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Commercial Vehicles: Vol. 1EPRCOMPV1420235/3/2024
ABSTRACT
Lehmann, Johannes, Moorehead, Stewart, Muelaner, Jody E.
USUALLY UNOBSERVED REFINEMENTS OF AUTOMOBILE CONSTRUCTION0800031/1/2024
ELLSWORTH, JOHN MAGEE, FAY, THOMAS J.
Key Technology Challenges of Electric Ducted Fan Propulsion Systems for eVTOLEPR202302711/22/2023
Electrical vertical takeoff and landing (eVTOL) vehicles for urban air mobility (UAM) are garnering increased attention from both the automotive and aerospace industries, with use cases ranging from individual transportation, public service, cargo delivery, and more. Distributed electric propulsion systems are their main technical feature; they determine vehicle size and propulsion efficiency and provide distributed thrust to achieve attitude control. Considering the intended role of eVTOL vehicles, ducted-fan systems are ideal choice for the propulsor, as the duct provides a physical barrier between the rotating blades and the human, especially during the take-off and landing phases. Key Technology Challenges of Electric Ducted Fan Propulsion Systems for eVTOL introduces the main bottlenecks and key enablers of ducted-fan propulsion systems for eVTOL applications. Based on the introduction and discussion of these important issues, this report will help eVTOL engineers understand the key technical issues and inspire them to develop the ideal solutions that will enable eVTOL vehicle deployment for UAM operations. Click here to access the full SAE EDGETM Research Report portfolio.
TESTING PACKAGE OVERWRITE: Aerodynamic Investigation by Computational Fluid Dynamics to Exterior Design Modifications in a Simplified Bus Model2023-01-50031/4/2023
Abstract Exterior design modifications have crucial importance on vehicle aerodynamics. Therefore, it makes one of the key parameters to achieve to reduce the fuel consumption in diesel-, CNG-, and hybrid-powered engines and increase the range of electric vehicles (EVs). The slightest change in the vehicle exterior design can directly affect the vehicle aerodynamics. Thus, four different parameters (front windshield angle, front diffuser angle, rear diffuser angle, and fillet [bending] on the rear and front top) are reviewed on a conceptual 12 m long bus which is to be designed at Anadolu Isuzu. Computational fluid dynamics (CFD) simulations become a source for comparative evaluations in these studies. Simulations are carried out for all different models with a realizable k-epsilon turbulence model and enhanced wall treatment wall function. In conclusion, a positive aerodynamic effect is observed with parameters that are the windshield, front diffuser angle, and fillet on the rear and front top ends. On the other hand, a negative aerodynamic effect is observed when rear diffuser angle is applied. All simulations are compared based on drag coefficient values. The front windshield angle is found the most influential parameter on a conceptual vehicle design that can be provided a drag coefficient reduction of up to 51%.
Özcan, Onur, Yıldız, Alp Eren
Study and Application of Gear Micro Modification of Electric Drive System15-16-01-00019/15/2022
Abstract The gear whine in the electric drive system of an electric vehicle is important and remains a challenge in developing novel electric vehicles. A gearbox dynamic model is established, and the effects of modification parameters on the sound pressure level, transmission error, and contact stress of the gear pair are introduced to reduce the gear whine. A multi-objective optimization study of four modification variables under multiple torque conditions is carried out by using transmission error and maximum contact stress as the objective functions. The eclectic programming method is imported to solve the convergence problem of multi-objective optimization. The influence of modification variables on objective functions is studied by establishing an approximate model of the optimal Latin hypercube design. Results show that the application of the multi-objective optimization method combined with the eclectic planning method for the micro modification of the gear can reduce the transmission error of multi-torque conditions, effectively reducing the gear whine noise in multiple torque conditions and improving the contact of the tooth surface.
