Browse Topic: Active safety systems

Items (1,781)
ABSTRACT In any active safety system, it is desired to measure the “performance”. For the estimation case, generally a cost function like Mean-Square Error is used. For detection cases, the combination of Probability of Detection and Probability of False Alarm is used. Scenarios that would really expose performance measurement involve complex, dangerous and costly driving situations and are hard to recreate while having a low probability of actually being acquired . Using a virtual tool, we can produce the trials necessary to adequately determine the performance of active safety algorithms and systems. In this paper, we will outline the problem of measuring the performance of active safety algorithms or systems. We will then discuss the approach of using complex scenario design and Monte Carlo techniques to determine performance. We then follow with a brief discussion of Prescan and how it can help in this endeavor. Finally, two Monte Carlo type examples for particular active safety
Gioutsos, TonyBlackburn, Jeff
ABSTRACT This paper will document the development of the Convoy Active Safety Technology (CAST) program, which was created to design a low cost, optionally manned vehicle (OMV) solution for tactical wheeled vehicle (TWV) fleet. This paper will describe the approach taken to integrate low cost sensors for understanding the environment sufficiently to accomplish convoy missions. This paper will also discuss the approach taken to develop the low cost guidance and navigation solution used in the CAST program
Simon, DavidTheisen, Bernard
ABSTRACT Over time, the National Institute of Standards and Technology (NIST) has refined the 4Dimension / Real-time Control System (4D/RCS) architecture for use in Unmanned Ground Vehicles (UGVs). This architecture, when applied to a fully autonomous vehicle designed for missions in urban environments, can greatly assist in the process of saving time and lives by creating a more intelligent vehicle that acts in a safer and more efficient manner. Southwest Research Institute (SwRI®) has undertaken the Southwest Safe Transport Initiative (SSTI) aimed at investigating the development and commercialization of vehicle autonomy as well as vehicle-based telemetry systems to improve active safety systems and autonomy. This paper will discuss the implementation of the 4D/RCS architecture to the SSTI autonomous vehicle, a 2006 Ford Explorer
McWilliams, GeorgeBrown, Michael
ABSTRACT This paper will describe the demonstrations that the Autonomous Mobility Appliqué System (AMAS) program has completed to date. First providing a high level technical overview of the system to understand how the system and its subsystems work. The paper will then describe the demonstrations and a summary of the results of the demonstrations
Schoenherr, EdwardTheisen, BernardWilliams, KennethSimon, David
ABSTRACT The real-world testing of robotic and autonomous vehicles faces many challenges including: safety; feasibility; effectiveness; expense; and timeliness. The development of high performance computing has created innumerable opportunities for effectively and efficiently processing large data sets. These data sets can range from modeling and simulation scenarios to the vast amounts of complex data being gathered by unmanned vehicles. In all cases, the data needs to be stored, managed, and processed to have usable information to drive smart decision making. Leveraging high performance computing to more efficiently, effectively, and economically conduct robotic and autonomous vehicle testing in a virtual environment is a logical step. Consequently, TARDEC has developed a real-time modeling and simulation capability to test and evaluate autonomy solutions while RAVE has designed and developed a specialized high performance computing system for TARDEC to support this capability
Rosenberger, KarlBlackmer, SaraWesoloski, SteveBrabbs, John
ABSTRACT Connected and automated vehicles (CAVS) have the potential to improve fuel economy by changing the way vehicles are driven. Fuel economy can be improved through a wide range of technologies, many of which do not require Level 5 automation. One of the most promising technologies is a smart cruise control that uses a speed-matching algorithm to account for fuel economy. Accounting for fuel economy in the algorithm leads to different driving behavior than simply matching the driver-entered set speed. This paper describes how such a smart cruise control could be applied to a class 8 vehicle both in simulation and in the actual vehicle on a closed test track. It evaluates the algorithm and describes the correlation procedure used to calibrate the model using test data from the vehicle
Sharer, PhillipRousseau, AymericKarbowski, DominikShen, DaliangHeim, ScottGonyou, Kevin MarkRizzo, DeniseRagatz, AdamGonder, JeffProhaska, RobertSong, Jae
