Browse Topic: Global positioning systems (GPS)

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Research on Deep Learning Navigation Algorithms for Helicopter Airborne Navigation2026-99-18647/17/2026
It is very hard to position helicopters in complex environments, and this severely limits their ability to navigate on their own. This paper proposes a navigation algorithm that uses a combination of different sensors and deep learning. It uses a special type of deep learning called ResNet50 and a special type of machine learning called LSTM. This algorithm extracts features of the environment and uses a Kalman filter to estimate the state of the system. The system is made more robust by merging information from multiple levels. The algorithm’s ability to maintain stable navigation in the face of faulty sensors is noteworthy, as is its use of an adaptive inference strategy that dynamically adjusts computational load. This strategy strikes a balance between performance and resource consumption. Experiments show that the plan works well in places where GPS is not available. This makes it much better for the helicopter to fly by itself, and it can be used in places like the army, for looking at places from the sky, and for helping people in danger.
Yang, Ming
Impact Study of Terrestrial Jamming on GNSS Receiver On-Board Launch Vehicles and Mitigation Technique Using RF Switch2026-26-07666/1/2026
Global Navigation Satellite System (GNSS) receivers are widely being used in aerospace as well as automotive applications primarily for navigation applications. ISRO uses indigenously developed GNSS receivers in its Launch vehicles (LV) mainly for POD (Preliminary Orbit Determination) and for INS aiding in long duration missions. Advanced GNSS receivers are being developed and used in ISRO’s new generation launch vehicles for closed loop guidance (CLG) applications. Being used in CLG, continuous solution availability and robustness of GNSS solutions are of paramount importance. From April 2023 onwards, GNSS receivers on-board ISRO’s LV missions have shown degraded performance in terms of reduction in no. of satellites tracked and in some cases loss of GNSS solution as well. This was seen in multiple missions and was analyzed in detail. It was observed that there is nearly 3-4dB reduction in carrier to noise density (C/No) ratio and corresponding change in RF AGC gain is also observed. The issue is seen when the LV’s ground trace is over a particular terrestrial area (latitude 7degN-10degN longitude 95degE-110degE). A survey on internet indicated presence of GPS interference/jamming signals from nearby region and aircraft pilots have also reported similar observations. This paper addresses the performance degradation observed due to terrestrial jamming in ISRO’s GNSS receiver and analysis of observation w.r.t reduction in carrier to noise ratio and RF AGC gains. Further details on anti-jamming techniques implemented in LV GNSS receivers using trajectory based jamming signal isolation using RF switch is also addressed in this paper. Future developments being pursued towards building resilience towards different threats including jamming and spoofing using dual RF-front end & other software techniques are also discussed in this paper.
A, Mohammed Basim, O T, Anand Shankara, V S, Biju, V Gopal, Biju, V S, Vinoj, K, Balan, C, Radhakrishna Pillai
Space Systems Command Looks Ahead to New Era of GPS Success26AERP06_076/1/2026
The successful launch of the final GPS-III satellite into orbit makes 32 total satellites in the GPS-III constellation, and paves the way for production and launch of GPS-IIIF satellites. Space Systems Command, El Segundo, CA With the successful launch of the 10th Global Positioning System III satellite on April 21 from Cape Canaveral Space Force Base, Space Systems Command is celebrating the start of a new era for the world's premier GPS constellation. “This milestone satellite launch completes GPS Block III,” said Erin Carper, Acting Portfolio Acquisition Executive for Satellite Communications and Positioning, Navigation, and Timing (PNT) at SSC. “Providing critical military and civil signal accuracy 24/7, GPS continues to underpin global military operations for our warfighters.”
Flight Test Results for Velocity Aided Navigation in GPS Denied EnvironmentsF-0082-2026-01295/5/2026
This paper presents the flight-test evaluation of a velocity-aided navigation solution that integrates inertial measurements with line-of-sight (LOS) Doppler velocity observations from the Psionic Navigation Doppler Lidar (PNDL) prototype to support navigation in GPS-denied environments. LOS velocity measurements collected during a helicopter flight-test campaign were first compared with velocities derived from an Applanix reference navigation system to assess measurement accuracy. The navigation solution was then developed and evaluated under simulated GPS-denied conditions by removing GPS aiding and continuing operation using LOS velocity measurements alone for extended periods. Results show that Doppler lidar velocity aiding effectively constrains inertial navigation error growth and maintains a stable navigation solution during prolonged GPS outages. These flight-test results demonstrate the utility of FMCW Doppler lidar velocity measurements as an enabling technology for Assured Positioning and Navigation (APN) and underscore its applicability to Contested Logistics operations, where resilient, GPS-independent navigation is essential for mission continuity.