Chen, Chen, Zhu, Linpei, Liu, Jing, Wei, Dan, Yu, Hao
V4-002 FK testSAE-PP-009554/26/2022
Heavy vehicles are essential for the modern economy, delivering critical food, supplies, and freight throughout the world. Connected heavy vehicles are also driven by embedded computers that utilize internal communication using common standards. However, some implementations of the standards leave an opening for a malicious actor to abuse the system. One such abuse case is a cyber-attack known as the “Address Claim Attack.” Proposed in 2018, this attack uses a single network message to disable all communication to and from a target electronic control unit, which may have a detrimental effect on operating the vehicle. This article demonstrates the viability of the attack and then describes the implementation of a solution to prevent this attack in real time without requiring any intervention from the manufacturer of the target devices. The defense technique uses a bit-banged Controller Area Network (CAN) filter to detect the attack. Once an attack is discovered, the defender induces a CAN protocol error to remove the malicious message from the network. We discuss our results in terms of their applicability for Address Claim Attacks and possible implications for preventing a variety of network-based attacks in real time.
Mutagaana, Festo
Plug-in Electrical Vehicle Charge Rate Reporting and Test ProceduresJ2953/4_202106 (Historical)6/10/2021
This document facilitates clear and consistent comparisons of realistic charging capabilities of passenger vehicles via commercially available DC EVSE. Common test procedures and metrics are established for both vehicles and EVSEs operating without limitations in nominal conditions. This document does not attempt to address performance variations of EV-EVSE interactions outside of nominal conditions such as extreme temperatures, variable SOCs, and so on.
Hybrid - EV Committee
Use Cases for Diagnostic Communication for Plug-in Electric VehiclesJ2836/4_202106 (Current)6/10/2021
This SAE Surface Vehicle Technical Information Report, SAE J2836/4, establishes diagnostic use cases between plug-in electric vehicles (PEV) and the electric vehicle supply equipment (EVSE). As PEVs are deployed and include both plug-in hybrid electric (PHEV) and battery electric (BEV) vehicle variations, failures of the charging session between the EVSE and PEV may include diagnostics particular to the vehicle variations. This document describes the general information required for diagnostics and SAE J2847/4 will include the detail messages to provide accurate information to the customer and/or service personnel to identify the source of the issue and assist in resolution. Existing vehicle diagnostics can also be added and included during this charging session regarding issues that have occurred or are imminent to the EVSE or PEV, to assist in resolution of these items.
Hybrid - EV Committee
Hybrid Electric Vehicle (HEV) and Electric Vehicle (EV) TerminologyJ1715_202105 (Historical)5/28/2021
This SAE Information Report contains definitions for HEV, PHEV, and EV terminology. It is intended that this document be a resource for those writing other HEV, PHEV, and EV documents, specifications, standards, or recommended practices.
Hybrid - EV Committee
Use Cases for Wireless Charging Communication for Plug-in Electric VehiclesJ2836/6_202104 (Current)4/9/2021
This SAE Information Report SAE J2836/6 establishes use cases for communication between plug-in electric vehicles and the EVSE for wireless energy transfer as specified in SAE J2954. It addresses the requirements for communications between the on-board charging system and the wireless EV supply equipment (WEVSE) in support of detection of the WEVSE, the charging process, and monitoring of the charging process. Since the communication to the charging infrastructure and the power grid for smart charging will also be communicated by the WEVSE to the EV over the wireless interface, these requirements are also covered. However, the processes and procedures are expected to be identical to those specified for V2G communications specified in SAE J2836/1. Where relevant, the specification notes interactions that may be required between the vehicle and vehicle operator, but does not formally specify them. Similarly, communications between the on-board charging sub-system and the on-board vehicle electronics is not formally specified in this document. This document will be published as a set of steps. The intent of step 1 was to record as much information on “what we think works” and publish. The intent of step 2 is to provide refinement and missing pieces to step 1, with a an eye to early testing. This version is step 2, with the aim of providing a communication protocol for home chargers.
Hybrid - EV Committee
Synthesis and Validation of Multidimensional Driving Cycles2021-01-01254/6/2021
Driving cycles are usually defined by vehicle speed as a function of time and they are typically used to estimate fuel consumption and pollutant emissions. Currently, certification driving cycles are mainly used for this purpose. Since they are artificially generated, the resulting estimates and analyzes can generally be biased. In order to address these shortcomings, recent research efforts have been directed towards development of statistically representative synthetic driving cycles derived from recorded real-world data. To this end, this paper focuses on synthesis of multidimensional driving cycles using the Markov chain-based method and particularly on their validation. The synthesis is based on Markov chain of fourth order, where the road slope is accounted, as well. The corresponding transition probability matrix is implemented in the form of a sparse matrix parameterized with a rich set of recorded city bus driving cycles. A wide collection of statistical features, including the frequency domain indicators, unique cross-correlation velocity-acceleration-slope indicators, and indicators related to bus stops at stations are considered for the purpose of driving cycle validation. To prove the synthesis method validity, a comparative statistical analysis of distributions of the nominated statistical features of synthetic and recorded driving cycles is carried out. Finally, a multi-criteria method of driving cycle validation based on lumped metrics is outlined and examined.