ABSTRACT This paper describes a simulation model for autonomous vehicles operating in highly uncertain environments. Two elements of uncertainty are studied – rain and pedestrian interaction – and their effects on autonomous mobility. The model itself consists of all the essential elements of an autonomous vehicle: Scene -roads, buildings, etc., Environment - sunlight, rain, snow, etc., Sensors - gps, camera, radar, lidar, etc., Algorithms - lane detection, pedestrian detection, etc., Control - lane keeping, obstacle avoidance, etc., Vehicle Dynamics – mass, drivetrain, tires, etc., and Actuation - throttle, braking, steering, etc. Using this model, the paper presents results that assess the autonomous mobility of a Polaris GEM E6 type of vehicle in varying amounts of rain, and when the vehicle encounters multiple pedestrians crossing in front. Rain has been chosen as it impacts both situational awareness and trafficability conditions. Mobility is measured by the average speed of the
Alghodhaifi, HeshamLakshmanan, SridharBaek, StanleyRichardson, Paul
ABSTRACT Popularity of Advanced Driver Assistance Systems (ADAS) in the passenger car industry has seen an explosive growth in recent years. Some ADAS that are becoming ubiquitous are Lane Departure Warning (LDW), Blind Spot Detection (BSD) and automatic parking or parking assistance systems. In many cases, such systems had been developed specifically to handle the most demanding driving conditions at very high speeds, which typically require very sophisticated software and high-power hardware. However, in the other application areas or geographical regions, such sophistication often hinders adoption of the technology. An alternate approach is to use off-the-shelf (OTS) component as much as possible so that similar systems with an appropriate subset of functions can be developed cheaply and quickly. The approach similar to the NASA’s “PhoneSats” program is discussed in this paper
Bae, HongJiang, YiHennessy, Chris
ABSTRACT The transportation industry annually travels more than 6 times as many miles as passenger vehicles [1]. The fuel cost associated with this represents 38% of the total marginal operating cost for this industry [8]. As a result, industry’s interest in applications of autonomy have grown. One application of this technology is Cooperative Adaptive Cruise Control (CACC) using Dedicated Short-Range Communications (DSRC). Auburn University outfitted four class 8 vehicles, two Peterbilt 579’s and two M915’s, with a basic hardware suite, and software library to enable level 1 autonomy. These algorithms were tested in controlled environments, such as the American Center for Mobility (ACM), and on public roads, such as highway 280 in Alabama, and Interstates 275/696 in Michigan. This paper reviews the results of these real-world tests and discusses the anomalies and failures that occurred during testing. Citation: Jacob Ward, Patrick Smith, Dan Pierce, David Bevly, Paul Richardson
Ward, JacobSmith, PatrickPierce, DanBevly, DavidRichardson, PaulLakshmanan, SridharArgyris, AthanasiosSmyth, BrandonAdam, CristianHeim, Scott
ABSTRACT Unmanned ground vehicles (UGVs) that autonomously maneuver over off-road terrain are susceptible to a loss of stability through untripped rollovers. Without human supervision and intervention, untripped rollovers can damage the UGV and render it unusable. We create a runtime monitor that can provide protection against rollovers that is independent of the type of high-level autonomy strategy (path planning, navigation, etc.) used to command the platform. In particular, we present an implementation of a predictive system monitor for untripped rollover protection in a skid-steer robotic platform. The system monitor sits between the UGV’s autonomy stack and the platform, and it ensures that the platform is not at risk of rollover by intercepting mobility commands sent by the autonomy stack, predicting platform stability, and adjusting the mobility commands to avoid potential rollovers. We demonstrate our implementation through experiments with skid-steer UGVs in Gazebo simulation
Dietrich, ElizabethPohland, SaraGenin, DanielSchmidt, AuroraVallabha, GautamComposto, AnthonyRandolph, Marcus
ABSTRACT The Army has identified an operational need for a Robotic Convoy capability for its tactical vehicle fleets. The Department of Defense (DoD), with a fleet of over several hundred thousand tactical vehicles, must identify an approach with supporting technology and supply base to procure and support a Robotic Convoy solution at the lowest possible cost. While cost is a key driver, the selected system approach must be proven and robust to ensure the safety of our soldiers and the supply chain. An effective approach is to integrate and adapt the advanced automotive technologies, components and suppliers currently delivering advanced safety technologies into the automotive market. These advanced automotive technologies merged with DoD robotics enhancements in tactical behaviors, autonomous driving, command & control and unmanned systems collaboration will advance the operational utility of robotic convoy application in manned and unmanned modes. Figure 1 Military Application The
Coplen, Christina E.Lane, Gerald R.