Hull, Jason, Pierrottet, Diego, Monaco, Jeffrey
Integrated DBSCAN-Based Segmentation of Tractor Activity into Productive and Non-Productive States from GPS Data2026-01-01694/7/2026
Accurate identification of Productive and Non-Productive States or tractor duty cycles—comprising working, idle, and transport states—is critical for performance analysis, fuel optimization, and emissions modeling in agriculture machinery and fleet monitoring. This study explores the application of integrated unsupervised machine learning (ML) techniques to classify duty cycles using GPS-derived parameters such as speed, location variance, and temporal patterns. Unlike supervised approaches, the proposed method does not rely on several labeled engine and vehicle parameters, making it scalable and adaptable across diverse operational contexts. Clustering algorithm DBSCAN (Density-Based Spatial Clustering of Applications with Noise) in integration with hybrid rule-based and a road feature is employed to segment GPS data into distinct behavioral states. Feature engineering focuses on extracting motion signatures and spatial-temporal features that correlate with operational modes. Validation against manually annotated datasets demonstrates high accuracy in distinguishing idle, working, and transport phases. Furthermore, the present study demonstrates that by accurately determining the operational status of the tractor, unnecessary idling can be prevented through an idle avoidance system. Additionally, after assessing transport and working conditions, a movement-based control system for tire pressure adjustment is proposed. Both strategies have the potential to reduce fuel consumption by approximately 5-7%; however, this lies outside the scope of the present work. The framework offers a robust, data-driven solution for duty cycle monitoring and can be integrated into telematics systems for predictive maintenance and operational efficiency of the tractors.
Maharana, Devi prasad, Gangsar, Purushottam, Dharmadhikari, Nitin, Pandey, Anand Kumar
Bias and Uncertainty in the Time, Position, and Speed Data of Consumer-Grade GPS Devices2026-01-05444/7/2026
The goal of this study is to quantify the accuracy (bias) and precision (uncertainty) of the time, position, and speed data acquired by a range of consumer-grade devices (4 bike computers, 5 watches, 1 application on 3 smart phones, and a camera) that access Global Positioning System (GPS) satellite signals. We acquired data at each device’s maximum sampling rate (typically 1 Hz) during 207 minutes (twelve sessions of ~17 min) over 61.6 km of road cycling. The time and position data from these devices were compared to real-time kinematic (RTK) data acquired using a differential GPS system, and speed data from these devices were compared to a high-resolution wheel speed sensor synchronized to the RTK data in order to statistically estimate the bias and 95th percentile confidence intervals of the uncertainty of the devices’ data. Overall, we found the position and speed data from the devices generally lagged the reference by 4 s or less, although the lags between the speed and position data within a device were less (0.0 to 1.2 s) and more precise. We found small position biases (0.1 to 1.4 m), although the major axis of the 95th percentile confidence ellipses of the position uncertainties ranged from ±3.4 to ±7.2 m across the devices. The speed biases were also small (-0.6 to 0.0 m/s) and had 95th percentile confidence intervals that were between 0.35 and 1.04 m/s wide. These findings help establish the accuracy and uncertainty across a range of consumer-grade GPS-enabled devices and to probabilistically interpret these data for collision reconstruction purposes.
Booth, Gabrielle R., Mitchell, Alan L., Siegmund, Gunter P.
Identification of Productive and Non-Productive Activities in Agricultural Machinery Using ECU and GPS Parameters through Machine Learning2026-26-01021/16/2026
Any agricultural operation (such as cultivation, rotavation, ploughing, and harrowing) includes both productive and non-productive activities (like transportation, stops, and idling) in the field. Non-productive work can mislead the actual load profile, fuel consumption, and emissions. In this project, a machine learning-based methodology has been developed to differentiate between effective operations and non-productive activities, utilizing data collected in the field from data loggers installed on the machinery. Measurements were conducted on various machines across the country in all major applications to minimize the influence of any individual sample deviation and to account for variability in customer operating practices. Few critical parameters such as Engine Speed, Exhaust Gas Temperature, Actual Engine Percentage Torque, GPS Speed etc.) were selected after screening and analyzing more than 100 CAN and GPS parameters. The critical parameters were subsequently integrated with road features and various machine learning algorithms (such as KNN, Decision Tree, and Support Vector Machine (SVM). The results demonstrate that the current methodology effectively differentiates between productive operations and non-productive activities (such as transportation and idling) in major agricultural operations, thereby aiding in design-related decision-making
Maharana, Devi prasad, Gangsar, Purushottam, gokhale, Varun, Pandey, Anand Kumar
Risk Assessment and Identification of Freight Vehicle Trip Chains2025-99-042112/10/2025
Although the number of trucks is low, their accident rate is high, and the consequences of accidents are severe. This paper is based on GPS data from 100 trucks, with each trip chain defined by a vehicle’s stay time greater than 20 minutes. The kinematic parameters for each trip chain are then extracted, and the entropy weight method is used to calculate the weights of various parameters. A random forest model is applied to select 11 key indicators, including speed and acceleration. The entropy weight-TOPSIS algorithm is used to assess the risk of each trip chain for the trucks. Different combinations of continuous and discontinuous trip chain scenarios are constructed. Finally, support vector machines (SVM) and decision tree methods are used for risk prediction under different trip chain combinations. The results show that the 11 selected key indicators provide an accuracy of 95.74% for describing the sample. In general, the SVM model shows better prediction accuracy than the decision tree under different trip chain combinations, though the decision tree results fluctuate significantly. As the penalty parameter in SVM and the minimum leaf node in the decision tree increase, the accuracy of the model gradually decreases.