Topić, Jakov, Škugor, Branimir, Deur, Joško
Validating an Approach to Assess Sensor Perception Reliabilities Without Ground Truth2021-01-00804/6/2021
A reliable environment perception is a requirement for safe automated driving. For evaluating and demonstrating the reliability of the vehicle’s environment perception, field tests offer testing conditions that come closest to the vehicle’s driving environment. However, establishing a reference ground truth in field tests is time-consuming. This motivates the development of a procedure for learning the vehicle’s perception reliability from fleet data without the need for a ground truth, which would allow learning the perception reliability from fleet data. In Berk et al. (2019), a method based on Bayesian inference to determine the perception reliability of individual sensors without the need for a ground truth was proposed. The model utilizes the redundancy of sensors to learn the sensor’s perception reliability. The method was tested with simulated data. In this contribution, we further explore and validate the method by utilizing real data, including ground truth data based on high-resolution LIDAR and human labeling. An area with overlapping field of view from five sensors is selected for the analysis. A basic association method is used to compare the object data obtained from the different sensors. Finally, we compare the sensor perception reliabilities learned from the Bayesian inference model with the sensor perception reliabilities determined from the labeled ground truth. In this paper, it is shown that the model introduced in Berk et al. (2019) can approximate the reference data based on the provided ground truth. The estimated parameters of the model do not perfectly correspond to the sensor reliabilities but are of the same order of magnitude as when derived from the ground truth.
Kryda, Marco, Berk, Mario, Buschardt, Boris, Straub, Daniel
Impact of Fog Particles on 1.55 μm Automotive LiDAR Sensor Performance: An Experimental Study in an Enclosed Chamber2021-01-00814/6/2021
To achieve full automation in self-driving vehicles, environmental perception sensing accuracy is critically important. However, ambient particles in adverse weather like foggy, rainy, or snowy conditions can significantly scatter the incident laser beam, and therefore contaminate the intensity and accuracy of light detection and ranging (LiDAR) sensors. Especially compared to the rapidity of technology development in self-driving vehicles, there is a significant lack of documented research on LiDAR systems with wavelength longer than 1 μm for application in Advanced Driver-Assistance Systems. In this work, experimental studies were performed with a state-of-the-art 1.55 μm wavelength automotive-grade LiDAR system in a controlled laboratory fog chamber. The goal of the research is to correlate laser attenuation and the optical properties of fog particles. In this work, a thorough multistep procedure for LiDAR data analysis is presented including spatial averaging of the object measurement and characterizing the temperature effect on a LiDAR intensity parameter. Fog particle density is measured by a commercial visibility sensor instrument. Assuming a constant extinction coefficient and backscatter coefficient, a simple analytical model is derived that correlates LiDAR reflectance and extinction coefficient measured by visibility sensor. Results show that the correlation coefficient between LiDAR and visibility sensor data is 0.98 and the R-squared value of linear fitting is 0.96. By comparing the LiDAR original signal and the model, the Root-Mean-Squared Deviation is 0.007, meaning the model performs very well for predicting LiDAR reflectance in the controlled environment. Furthermore, although the returned signal strength is attenuated, the LiDAR can measure the target with a visibility range lower than six meters.
Zhan, Lu, Northrop, William F.