ABSTRACT In order to expedite the development of robotic target carriers which can be used to enhance military training, the modification of technology developed for passenger vehicle Automated Driver Assist Systems (ADAS) can be performed. This field uses robotic platforms to carry targets into the path of a moving vehicle for testing ADAS systems. Platforms which are built on the basis of customization can be modified to be resistant to small arms fire while carrying a mixture of hostile and friendly pseudo-soldiers during area-clearing and coordinated attack simulations. By starting with the technology already developed to perform path following and target carrying operations, the military can further develop training programs and equipment with a small amount of time and investment. Citation: M. Bartholomew, D. Andreatta, P. Muthaiah, N. Helber, G. Heydinger, S. Zagorski, “Bringing Robotic Platforms from Vehicle Testing to Warrior Training,” In Proceedings of the Ground Vehicle
Bartholomew, MeredithAndreatta, DaleMuthaiah, PonaravindHelber, NickHeydinger, GaryZagorski, Scott
ABSTRACT Over time, the National Institute of Standards and Technology (NIST) has refined the 4Dimension / Real-time Control System (4D/RCS) architecture for use in Unmanned Ground Vehicles (UGVs). This architecture, when applied to a fully autonomous vehicle designed for missions in urban environments, can greatly assist in the process of saving time and lives by creating a more intelligent vehicle that acts in a safer and more efficient manner. Southwest Research Institute (SwRI®) has undertaken the Southwest Safe Transport Initiative (SSTI) aimed at investigating the development and commercialization of vehicle autonomy as well as vehicle-based telemetry systems to improve active safety systems and autonomy. This paper will discuss the implementation of the 4D/RCS architecture to the SSTI autonomous vehicle, a 2006 Ford Explorer
McWilliams, GeorgeBrown, Michael
ABSTRACT The effective and safe use of Rough Terrain Cargo Handlers is severely hampered by the operator’s view being obstructed. This results in the inability to see a) in front of the vehicle while driving, b) where to set a carried container, and c) where to maneuver the vehicles top handler in order to engage with cargo containers. We present an analysis of these difficulties along with specific solutions to address these challenges that go beyond the non-technical solution currently used, including the placement of sensors and the use of image analysis. These solutions address the use of perception to support autonomy, drive assist, active safety, and logistics
Beach, GlennHaanpaa, DouglassMoody, GaryMahal, PritpaulRowe, SteveSiebert, GaryBurkowski, JimCohen, Charles J.
In this paper, a single-chip based design for an automotive 4D millimeter -wave radar is proposed. Compared to conventional 3D millimeter-wave radar, this innovative scheme features a MIMO antenna array and advanced waveform design, significantly enhancing the radar's elevation measurement capabilities. The maximum measurement error is approximately ±0.3° for azimuth within ±50° and about ±0.4° for elevation within ±15°. Extensive road testing had demonstrated that the designed radar can routinely measure targets such as vehicles, pedestrians, and bicycles, while also accurately detecting additional objects like overpasses and guide signs. The cost of this radar is comparable to that of traditional automotive 3D millimeter-wave radar, and it has been successfully integrated into a forward radar system for a specific vehicle model
Cai, YongjunZhang, XianshengBai, JieShen, Hui-LiangRao, Bing
Advances in vehicle sensing and communication technologies are enabling new opportunities for intelligent driver assistance systems that enhance road safety and performance. This paper provides a comprehensive review of recent research on two complementary areas: haptic/tactile interfaces for conveying road terrain and hazard information to drivers, and shared control frameworks that employ assistive automation to supplement driver inputs. Various haptic feedback techniques for generating realistic road feel through steering wheel torque overlays, pedal interventions, and alternative interface modalities are examined. Control assistance approaches integrating environmental perception to provide steering, braking, and collision avoidance support through blended human–machine control are also analyzed. The paper scrutinizes methods for road sensing using cameras, LiDAR, and radar to classify terrain for adapting system response. Evaluation practices across this domain are critically
Shata, Abdelrahman Ali AdelNaghdy, FazelDu, Haiping
Advanced Driver Assistance Systems (ADAS) is a growing technology in automotive industry, intended to provide safety and comfort to the passengers with the help of variety of sensors like radar, camera, Light Detection and Ranging (LIDAR) etc. The camera sensors in ADAS used extensively for the purpose of object detection and classification which are used in functions like Traffic sign recognitions, Lane detections, Object detections and many more. The development and testing of camera-based sensors involves the greater technologies in automotive industry, especially the validation of camera hardware and software. The testing can be done by various processes and methods like real environment test, model-based testing, Hardware, and Software in loop testing. A fully matured ADAS camera system in the market comes after passing all these verification processes, yet there are lot of new failures popping up in the field with this ADAS system. Since ADAS is an evolving technology, many new