Huang, Yunhe, Xiong, Zhihua, Li, Jiayu
A New Method to Protect Aircraft Against GPS OutagesTBMG-5429612/1/2025
Dangling from a weather balloon 80,000 feet above New Mexico, a pair of antennas sticks out from a Styrofoam cooler. From that height, the blackness of space presses against Earth’s blue skies. But the antennas are not captivated by the breathtaking view. Instead, they listen for signals that could make air travel safer.
Machine Learning Based off-Road Vehicle Turn Identification Using Vehicle & GPS Parameters2025-28-034411/6/2025
Identification of different types of turns during field operation of off-road vehicles is critical in the overall vehicle development as it is helpful in identifying & optimizing machine performance, correct duty cycle, fuel economy, stability analysis, accurate path planning, customer usage pattern & designing the critical components, etc. In this study, a machine learning (ML) based methodology has been developed to detect the off-road vehicle turns using vehicle & GPS parameters. Three most common types of off-road vehicles turn conditions e.g., Straight line, Bulb turn, and Three-Point turn have been considered. Different vehicle parameters (like latitude & longitude, compass bearing, yaw rate, vehicle speed, swash plate angle, engine speed, percent load at vehicle speed, raise lower front & PTO channels) generated during field test have been used here. These vehicle parameters are further processed, analysed and used in ML learning model building. Four ML models e.g., SVM, K-NN, Gaussian Naïve Byes and Random Forest have been used here. Experimental results show that the present ML based methodology can identify most common vehicle turns considered in this study with a good accuracy.
Rai, Rohit, Gangsar, Purushottam, Joseph, Roberts, Malik, Manish, Dutta, Mausum, Fapal, Anand
Development of Anti-SideSlip Control for Motorcycles Using IMU2025-32-003711/3/2025
In motorcycle racing and other competitions, there is a technique to intentionally slide the rear wheel to make turns more quickly. While this technique is effective for high-speed riding, it is difficult to execute and carries risks such as falling. Therefore, an anti-sideslip control system that suppresses unintended or excessive sideslip is needed to ensure safe, natural, and smooth turning. In anti-sideslip control, the slip angle is usually used as a control parameter. However, for motorcycles, it is necessary to know the absolute direction of the vehicle's movement. To determine this, GPS or optical sensors are required, but using such sensors for driving is costly and may not provide accurate measurements due to contamination or other environmental factors, making it impractical. Therefore, an anti-sideslip control system was developed by calculating another parameter that indicates the characteristics of the slip angle, without measuring the slip angle itself, thus eliminating the need for impractical sensors. To detect sideslip, lean angles calculated using two different methods are used. The first lean angle calculates the true value even when side slip occurs, while the second lean angle shows a higher value than the true value when side slip occurs. The difference between these is defined as the slide amount, which can be detected as a parameter representing side slip. When a sideslip is detected, the drive force reduction control suppresses the sideslip to bring the slide amount closer to the target slide amount. To suppress sideslip, drive force reduction through ignition retardation is used. As an experiment, the slide amount obtained by the current method was compared with the values from a GPS device capable of calculating the slip angle. It was confirmed that the differential value of the slip angle obtained from the GPS and the slide amount had a very similar waveform. Furthermore, a test was conducted to verify whether the anti-sideslip control effectively suppressed sideslip during actual driving, and it was confirmed that applying this control allowed for more stable cornering. The effectiveness and validity of the anti-sideslip control were confirmed through the above experiment.
Nakano, Kyosuke, Kawai, Kazunori, Takeuchi, Michinori
Target Geolocation Method Based on Monocular Vision2025-99-002110/17/2025
In the intelligent traffic system (ITS), roadside sensing can obtain the movement status of various objects in the traffic scene in real time with a globalized perspective, which is of great significance for traffic flow optimization, accident early warning, and rescue afterwards. Accurate target positioning is one of the key links to realize these functions, which can not only help the traffic management department to grasp the traffic condition in time, but also provide the basis for rescue personnel to respond quickly when an accident occurs, so as to minimize the damage caused by the accident. Therefore, a method for acquiring the Global Positioning System (GPS) coordinates of objects relying on monocular surveillance installed on the roadside is proposed in this paper. By combining the target detection algorithm and the coordinate transformation method, and considering the information such as the installation status and internal parameters of the camera, the pixel positions of objects of interest are converted to GPS coordinates under the Global Navigation Satellite System (GNSS) by two different methods according to the known conditions in different situations. In order to evaluate the accuracy and stability of the method in practical applications, several sets of experiments in real scenes are conducted. The results of the experiments show that the latitude and longitude information of the objects in the camera-monitored scene can be estimated by our method in different intervals from the camera. Meanwhile, comparative analysis with other localization methods demonstrates the higher accuracy, feasibility, and superiority of our method.