Object Detection and Tracking for Autonomous Vehicles in Adverse Weather Conditions2021-01-00794/6/2021
Object detection and tracking is a central aspect of perception for autonomous vehicles. While there has been significant development in this field in recent years, many perception algorithms still struggle to provide reliable information in challenging weather conditions which include night-time, direct sunlight, glare, fog, etc. To achieve full autonomy, there is a need for a robust perception system capable of handling such challenging conditions. In this paper, we attempt to bridge this gap by proposing an algorithm that combines the strength of automotive radars and infra-red thermal cameras. We show that these sensors complement each other well and provide reliable data in poor visibility conditions. We demonstrate the advantages of a thermal camera over a visible-range camera in these situations and employ YOLOv3 for object detection. The proposed system utilizes a modified Track-Oriented Multiple Hypothesis Tracking (MHT) algorithm which uses data from these sensors to keep track of the surrounding vehicles. The modifications in the well-known MHT algorithm were introduced in order to curb the exponential growth of possible hypotheses and consequently reduce the computational time without loss of any critical information. To validate the system, we provide a real-time implementation on an urban dataset collected at the Texas A&M University.
Bhadoriya, Abhay Singh, Vegamoor, Vamsi Krishna, Rathinam, Sivakumar
A Semantic Slam System Based on Visual-Inertial Information and around View Images for Underground Parking Lot2021-01-00784/6/2021
As one of the most challenging driving tasks, parking is a common but particularly troublesome problem in large cities. Recently, an excellent solution-automated valet parking (AVP) has become a hot research topic, which allows the driver to leave the vehicle in a drop-off area, while the vehicle driving into the parking slot by itself. For AVP, the precise localization is an indispensable module. However, the global positioning system (GPS) cannot be used in the underground parking lot and the localization method based on lidar is too expensive. In response to solve this problem, we propose a simultaneous localization and mapping system with the semantic information of parking slots (PS-SLAM), which is based on visual-inertial and around view images. First, the calibration of multi-sensors is conducted to obtain their intrinsic and extrinsic parameters. In this way, the around view image and transformation matrices between sensors can be acquired. Then, the ORB-SLAM3 based on visual-inertial information is used to acquire the pose of the vehicle and sparse point cloud map. Next, the parking slot in the around view image is detected by the deep convolutional neural network (DCNN) model called VPS-Net. Finally, a parking-slot association method is devised to associate the detected parking slots with the point cloud map to generate a semantic map. The field experiments are conducted using a wire control chassis with 4 fisheye cameras, an inertial measurement unit (IMU), and a monocular camera. The results show that the proposed visual semantic SLAM system not only can achieve centimeter-level localization in the indoor parking lot but also generate a semantic map with parking slots.
LI, Wei, Li, Chaohui, Xiao, Dongjie, Zhou, Dong, Wang, Tao, Cao, Libo
Object Segmentation and Augmented Visualization Based on Panoramic Image Segmentation2021-01-00894/6/2021
Panoramic images can provide critical information for Advanced Driving Assistance Systems (ADAS), such as parking spaces and surrounding vehicles. However, the vehicle in the bird's-eye view image is severely distorted and incomplete, and the visual information becomes very blurred in some illumination insufficient environments. If the driver cannot see the surrounding environment information, the risk of collision will increase, especially during parking. To better percept the local environment with the help of panoramic images, we use panoramic image segmentation results to construct a virtual surround view monitoring system to provide drivers with clearer perception information. Firstly, a lightweight segmentation network is redesigned based on SegNet, which will improve the accuracy of the segmentation without increasing the model’s inference time. Secondly, we build an augment visualization around view monitor (AV-AVM) system with regards to the segmentation results. All necessary segmentation results will be presented as augmented visualization in AV-AVM systems, such as parking slots and road markings. Compared with the traditional panoramic system, the virtual panoramic surround view system we designed can provide the driver with more intuitive environmental perception information and can be further used to construct an automatic parking map.
