2022 that it claims is ready for large-scale production. Based on Deere's 8R tractor, the machine combines a TruSet-enabled chisel plow, GPS guidance system, advanced AI and six pairs of stereo cameras that enable 360-degree obstacle detection and distance calculation. The autonomous 8R tractor also continuously checks its position relative to a geofence and is accurate to within less than 1 inch (25 mm), Deere claims. Farmers monitor and control it from a smartphone app.
The GPS Radio Occultation and Ultraviolet — Colocated (GROUP-C) experiment was originally conceived in 2010 as a CubeSat mission, combining a compact GPS occultation receiver and high-sensitivity far-ultraviolet (FUV) photometer experiment to be flown as a Space Test Program experiment. The concept was to incorporate a commercial off-the-shelf GPS receiver and a small second-generation FUV photometer to replicate the space weather portion of the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC/FORMOSAT-3) mission at lower cost. In the same timeframe, the Air Force Space and Missile System Center initiated the Space Environment NanoSatellite Experiment (SENSE) to demonstrate several CubeSat technologies for space environment sensing, which included the Compact Tiny Ionospheric Photometer (CTIP) and the Compact Total Electron Content Sensor (CTECS).
The scope of this document is the concept of operations including reference system architecture, the user needs, the system functional and performance requirements, the messages, the corresponding data frames and elements, and other related functionality to enable V2X-based fee collection and other financial transactions.
Tolling Applications Technical Committee
NASA’ Deep Space Network (DSN), a sort of GPS system for space, relies on atomic clocks for extreme accuracy. Any modern navigation system must accurately time radio signals to triangulate a location. But the need for accuracy is even higher in space, where great distances can compound even tiny errors.
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