Zhang, Nijia, Lu, Mingfeng, Chen, Ziyi, Zhang, Feng, Tao, Ran, Hu, Weidong, Fu, Xiongjun
Aerospace & Defense Technology: June 202525AERP066/5/2025
IQSat: Aitech’s AI-Enabled Picosatellite for Earth Observation and Imaging Applications Pushing the Boundaries of Rapid Production of Spacecraft: Flight Results from NearSpace Launch’s TROOP and ThinSat Platforms Transforming Satellite Antenna Technology for the Next Era of Aerospace and Defense Legacy in Action: The Enduring Role of MIL-STD-1553B Are Defense Satellites Ready for Space-Based Laser Communications? Microcomb Chips Could Improve Accuracy of GPS Systems Thermoelectric Generators Could Convert Waste Heat to Clean Energy in Jet Engines and Spacecraft Improving Electric Propulsion Thrusters for Future Spacecraft Missions A Satellite to Detect Short Gamma-Ray Burst Emissions In-Orbit Testing of Autonomous ‘Swarm’ Satellites NanoAvionics Satellite Suffers Space Debris Impact, Selfie Image Shows Damage
Microcomb Chips Could Improve Accuracy of GPS SystemsTBMG-532646/1/2025
Today, our mobile phones, computers, and GPS systems can give us very accurate time indications and positioning thanks to the over 400 atomic clocks worldwide. All sorts of clocks - be it mechanical, atomic or a smartwatch - are made of two parts: an oscillator and a counter. The oscillator provides a periodic variation of some known frequency over time while the counter counts the number of cycles of the oscillator. Atomic clocks count the oscillations of vibrating atoms that switch between two energy states with very precise frequency.
Effects on Motorcycle Response Data Using Wheel Force Transducers2025-01-00945/5/2025
Wheel Force Transducers (WFT) are precise and accurate measurement devices that seamlessly integrate into any vehicle. They can be applied in numerous vehicle applications for both on-road and in laboratory settings. The instrumentation requires replacing an original equipment manufacturer (OEM) wheel with a custom WFT system which is specific to the wheel hub design. An ideal design will minimally impact a vehicle's dynamics, but the vehicle system is inherently modified from the mass of the measurement device. Research and technical documentation have been published which provide conclusions explaining reduction in the unsprung mass reduces dynamic wheel load. However, there doesn’t appear to be clear compensation techniques for how a modified unsprung mass can be related to the original system, thus allowing the WFT signals to be more accurate to the OEM wheel forces. An experimental study was performed on a prototype motorcycle to better understand these differences. An instrumented “impact bump” acting as a force transducer was designed particularly for this testing to assist in characterizing the dynamic responses of a vehicle with variable unsprung mass setups. The motorcycle was equipped with WFTs to measure reaction forces, tri-axial accelerometers for vibration, linear variable differential transducers (LVDTs) for fork and shock travel, and a GPS to reference vehicle speed. The test variables included modifying the unsprung mass of the motorcycle’s front wheel by using OEM wheels, WFT systems, rim masses, hub masses, varying the speed of impact, and changing the motorcycle suspension setup. In this paper, there is consideration to the time domain and frequency domain for these changes in the system dynamic responses. There is discussion of correlation between measurement sensors and the relationship to the mass added from using WFT systems.
Frisco, Jacob, Larsen, William, Rhudy, Scott, Oosting, Nicholas, Laurent, Matthew
Quantifying the Uncertainty in Bicycle-Computer Speed Measurements2025-01-87014/1/2025
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 speed sensors as a reference. We found that the time, position, and speed recorded in the data files were not synchronized, although the lag between the speed and position data was consistently within 0 to 3 s. We then generated probability distributions that quantified the bias (median) and uncertainty (95th percentile interval) in the internal and external measures of speed. The biases were -0.10 m/s for the internally calculated speed and -0.02 m/s for the externally calculated speed. The uncertainty ranged from 1.14 m/s below to 0.47 m/s above the reference speed for the internally calculated speed, and from 0.51 m/s below to 0.47 m/s above the reference speed for the externally measured speed. This study provides useful baseline data for quantifying the temporal asynchrony, bias, and uncertainty of speed measurements recorded by bicycle computers.
Booth, Gabrielle R., Siegmund, Gunter P.
Aggressive Autonomous Control on Snow and Ice2025-01-80404/1/2025
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 failure cases during testing also reveal the process of losing control and the potential hazards, which also inspired us for future research directions.
Yang, Yiming, Bos, Jeremy P.
FIT File Processing for Accident Reconstruction2025-01-86964/1/2025
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 compared to the test platform data or written to .kml files using a custom MATLAB script and uploaded to Google Earth for comparison, which yielded the following conclusions. First, when imported into Google Maps, the latitude, longitude, and timestamp data from the .gpx and .tcx files matched the SDK data almost exactly; however, the speed data for the .gpx and .tcx files all appeared to be calculated via backwards differentiation of the GPS data, regardless of whether a wheel speed sensor was in use or not . Second, when imported into a spreadsheet, .gpx files contain no speed or distance data; on the contrary, .tcx files imported in Excel do report speed and distance data that exactly match the SDK data. Third, all the test files maintained generally the same number of data points as the SDK data (barring some minor discrepancies around auto-pauses) with the exception of the files produced by Golden Cheetah, which interpolated times and positions for missing data points to artificially produce 1 Hz resolution. Fourth, the SDK .csv file contained non-activity data - connected ANT+ and Bluetooth devices, hardware product model, software version, and more - that none of the other exported file types contained.