Liao, Jiacai, Cao, Libo, Gong, Yipeng, Zhao, Junjie, Chen, Zhen, Chen, Kai
Dynamically Adjustable LiDAR with SPAD Array and Scanner2021-01-00914/6/2021
An important function of an Automated Driving (AD) system is to detect objects including vehicles and pedestrians on the road. Typical devices for detecting those objects include cameras, millimeter-wave RADAR, and light detection and ranging (LiDAR). LiDAR uses the flight time of a short-wavelength electromagnetic wave. Because of that LiDAR is expected to find even small objects such as tire fragments on a road in high resolution. The detection performance required for LiDAR depends on the operational design domain (ODD). For example, while a vehicle is travelling at high speeds, LiDAR needs to detect apparently small objects at long distances, and while it is travelling at low speeds, LiDAR has to detect objects over a wide angular range. Conventional LiDAR is developed to satisfy all requirements, providing performance including detection distance, resolution, and angle of view tends to expose issues such as cost and size when it is mounted onboard. To solve these problems, we have built LiDAR with a new structure consisting of an originally developed light receiving unit and scanning unit, which are the main components. The light receiving units uses an array of high-sensitivity single-photon avalanche diodes (SPADs). Its vertical resolution can be selected by changing the number of SPADs per pixel. The scanning unit has introduced a reciprocal motion system, which enables dynamically choosing the range and speed of scanning, with the range of scanning 100 ° or wider. With these mechanisms, it is possible to select a high-resolution and narrow-angle mode when detecting small objects at long distances, and low-resolution and wide-angle mode for detecting many objects at short distances. Therefore, the LiDAR can adjust its performance dynamically according to driving scenes. We have confirmed that our LiDAR is effective for detecting objects under various conditions.
Nakajima, Masato, Hata, Takehiro, Ueno, Akifumi, Ozaki, Noriyuki, Mizuno, Fumiaki, Kashiwada, Shinji, Yanai, Kenichi
Interactive Lane Change with Adaptive Vehicle Speed2021-01-00944/6/2021
Advanced Driver Assistance Systems (ADAS) has gained an enormous interest in the past decade with growing complexity in systems software and hardware. One of the most challenging ADAS features to develop is lane change as it requires full awareness of the objects surrounding the Ego vehicle as well as performing safe and convenient maneuvers. This paper discusses a camera-based lane change approach that is designed to improve the driver’s safety and comfort with the help of LiDAR object detection. The forward-facing camera is capable of detecting the Ego and adjacent lane lines as well as the moving objects in the camera’s field of view. A Graphical User Interface (GUI) was also developed for the driver to interact with the lane change feature by visualizing the sensor data and optionally request the vehicle to change lanes when the system suggests that it is safe to do so. Path planning and following algorithms were developed to plan the path between the center of the Ego lane and the center of the right/left adjacent lanes. The developed algorithms were implemented on FEV’s Smart Vehicle Demonstrator and tested on highway roads. The test results show that the vehicle was able to successfully achieve the lane change by following the planned path and adjusting its speed based on the surrounding objects and curvature of the road.
Alzu'bi, Hamzeh, Taylor, Elizabeth, Matta, Sherif, Tasky, Tom
Adopting Aviation Safety Knowledge into the Discussions of Safe Implementation of Connected and Autonomous Road Vehicles2021-01-00744/6/2021
The development of connected and autonomous vehicles (CAVs) is progressing fast. Yet, safety and standardization-related discussions are limited due to the recent nature of the sector. Despite the effort that is initiated to kick-start the study, awareness among practitioners is still low. Hence, further effort is required to stimulate this discussion. Among the available works on CAV safety, some of them take inspiration from the aviation sector that has strict safety regulations. The underlying reason is the experience that has been gained over the decades. However, the literature still lacks a thorough association between automation in aviation and the CAV from the safety perspective. As such, this paper motivates the adoption of safe-automation knowledge from aviation to facilitate safer CAV systems. The authors briefly elaborate on the widely discussed aviation themes, including autopilot and auto-throttle malfunctions, flight management system, human factors, and suggests how this knowledge can improve the safety of road CAVs use-case. Besides, the differences between the safety consideration in the two fields are also denoted. In summary, the main aim of this paper is to highlight the potential benefits of adopting aviation automation safety knowledge into safe CAV development. With the advances in the CAV, the authors are convinced that this subject could serve software developers and engineers in developing safe and standardized CAV technology.