R, ManjunathSaddaladinne, JagadeeshPachaiyappan, Sathish
The advancements towards autonomous driving have propelled the need for reference/ground truth data for development and validation of various functionalities. Traditional data labelling methods are time consuming, skills intensive and have many drawbacks. These challenges are addressed through ALiVA (automatic lidar, image & video annotator), a semi-automated framework assisting for event detection and generation of reference data through annotation/labelling of video & point-cloud data. ALiVA is capable of processing large volumes of camera & lidar sensor data. Main pillars of framework are object detection-classification models, object tracking algorithms, cognitive algorithms and annotation results review functionality. Automatic object detection functionality creates a precise bounding box around the area of interest and assigns class labels to annotated objects. Object tracking algorithms tracks detected objects in video frames, provides a unique object id for each object and
Mardhekar, AmoghPawar, RushikeshMohod, RuchaShirudkar, RohitHivarkar, Umesh N.
The primary purpose of the active safety feature is to reduce the danger of a collision between the car and an obstruction. To improve occupant safety, active safety systems must be included on all new vehicles; nonetheless, not all incidents are preventable. The frequency of incidents on the road has recently increased in tandem with the number of cars, making it critical to investigate the crashworthiness of a vehicle because human life is at the top of the priority list. This study examines an occupant's responses prior to a crash event, as well as studies into how occupant posture influences injury data. Most of the existing research focuses on the pre-crash event or the occupant's optimal seated position. However, it is critical to understand an occupant's reflex or behavior during the pre-crash event, when the occupant is typically not in an appropriate seating posture due to the panic reflex. As a result, an occupant's reflex in a panic situation will change their seating
Shankara Murthy, SantoshSrinivasa, PraveenCK, UmeshPatil, ShubhamJois, Rahul
Automatic emergency braking (AEB) systems play a crucial role in enhancing vehicular safety. Current research predominantly focuses on the longitudinal dynamics of vehicles, utilizing various control algorithms to improve braking effectiveness. However, there has been limited exploration into utilizing wheel deflection as a method to further enhance emergency braking performance. This study aims to contribute by proposing an advanced enhancement of the AEB system through coordinated wheel deflection strategies. In an emergency situation, when the speed of AEB-equipped vehicle drops to the set threshold due to wheel braking, the innovative control system will activate. The vehicle’s coaxial wheels will then execute a counter-deflection maneuver to maximize friction between the tires and the road surface. As a result, this approach reduces braking distance, thereby enhancing vehicle safety. The effectiveness of the proposed control algorithm is validated through combined simulation using
Lai, FeiXiao, HaoHuang, Chaoqun
India is a diverse country in terms of road conditions, road maintenance, traffic conditions, traffic density, quality of traffic which implies presence of agricultural tractors, bullock carts, autos, motor bikes, oncoming traffic in same lane, vulnerable road users (VRU) walking in the same lanes as vehicles, VRU’s crossing roads without using zebra crossings etc. as additional traffic quality deterrents in comparison to developed countries. The braking capacity of such vivid road users may not be at par with global standards due to their maintenance, loading beyond specifications, driver behavior which includes the tendency to maintain a close gap between the preceding vehicle etc. which may lead to incidents specifically of rear collisions due to the front vehicle going through an emergency braking event. The following paper provides a comprehensive study of the special considerations or intricacies in implementation of Autonomous Emergency Braking (AEBS) feature into Indian traffic
Kartheek, NedunuriKhare, RashmitaSathyamurthy, SainathanManickam, PraveenkumarKuchipudi, Venkata Sai Pavan