Sweet, David, Bretting, Gerald
Predictive Steering Angle Generation Algorithm for High Efficiency Vehicle’s Path Optimization2025-01-87914/1/2025
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 simulated state of the system. The results of the various steering angle simulations are collected and used by a cost function minimization algorithm. The performance target of the path optimization is described by the tunable parameters inserted in the algorithm’s cost function, allowing to prioritize speed or fuel consumption. The model is being tested and validated, with good accuracy (the error on the lap time is below 0.1%), on the vehicle track data obtained during 2023 and 2024 racing events and can be used as a basis for developing an automated race strategy algorithm for vehicle performance enhancement.
De Carlo, Matteo, Manzone, Simone, de Carvalho Pinheiro, Henrique, Carello, Massimiliana
Hierarchical Feature-Based Localization Using Scene Graphs in Off-Road Navigation2025-01-80464/1/2025
While numerous advancements have been made in autonomous navigation for structured indoor and outdoor environments, these solutions often do not generalize well to off-road settings. There are unique challenges in such settings such as unreliable GPS, limited computational and memory resources, and sparse environmental features, making navigation particularly difficult. In our work, we propose a novel data structure called Hierarchical Dynamic Scene Graphs (HDSG) to address these challenges. HDSG captures environmental information at different resolutions, integrating both geometric and semantic features. It enables various navigation tasks such as localization, loop closure, and human interaction through the visualization of environmental features for remote operators. We evaluated the performance of localizing a robot’s position within the world frame by comparing compact spatial descriptors extracted from semi-consecutive scene graphs, derived from 3D LiDAR point clouds. Compared to directly applying traditional Iterative Closest Point (ICP) algorithms on point clouds, our approach demonstrates that localization on scene graphs is more efficient and accurate. In evaluations using the RELLIS-3D dataset, the HDSG is constructed in at most 5 seconds using only commodity hardware. The overall memory footprint of the HDSG is very compact accounting for only 450-500 MB. Moreover, using the HDSG for robot localization has demonstrated faster and more precise results than using traditional ICP approaches directly on the input point cloud. These results highlight the potential of scene graph-based localization to deliver faster, more memory-efficient, and more accurate performance in unstructured off-road environments, showing a promising foundation for future enhancements and applications.
Alam, Fardifa Fathmiul, Luricich, Federico, Li, Nianyi, Jia, Yunyi, Li, Bing
Validation of SynthEyes for Use in Collision Reconstruction2025-01-86884/1/2025
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 accuracy and reliability of using one such 3D tracking software, SynthEyes, for this purpose. Dashcam footage of a VBOX-equipped test vehicle, in a 3D laser scanned environment, was processed using SynthEyes to track the camera and calculate vehicle speed based on an understanding of the dashcam’s average frame rate. The resulting speed profiles were analyzed and compared to the VBOX’s high-accuracy GPS data. Data processing methods were explored and evaluated to determine which, if any, filtering techniques reduced variability and best approximated the actual speed profile of the vehicle. The findings indicate that SynthEyes provides a viable solution for speed estimation in collision reconstruction across a wide range of vehicle motion, with potential errors minimized through use of a standardized workflow, importing 3D scene data, and appropriate data filtering. The software can be a valuable tool for accident reconstruction investigators.
Perera, Nishan, Griffiths, Harrison, Prentice, Greg
Evaluation of Several Tesla Dashcam Angles for Model 3 and Y via Reverse Project Photogrammetry2025-01-87004/1/2025
Tesla Model 3 and Model Y vehicles come equipped with a standard dashcam feature with the ability to record video in multiple directions. Front, side, and rear views were readily available via direct USB download. Additional types of front and side views were indirectly available via privacy requests with Tesla. Prior research neither fully explored the four most readily available camera views across multiple vehicles nor field camera calibration techniques particularly useful for future software and hardware changes. Moving GPS instrumented vehicles were captured traveling approximately 7.2 kph to 20.4 kph across the front, side, and rear views available via direct USB download. Reverse project photogrammetry projects and video timing data successfully measured vehicle speeds with an average error of 2.45% across 25 tests. Previously researched front and rear camera calibration parameters were reaffirmed despite software changes, and additional parameters for the side cameras calculated.
Jorgensen, Michael, Swinford, Scott, Imada, Kevin, Farhat, Ali
Dynamic Evaluation Method for Public Transport Operation Indicators Based on Rank Transformation2025-01-72192/21/2025
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 routes. This method uses K-means clustering to classify and applies rank transformation techniques to score. At stop levels, we use principal component analysis(PCA) to identify key influencing factors, anf apply K-means for clustering and service-level classification. At the vehicle and route level, we perform rank transformation on indicators such as average waiting time and vehicle bunching frequency. Delphi method is used to determine the relative weights of each indicator, so as to facilitate the ranking of bus routes according to the comprehensive score. This method is applicable to the dynamic operation indicators of 20 bus routes in Shenzhen, involving 293 vehicles and 506 stops. The results show that this method can effectively evaluate the dynamic operation of public transport and make contribution to daily management.