Abdul Hamid, Umar Zakir, Mehndiratta, Mohit, Adali, Erkan
An Online Coverage Path Planning Method for Sweeper Trucks in Dynamic Environments2021-01-00954/6/2021
In this paper, a novel online coverage path planning (CPP) method for autonomous sweeper trucks in closed areas is proposed. This method can efficiently generate executable paths for sweeper trucks that cover all feasible uncleaned areas without getting tracked in dead-end, i.e., no backward behaviors required and avoid dynamic obstacles. To reach that end, a modified biological inspired neuron network method considering vehicle constrains is developed, where the dynamic of each neuron is determined by the shunting function. The path will be iteratively generated based on local neuron dynamics. In order to avoid dead-end, a detour algorithm combing with back iteration is introduced to search the nearest uncleaned area that can be reached within vehicle constrains. The proposed method is empirically approved to be computationally efficient and adaptive to maps with arbitrary shapes. The feasibility of generated paths is validated in simulations, where the pure pursuit method is applied to achieve path following. The truck model in the simulation achieves 100% coverage with reasonable cross-track errors.
Zhang, Weiyang, Sun, Yong, Yu, Wenbo, XU, MENG
Time-Optimal Trajectory Planning for Multi-Vehicle Coordinated Left-Turn Condition at an Unsignalized Intersection2021-01-00964/6/2021
The left-turn condition is the most complicated one at the unsignalized intersection, which is one of the key factors that affect traffic safety and efficiency. To solve this problem, this study proposes a distributed trajectory optimization framework based on the Gauss pseudospectral method (GPM). First, a circular obstacle based on the road size is constructed to replace the actual path constraint. The movement of obstacle is used for iterative calculations, and the trajectory of the left-turn vehicle is approached to the theoretical path. Then, for the multi-vehicle coordinated condition, the collision free constraints between vehicles is added to the optimization framework several times. In addition, the previous calculation result is used as the initial guess solution for the next calculation until all constraints are set. The simulation results show that the circular obstacle is effective and convenient, and the trajectory of a single vehicle is close to the actual driving state due to the good restraint effect. The iterative method of gradually increasing constraints can effectively avoid calculation failures caused by complex conditions, and the real-time performance of the framework is improved. Finally, the order of addition of constraints is discussed to explain the universality of the proposed framework.
Chen, Chen, Qian, Lijun, Wu, Bing
Development of Fault Detection and Emergency Control for Application to Autonomous Vehicle2021-01-00754/6/2021
This paper describes a failsafe system of automated driving vehicles. The failsafe system consists of the following two parts: sliding mode observer-based environment sensor, chassis sensor fault detection, and emergency deceleration control. Two sliding mode observers are designed to reconstruct the fault of acceleration and environment sensor(Lidar) in a longitudinal direction. In the environment sensor's fault detection part, the longitudinal vehicle model receives clearance and relative velocity values. Therefore, failure diagnosis is possible regardless of environmental sensors, such as radar, lidar, and camera. This paper's sensor data is the failure of Delphi's Electronically Scanning Radar (ESR) and Ibeo's LUX Lidar installed in an autonomous vehicle. The emergency deceleration control algorithm employs the sliding mode control with adaptive convergence time. In the event of a failure, it is significant to control the vehicle within a short period safely. The Adaptive convergence time concept proves a mathematical convergence of the vehicle control time after a failure occurs. As soon as the error occurred, the error was proved to always converge to zero within the final time. Thus, the proposed method introduces the concept of convergence time, and mathematically demonstrates that the state reached the reference target within the specified time when a failure occurred. In the emergency control part, two processing unit hardware structures are adopted to comply with SAE International standard J3016 and NHTSA autonomous vehicle safety report standards. The proposed fail-safe detection algorithm is evaluated through vehicle test data, and the fail-safe control algorithm evaluates through computer simulation and vehicle tests.
Jong Min, Lee, Oh, Kwang Seok, Song, Taejun
Research on Photobiological Safety of Automotive Active Infrared Detection System2021-01-00724/6/2021
The automotive active infrared detection system is usually applied to the night driver assistance system or the diver attention monitoring system. However, the infrared light emitted by the active infrared detection system can cause damage to retina, cornea and eye crystals. This paper has studied the photobiological safety of the infrared light source used in the automotive active infrared detection system. Although it has been already have the general requirements of photobiological safety in international standards, there is not any requirements for automotive active infrared detection system. The range of the active infrared detection system depends on the radiation intensity of the infrared light source, but too much radiation intensity will cause harm to retina, cornea and eye lens when the infrared light source is too close to eyes. Based on the international standards, this paper has analyzed the retinal thermal hazard and the harm to skin and eyes caused by infrared radiation, and it has calculated the theoretical radiation intensity threshold under different risk groups and safety distances. The threshold of radiation intensity of the automotive active infrared detection system have been proposed, which could provide references for the formulation of Chinese national standard. What’s more, the experimental verification has been conducted by using the driver attention monitoring system, and the conclusion indicates that the threshold proposed in this paper is reasonable.