This article proposes a new model for a cooperative and distributed decision-making mechanism for an ad hoc network of automated vehicles (AVs). The goal of the model is to ensure safety and reduce energy consumption. The use of centralized computation resource is not suitable for scalable cooperative applications, so the proposed solution takes advantage of the onboard computing resources of the vehicle in an intelligent transportation system (ITS). This leads to the introduction of a distributed decision-making mechanism for connected AVs. The proposed mechanism utilizes a novel implementation of the resource-aware and distributed–vector evaluated genetic algorithm (RAD-VEGA) in the vehicular ad hoc network of connected AVs as a solver to collaborative decision-making problems. In the first step, a collaborative decision-making problem is formulated for connected AVs as a multi-objective optimization problem (MOOP), with a focus on energy consumption and collision risk reduction as
Ghahremaninejad, RezaBilgen, Semih
Advanced driver assistance systems (ADAS) have become an integral part of today’s vehicle development. These systems are designed to provide secondary support to the driver, but the driver is primarily responsible for the driving task, e.g., lane-keeping assist (LKA). The driving setup and testing of these LKA systems is very time-consuming and usually applied in the car, based on experiences and subjective evaluation. This results in a cost-intensive calibration of the system. An objective-based calibration procedure can increase efficiency. For a targeted calibration of the system, it is necessary to define and identify key performance indicators (KPIs), which are able to describe the secondary support in sufficient detail. Usually, subjective feelings are used to derive KPIs. Vice versa, there are no results on how to design an LKA without any subjective assessment, before the calibration. With this in mind, this paper is focused on filling this unknown aspect by using virtual
Baumann, BenjaminIatropolous, JannesPanzer, AnnaHenze, Roman
While weaponizing automated vehicles (AVs) seems unlikely, cybersecurity breaches may disrupt automated driving systems’ navigation, operation, and safety—especially with the proliferation of vehicle-to-everything (V2X) technologies. The design, maintenance, and management of digital infrastructure, including cloud computing, V2X, and communications, can make the difference in whether AVs can operate and gain consumer and regulator confidence more broadly. Effective cybersecurity standards, physical and digital security practices, and well-thought-out design can provide a layered approach to avoiding and mitigating cyber breaches for advanced driver assistance systems and AVs alike. Addressing cybersecurity may be key to unlocking benefits in safety, reduced emissions, operations, and navigation that rely on external communication with the vehicle. Automated Vehicles and Infrastructure Enablers: Cybersecurity focuses on considerations regarding cybersecurity and AVs from the
Coyner, KelleyBittner, Jason
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 contrast to passenger cars, whose regulation allowed only a simple trailer combination, the autonomous technologies implementation of Electronic Stability Control (ESC) and Advanced Emergency Braking System (AEBS) for commercial vehicles demands more application and calibration efforts. At this case, the focus is on dynamic control of towing vehicles when applying the service brakes of trailer, in special when complex combination as bi-train and road-train, allowed in North and South America. However, the major risk is present occurrence when an ESC or AEBS equipped towing vehicles is connected to a double or triple trailer combination with a conventional braking system, it means: a system that is not equipped with Anti-lock Braking System (ABS). For instance, if during autonomous control, trailers wheels lock, a jackknifing phenomenon can easily occur. Therefore, in case longer and heavier vehicles (LHV) or megatrucks as called in Europe, the strategy for safety assistance systems
Guarenghi, Vinicius MendesPizzi, Rafael FortunaDepetris, AlessandroPinto, Gustavo Laranjeira NunesCollobialli, Germano
New tests for a Truck Safe rating scheme aim to emulate real-world collisions and encourage OEMs to fit collision avoidance technologies and improve driver vision. Euro NCAP has revealed the elements it is considering as part of an upcoming Truck Safe rating, and how it intends to test and benchmark truck performance. The announcement was made to an audience of international road safety experts at the NCAP24 World Congress in Munich, Germany, in April. The action is intended to mitigate heavy trucks' impact on road safety. The organization cited data showing that trucks are involved in almost 15% of all EU road fatalities but represent only 3% of vehicles on Europe's roads. Euro NCAP says the future rating scheme is designed to go further and faster than current EU truck safety regulations. The organization's goal is to drive innovation and hasten the adoption of advanced driver-assistance systems (ADAS) such as automatic emergency braking (AEB) and lane support systems (LSS), while
Gehm, Ryan