Zhou, Yang, Shao, Yichang, Han, Zhongyi, Ye, Zhirui
Route-Level Energy Efficiency Analysis of Pure Electric Buses: Key Influencing Factors and Optimized Suggestions2025-01-71842/21/2025
Currently, the adoption rate of pure electric buses is continuously increasing across cities nationwide, and their energy consumption costs have become an important component of urban bus operating expenses. The aim of this study is to explore significant factors related to energy savings for a bus route, which can help bus operators improve route energy efficiency and make resource allocation more reasonable. This study selects per capita energy consumption per thousand kilometers (PKEK) as the energy efficiency indicator and constructs a regression model with robust standard errors and a hierarchical clustering model using GPS operation data, total daily energy consumption data, and card swiping data from electric buses on eight routes in the same operational area of Nanjing from April 1 to June 10, 2021. The research results confirm the existence of significant variables affecting energy efficiency, primarily including: average speed, proportion of high-speed intervals, vehicle age, number of turns, whether it is a weekend, minimum distance between stations, average temperature, distance from the first station to the charging station, and number of seats. Based on these variables, the eight routes are classified into four types, i.e., Type I to Type IV routes, with significant differences in their energy efficiency distribution and a gradual decrease in performance. For Type III and Type IV routes with lower energy efficiency, this study offers targeted improvement suggestions in areas such as driver behavior, vehicle updates, charging station placement and vehicle scheduling. These suggestions point to some feasible directions at the route level for bus companies to reduce operating costs and promote green development.
Li, Muyang, Sun, Huayang, Li, Hong, Qian, Xiyou, Wang, Weining, Chen, Xuewu
Research on Triple-Frequency Dual-Ionosphere-Free Combination PPP Based on PPP-B2b Service2025-01-71572/21/2025
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 demonstrates the model's potential to enhance performance under static conditions. For dynamic positioning, the model proves equally effective. The four BDS-only tri-frequency dual ionosphere-free combinations show accuracy in the E and U directions comparable to that of the BDS-only four-frequency undifferenced uncombined model. However, in the N direction, the tri-frequency dual ionosphere-free combinations reach an average accuracy of 0.010m, which represents an approximate 40% improvement over the 0.017m achieved by the four-frequency undifferenced uncombined model. Additionally, these combinations reduce convergence time by about 30%.When GPS is incorporated, the dual-system tri-frequency combination offers even more benefits. Both in dynamic and static scenarios, the dual-system approach improves convergence time by 20% to 40% compared to single-system positioning, while also achieving slightly higher positioning accuracy. These findings underscore the effectiveness of the PPP-B2b service in optimizing PPP applications for both static and dynamic use cases.
Xu, Dawei, Gao, Chengfa, Xu, Zhenhao, Zhan, Kaidi, Guo, Songlin
Application of Servo-Assisted Technology in Commercial Vehicle Steering Systems for Autonomous Mobility in Off-Road Trucks. Case Study: Application on 8x2/8x4 Sugarcane Trucks2024-36-003312/20/2024
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 when comparing available technologies. The proposal was assembled on a national vehicle with a capacity of 31t in an 8x4 configuration, duly modified to meet the effort demands on typical national grounds and validated in the field through special test circuits. The use of the technology proved to be highly satisfactory and allowed an increase in efficiency of up to 7,5% compared to the use of conventional technology.
Oliveira Santos Neto, Antídio, Lara, Vanderlei, Silva, Everton, Destro, Daniel, Moura, Márcio, Borges, Felipe, Haegele, Timo
Vision-Based Approach and Landing System (VALS)TBMG-5219412/1/2024
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.
New Technique Could Improve GPS Navigation DevicesTBMG-5174610/1/2024
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.
Efficient GPS Route Matching Method for Battery Electric Bus Fleets2024-24-00269/18/2024
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 bus. To that end, an algorithm is presented which merges speed data with the corresponding altitude information. It accomplishes this by optimizing time segments of the resampled speed signal based on the distance traveled on the road, which is extracted via map matching. The optimized data feeds a verified longitudinal dynamics model of a battery electric bus and evaluates the energy consumption and battery SOC for different operating conditions. The consumption is compared to the energy consumption evaluated by a simulation model using high-frequency sampled real route data collected by a dedicated GPS data logger installed in a battery electric bus to verify the algorithm. The proposed method reconstructs and approximates the driven route (speed and slope) with high resolution. Therefore, it enables model-based predictions for the bus fleet for different operating conditions e.g. ambient temperature, battery age or loading. The method facilitates the optimization of fleet operations, focusing on battery sizing, charging management and energy grid conservation. In subsequent works, the toolchain is integrated into an ecosystem supporting bus and energy grid operators.