Hu, Yue, Zhu, Tong, Li, Qian, Yang, Xiong
Multi-Sensor Fusion in Slow Lanes for Lane Keep Assist System2021-01-00844/6/2021
Implementing Advanced Driver Assistance Systems (ADAS) features that are available in all road scenarios and weather conditions is a big challenge for automotive companies and considered key enablers to achieve autonomous Level 4 (L4) vehicles. One important feature is the Lane Keep Assist System (LKAS). Most LKAS systems are based on lane line detection cameras and lane coefficient estimations by the camera is the key point for LKAS where the camera recognizes the lane lines using edge detection. But when the lane markers are not available due to high traffic and slow driving on the roads, another source of data for the lane lines needs to be available for the LKAS. In this paper a multi-sensor fusion approach based on camera, Lidar, and GPS is used to allow the vehicle to maintain its lateral location within the lane. The lateral distances of the lane lines are measured by LiDAR detection of the markers based on the intensity and fused with lane line information from the HD Map after transforming the sensors to the same reference. This approach was tested on FEV’s Smart Vehicle Demonstrator and the test results show the vehicle was able to maintain the lane.
Alrousan, Qusay, Matta, Sherif, Tasky, Tom
Correlation between Sensor Performance, Autonomy Performance and Fuel-Efficiency in Semi-Truck Platoons2021-01-00644/6/2021
Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each other in close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-truck autonomy is easily integrated on existing platforms, reduces delivery times, and reduces greenhouse gas emissions via fuel economy benefits. Level 1 SAE fuel studies were performed on class-8 trucks operating with the Auburn Cooperative Adaptive Cruise Control (CACC) system, and fuel savings up to 10-12% were seen. Enabling platooning autonomy required the use of radar, global positioning systems (GPS), and wireless vehicle-to-vehicle (V2V) communication. Poor measurements and state estimates can lead to incorrect or missing positioning data, which can lead to unnecessary dynamics and finally wasted fuel. This is especially an issue if deceleration is applied in response to a bad measurement. In this study, a faulty radar was shown to cause a greater than 5% increase in fuel consumption. The mechanism of this fuel consumption increase is investigated and applied to other types of sensor failures to indicate their potential effects on fuel economy. This analysis indicates that poor GPS signals over short time can be largely filtered out, with no real gain or loss of fuel economy. V2V communications were intentionally limited by causing interference, which resulted in dropped communication packets over a small physical area, but not an appreciable impact on fuel economy.
Adam, Cristian, Lakshmanan, Sridhar, Richardson, Paul, Stegner, Evan, Ward, Jacob, Hoffman, Mark, Bevly, David M.
Leveraging Risk Tolerances and Simple Kinematics to Quantify Fault Tolerant Time Intervals for Commercial Trucks2021-01-00664/6/2021
The ISO 26262 series of standards for vehicle functional safety codify requirements to avoid unreasonable risk from the failure of electrical or electronic (E/E) systems. E/E failures may cause malfunctioning behavior that manifest as vehicle-level hazardous events. The ISO 26262 second edition includes commercial trucking, which employs significant variation from the passenger car development cycle. The highly distributed nature of E/E system development and integration in commercial trucks complicates forging unified safety concepts. For instance, the Fault Tolerant Time Interval (FTTI) quantifies the minimum time span from the occurrence of a fault to the possible occurrence of a hazardous event. Often, the subjectivity involved in defining unreasonable risk and hazardous event onset frustrates consensus among stakeholders. In order to provide some uniformity in the adoption of ISO 26262 across the commercial truck industry, this paper introduces the Risk Threshold (RT) Method to clarify the boundary between acceptable and unreasonable risk. RT is defined as the acceptable travel distance caused by a malfunctioning behavior. The RT Method includes: Selecting a malfunctioning behavior and a corresponding hazardous event from a Hazard Analysis and Risk Assessment (HARA) Designing a vehicle-level experiment that simulates the hazard Defining a RT that quantifies hazardous event onset Applying kinematic equations using the RT and experimental data to calculate FTTI This paper applies the RT Method to four key hazards: unintended acceleration, unintended motion, unintended direction, and increased stopping distance. For ease of illustration, all motion described in this paper aligns with a truck’s longitudinal axis. The RT Method correlates FTTI to hazardous event onset using objective and repeatable measurements. For commercial trucks, consistently predictable velocity during the FTTI facilitates this correlation. The simplicity of this approach enables stakeholder comparison of differing risk tolerances in terms of RT. Driving consensus on RT then yields a corresponding FTTI.