You've got regulations, cost and personal preferences all getting in the way of the next generation of automated vehicles. Oh, and those pesky legal issues about who's at fault should something happen. Under all these big issues lie the many small sensors that today's AVs and ADAS packages require. This big/small world is one topic we're investigating in this issue. I won't pretend I know exactly which combination of cameras and radar and lidar sensors works best for a given AV, or whether thermal cameras and new point cloud technologies should be part of the mix. But the world is clearly ready to spend a lot of money figuring these problems out
Blanco, Sebastian
At the InCabin USA vehicle technology expo in Detroit, Ford customer research lead Susan Shaw said that the sea of letters around ADAS features and control and indicator icons that vary between vehicles are often confusing to drivers. Shaw pointed out that the following all represent features related to driving lanes: LDW, LKA, LKS, LFA, LCA. These initialisms (groups of letters that form words) are not the only ways the industry refers to these technologies, as some OEMs have their own names for similar things. It all contributes to what can be dangerous assumptions on the part of a driver. “It's shocking how many people think their vehicle will apply the brakes in an emergency, when the car has no such system,” she said. As an overview to the subject of control and indicator iconography, Shaw began with an introduction to user experience research by talking about a classic example: Norman is the author of “The Design of Everyday Things.” A so-called Norman door is any door that is
Clonts, Chris
To round out this issue's cover story, we spoke with Clement Nouvel, Valeo's chief technical officer for lidar, about Valeo's background in ADAS and what's coming next. Nouvel leads over 300 lidar engineers and the company's third-generation Scala 3 lidar is used on production vehicles from European and Asian automakers. The Scala 3 sensor system scans the area around a vehicle 25 times per second, can detect objects more than 200 meters (656 ft) away with a wide field of vision and operates at speeds of up to 130 km/h (81 mph) on the highway. In 2023, Valeo secured two contracts for Scala 3, one with an Asian manufacturer and the other with a “leading American robotaxi company,” Valeo said in its most-recent annual report. Valeo has now received over 1 billion euros (just under $1.1 billion) in Scala 3 orders. Also in 2023, Valeo and Qualcomm agreed to jointly supply connected displays, clusters, driving assistance technologies and, importantly, sensor technology for to two- and three
Dinkel, John
The traditional approach to applying safety limits in electromechanical systems across various industries, including automated vehicles, robotics, and aerospace, involves hard-coding control and safety limits into production firmware, which remains fixed throughout the product life cycle. However, with the evolving needs of automated systems such as automated vehicles and robots, this approach falls short in addressing all use cases and scenarios to ensure safe operation. Particularly for data-driven machine learning applications that continuously evolve, there is a need for a more flexible and adaptable safety limits application strategy based on different operational design domains (ODDs) and scenarios. The ITSC conference paper [1] introduced the dynamic control limits application (DCLA) strategy, supporting the flexible application of diverse limits profiles based on dynamic scenario parameters across different layers of the Autonomy software stack. This article extends the DCLA
Garikapati, DivyaLiu, YitingHuo, Zhaoyuan
The rise of AI models across diverse domains includes promising advancements, but also poses critical challenges. In particular, establishing trust in AI-based systems for mission-critical applications is challenging for most domains. For the automotive domain, embedded systems are operating in real-time and undertaking mission-critical tasks. Ensuring dependability attributes, especially safety, of these systems remains a predominant challenge. This article focuses on the application of AI-based systems in safety-critical contexts within automotive domains. Drawing from current standardization methodologies and established patterns for safe application, this work offers a reflective analysis, emphasizing overlaps and potential avenues to put AI-based systems into practice within the automotive landscape. The core focus lies in incorporating pattern concepts, fostering the safe integration of AI in automotive systems, with requirements described in standardization and topics discussed
Blazevic, RomanaVeledar, OmarStolz, MichaelMacher, Georg
This article aims to address the challenge of recognizing driving styles, a task that has become increasingly complex due to the high dimensionality of driving data. To tackle this problem, a novel method for driver style clustering, which leverages the principal component analysis (PCA) for dimensionality reduction and an improved GA-K-means algorithm for clustering, is proposed. In order to distill low-dimensional features from the original dataset, PCA algorithm is employed for feature extraction and dimensionality reduction. Subsequently, an enhanced GA-K-means algorithm is utilized to cluster the extracted driving features. The incorporation of the genetic algorithm circumvents the issue of the model falling into local optima, thereby facilitating effective driver style recognition. The clustering results are evaluated using the silhouette coefficient, Calinski–Harabasz (CH) index, and GAP value, demonstrating that this method yields more stable classification results compared to