Hitz, Arne, Konzept, Anja, Reick, Benedikt, Rheinberger, Klaus
Everyday Life, Improved by Light: GRYPHON’s Photonic DiscoveriesTBMG-514689/1/2024
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.
Emergency Braking System: Verification of system behavior on commercial vehicles equipped with drum braking system2024-36-03098/9/2024
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 combination were equipped with drum brakes. To monitor the braking performance, the vehicle speed, the brake temperature, and braking pressure were collected using, respectively, a global positioning system, GPS, thermocouples and pressure transducers. The dynamic tests were performed according to the ECE R131 European resolution, using a balloon car as target. An additional driving condition was simulated during the tests: elevated temperature level of the brakes. The tests led to the conclusion that the efficiency during emergency braking, under normal and critical conditions, fulfilled the requirements without any stability and drivability degradation. Regardless of the temperature, the system remained operating within the established technical limits. It was therefore concluded that the emergency braking system, on vehicle combination using drum brakes, met the requirements established by resolution ECE R131 in a fully satisfactory manner.
Dias, Eduardo Miranda, Rudek, Claudemir, Travaglia, Carlos Abflio Passos, Rodrigues, André, Brito, Danilo
To 6G and Beyond: Penn Engineers Unlock the Next Generation of Wireless CommunicationsTBMG-512458/1/2024
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.
To 6G and Beyond: Penn Engineers Unlock the Next Generation of Wireless Communications24AERP08_078/1/2024
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.
Quantifying Uncertainty in Bicycle-Computer Position Measurements2024-01-24864/9/2024
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 error was mildly sensitive to the navigation system being used (GPS+Galileo had slightly smaller errors) and more sensitive to the geographic location where the data were acquired (BC errors were larger than CA errors). An absolute error of ±8.04 m is relatively large and limits a forensic investigator’s ability to precisely locate a bicycle within a crash scene based solely on data from this device.
Siegmund, Gunter P., Miller, Ian L., Booth, Gabrielle, Lawrence, Jonathan M.
Leveraging the Internet to Drive a Real Car in the Virtual Earth 3D Model2024-01-28784/9/2024
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 overlay in a Mixed Reality environment. Two case scenarios are examined. The first case involves navigating downtown Denver. The use of photorealistic representations of Denver's buildings offers an immersive experience, although the 3D topology presents some irregularities. These irregularities result from the limited number of polygons used for the digital modeling, especially on flat surfaces like roads and pavements. The second scenario leverages the hilly landscapes outside Denver. These areas, characterized by arid, treeless terrain typical of Colorado, offer a smooth driving experience. Still, the technology incorporates projection such as phantom cars, flat images of vehicles on the roadway that were captured during satellite data acquisition. We explore opportunities to address these inaccuracies and enhance the environment for a more realistic and immersive driving experience.
Loeb, Helen S., Hernandez, Jaime, Leibowitz, Chase, Loeb, Benjamin, Guerra, Erick, Mangharam, Rahul
High-Precision Autonomous Parking Localization System based on Multi-Sensor Fusion2024-01-28434/9/2024
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 initialization. Finally, Error-State Kalman filtering is conducted for point cloud matching and IMU pre-integration information, resulting in filtered accurate poses. In our Bag-of-Words-based localization approach, YOLO object detection is used to exclude keyframes that may have dynamic features. When the vehicle reaches a similar scene, it triggers pose optimization to improve the accuracy and stability of initial localization. This paper validates the proposed SLAM system on multiple sequences of KITTI dataset to demonstrate the accuracy of prior maps. Finally, a vehicle platform was built for localization experiments in parking scenarios. In the absence of sufficient GPS signal, the optimal RMSE of the trajectory can reach 5.24cm, with an angle error within 0.35 °.
Chen, Guoying, Wang, Ziang, Gao, Zheng, Yao, Jun, Wang, Xinyu
Light-Based Tech to Navigate the MoonTBMG-503914/1/2024
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.
New Method to Measure Wind Speed Could Unlock Drones' Potential24AERP02_072/1/2024
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.
School Bus Safety: Enhanced Security through People Counter and Face Recognition System2024-26-02361/16/2024
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
Exploiting Signals Broadcast by Multi-Constellation LEO SatellitesTBMG-4960312/1/2023
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.
Toughening a PNT System with COTS Inline GPS/GNSS Jamming ProtectionSAE1026 (Current)11/20/2023
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
Next Generation Airborne Navigation SystemTBMG-489709/1/2023
Northrop Grumman Woodland Hills, CA 224-200-7539
A SEMANTICALLY CLASSIFIED GEO-SPATIAL 3D OCTREE VOXEL BASED SYSTEM FOR GEOTECHNICAL SITE CHARACTERIZATION2024-01-40538/10/2023
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 (SMGS). This site model leverages an octree spatial data model to store heterogeneous geotechnical information in a Volumetric Pixel (Voxel) grid, which allows for more efficient algorithms in data analysis and fusion. SMGS provides a real-time, dynamically updated, 3D data model with semantically derived costmaps for navigation and Engineer operations, ground truth localization without GPS, and produces standard Geographic Information System (GIS) maps. Citation: M. Richards, K. Murphy, I. Lopez Toledo, A. Soylemezoglu, “A Semantically Classified Geo-spatial 3D Octree Voxel Based System for Geotechnical Site Characterization,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 15-17, 2023.
Richards, Matthew E., Murphy, Kevin F., Toledo, Israel Lopez, Soylemezoglu, Ahmet
Interface Standard, Miniature Mission Store InterfaceAS5725C (Current)5/22/2023
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
Localization in Global Positioning System–Denied Environments Using Infrastructure-Embedded Analog-Digital Information12-06-04-00295/11/2023
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 primarily in the infrared (IR) spectrum. A specialized camera that is optimized to read the digital signature extracts the analog information associated with the signage (ground truth and geometry). This is then used by both the camera, as well as a millimeter (mm)-wave radar to produce independent localization information. The camera and radar information are correlated with the signage information using a global nearest neighbor algorithm, followed by fusion with vehicle odometry using an extended Kalman filter (EKF) to generate accurate localization of the vehicle. The EKF is set up to manage asynchronous observations between the camera, radar, and vehicle odometry. The proposed method is implemented to localize a vehicle without the aid of GPS, and the results show consistent localization with the root mean squared (RMS) longitudinal and lateral errors less than 0.46 m and 0.19 m, respectively.
Moosavi, Samin, Weaver, Andrew, Gopalswamy, Swaminathan
Data Collection for Incident Response for Vehicles with Autonomous Systems2023-01-06284/11/2023
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 sufficient data to replace firsthand vehicle operator accounts in autonomous vehicles. For this work, an autonomous mobile impact attenuator vehicle system was used to gather data that may appear from potential crash incidents. Data obtained from a combination of vehicle data from the J1939 networks, a precision GPS system as a truth source, and the onboard autonomy sensor logs for the attenuator vehicle was analyzed for completeness and usefulness in describing the incident that occurred. Findings indicate a shift in technique and strategy is needed for incident data collection for autonomous vehicles. Potential issues in the duration of the recording are also presented and discussed.
Rayno, Mars, Span, Trae, Brown, Weston, Daily, Jeremy
Comparison of Infrastructure- and Onboard Vehicle-Based Sensor Systems in Measuring Operational Safety Assessment (OSA) Metrics2023-01-08584/11/2023
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 created for the LIDAR and cameras. In total, there are 26 different scenarios of the test vehicles navigating the testbed intersection; for this work, we are only considering car following scenarios. The LIDAR data collected from the infrastructure-based and onboard vehicle-based sensors system are used to perform object detection and multi-target tracking to estimate the velocity and position information of the test vehicles and use these values to compute OSA metrics. The comparison of the performance of the two systems involves the localization and tracking errors in calculating the position and the velocity of the subject vehicle, with the real-time differential GPS data serving as ground truth for velocity comparison and tracking results from the drone for OSA metrics comparison.
Das, Siddharth, Rath, Prabin, Lu, Duo, Smith, Tyler, Wishart, Jeffrey, Yu, Hongbin
Validation of MoTeC Data Acquisition System2023-01-06304/11/2023
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 validate the capabilities of the MoTeC C185. The purpose of this paper is to validate the MoTeC data acquisition system to provide an alternative for use in the field of accident reconstruction.
Danaher, David, McDonough, Sean, Donaldson, Drew, Cochran, Reece
Quantitative Resilience Assessment of GPS, IMU, and LiDAR Sensor Fusion for Vehicle Localization Using Resilience Engineering Theory2023-01-05764/11/2023
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 multipath and overpass scenario. These scenarios were developed in the CARLA simulator by collecting real-world data in an overpass and multipath scenario using WMU’s research vehicle. The absorptive, adaptative, restorative capacities, and the overall resilience of the system was assessed by using the resilience triangle. Simulation results indicate that the vehicle localization pipeline possesses a higher quantitative resilience when encountering overpass scenarios. Nevertheless, the system obtained a higher adaptive capacity when encountering multipath scenarios. These resilience engineering metrics show that the fusion systems recover faster when encountering disturbances due to signal interference in overpasses and that the system is in a disturbed state for a shorter duration in multipath scenarios. Overall these results demonstrate that resilience engineering metrics provide valuable insights regarding complicated systems such as automated vehicle localization. In future work, the insights from resilience engineering can be used to improve the design and thus performance of future localization algorithms.
Fanas Rojas, Johan, Kadav, Parth, Brown, Nicolas, Meyer, Rick, Bradley, Thomas, Asher, Zachary
Evaluation of Tesla Dashcam Video System for Speed Determination Via Reverse Projection Photogrammetry2023-01-06294/11/2023
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 from the rear and an offset vehicle approaching from the front. For both tests, the Tesla was stationary. Several frames from each test were analyzed via reverse projection, using a point cloud of the approaching vehicles. The speeds obtained through photogrammetry were compared to GPS instrumentation onboard the approaching vehicle. The mean difference between photogrammetry and GPS instrumentation ranged between 0.38 and 0.72 mph across all tests.
Molnar, Benjamin T., Peck, Louis R.
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