Chen, YinghaoWu, GuangqiangWu, JianWang, Hao
An essential component in the approval of advanced driver assistance systems (ADAS) and automated driving systems (ADS) is the quantification of residual risk, which demonstrates that hazardous behavior (HB) occurs less frequently than specified by a corresponding acceptance criterion. In the case of HB with high potential impact severity, only very low accepted frequencies of occurrence are tolerated. To avoid uncertainties due to abstractions and simplifications in simulations, the proof of the residual risk in systems such as advanced emergency braking systems (AEBS) is often partially or entirely implemented as system level field test. However, the low rates and high confidence required, common for residual risk demonstrations, result in a significant disadvantage of these field tests: the long driving distance required. In this publication, the prediction divergence principle (PDP) is presented as an approach that has the potential to reduce the testing effort in the future
Betschinske, DanielSchrimpf, MalteLippert, MoritzPeters, Steven
AEB systems are critical in preventing collisions, yet their effectiveness hinges on accurately estimating the distance between the vehicle and other road users, as well as understanding road conditions. Errors in distance estimation can result in premature or delayed braking and varying road conditions alter road-tire friction coefficients, affecting braking distances. The integration of advanced sensors like LiDARs has significantly enhanced distance estimation. Cameras and deep neural networks are also employed to estimate the road conditions. However, AEB systems face notable challenges in urban environments, influenced by complex scenarios and adverse weather conditions such as rain and fog. Therefore, investigating the error tolerance of these estimations is essential for the performance of AEB systems. To this end, we develop a digital twin of our test vehicle in the IPG CarMaker simulation environment, which includes realistic driving dynamics and sensor models. Our simulated
Wang, YifanIatropoulos, JannesThal, SilviaHenze, Roman
This paper presents a novel and robust approach to estimate both the side-slip gradient and the lateral velocity by integrating radar-doppler measurements into a vehicle motion observer. In ego-motion estimation the side-slip gradient is used to model the lateral velocity of the vehicle, since it cannot be measured directly. The algorithm only requires low-dynamic, steady-state excitation and is based on an adaptive Kalman-Filter assuring high accuracy and stability. The number of radar sensors can be chosen arbitrarily. The algorithm has shown to estimate the side-slip gradient within 10% of its true value. It also rejects radar outliers and does not depend on permanent availability of the radar sensors. The approach requires little tuning which makes it applicable to mass-produced vehicles
Diener, LuisKalkkuhl, JensSchirle, Thomas
As part of the safety validation of advanced driver assistance systems (ADAS) and automated driving (AD) functions, it is necessary to demonstrate that the frequency at which the system exhibits hazardous behavior (HB) in the field is below an acceptable threshold. This is typically tested by observation of the system behavior in a field operational test (FOT). For situations in which the system under test (SUT) actively intervenes in the dynamic driving behavior of the vehicle, it is assessed whether the SUT exhibits HB. Since the accepted threshold values are generally small, the amount of data required for this strategy is usually very large. This publication proposes an approach to reduce the amount of data required for the evaluation of emergency intervention systems with a state machine based intervention logic by including the time periods between intervention events in the validation process. For this purpose, a proximity measure that indicates how close the system is to an
Schrimpf, MalteBetschinske, DanielPeters, Steven
Deep learning algorithms are being widely used in autonomous driving (AD) and advanced driver assistance systems (ADAS) due to their impressive capabilities in visual perception of the environment of a car. However, the reliability of these algorithms is known to be challenging due to their data-driven and black-box nature. This holds especially true when it comes to accurate and reliable perception of objects in edge case scenarios. So far, the focus has been on normal driving situations and there is little research on evaluating these systems in a safety-critical context like pre-crash scenarios. This article describes a project that addresses this problem and provides a publicly available dataset along with key performance indicators (KPIs) for evaluating visual perception systems under pre-crash conditions
Bakker, Jörg
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