Jones, Darren K, Awowede, Collins, Ellinger, Michael, Kretz, Angelina, Krishnamoorthy, Jayalekshmi
Leveraging Systems Theoretic Process Analysis (STPA) for Efficient ISO 26262 Compliance2021-01-00674/6/2021
There has been a significant increase - both in the content of electronics and software in vehicles as well as in recalls attributed to these components and systems. The advanced features, including the onset of autonomous vehicles accompanied by millions of lines of code in software have exponentially increased the complexity of vehicle systems and decreased effectiveness of many of the safety analysis techniques being used to identify hazards and safety requirements - for example, FMEA, FTA, ETA, etc.- which were invented decades before the existence of complexities of such magnitude. This paper examines a new hazard identification technique formalized by Nancy G Leveson of Massachusetts Institute of Technology (MIT), USA in her book “Engineering a Safer World” and further elaborated in the STPA Handbook co-authored with John P Thomas in March 2018. This paper explains how the STPA technique could be effectively used to comply with ISO 26262 in various phases of the “V” lifecycle of product development and later during production, operation, service, and decommissioning. It is interesting to note that although STPA is referenced in the Standard for Safety for the Evaluation of Autonomous Products, UL 4600, the ISO 26262:2018 standard second edition makes no explicit reference to this technique although it allows practitioners to use any suitable technique so long as evidence can be provided that the objectives of the applicable clauses are met. Some reference(s) to prior work in this context will also be provided.
Bongirwar, Rajiv
Driving Automation System Test Scenario Development Process Creation and Software-in-the-Loop Implementation2021-01-00624/6/2021
Automated driving systems (ADS) are one of the key modern technologies that are changing the way we perceive mobility and transportation. In addition to providing significant access to mobility, they can also be useful in decreasing the number of road accidents. For these benefits to be realized, candidate ADS need to be proven as safe, robust, and reliable; both by design and in the performance of navigating their operational design domain (ODD). This paper proposes a multi-pronged approach to evaluate the safety performance of a hypothetical candidate system. Safety performance is assessed through using a set of test cases/scenarios that provide substantial coverage of those potentially encountered in an ODD. This systematic process is used to create a library of scenarios, specific to a defined domain. Beginning with a system-specific ODD definition, a set of core competencies are identified. These core competencies are then considered both in isolation and in conjunction with other potential confounding factors (e.g. other traffic or atmospheric conditions); with “edge cases” being represented as compounded or unique sets of confounding factors. Using this approach, a candidate scenario set is presented, along with a discussion of nuances and necessary considerations in scenario selection. These approaches are combined in a simulated environment to demonstrate their use. Finally, a strategy is proposed to automate the overall scenario testing process to make the execution less cumbersome. This process of test scenario creation strictly follows the ISO 26262 concept phase to verify the safety goals and functional safety requirements.
Patil, Mayur, Lybarger, Alexander, Midlam-Mohler, Shawn, Stoddart, Evan
V2X Connectivity with ROS for AD Applications2021-01-00604/6/2021
Increased levels of autonomy requires an increasing amount of sensory data for the vehicle to make appropriate decisions. Sensors like camera, Lidar and Radar will help to perceive the surroundings, exposing nearby objects and blind spots within the line of sight. With V2X connectivity, vehicles communicate to other vehicles and infrastructure using wireless communications even in non-line of sight conditions. This paper presents an approach to utilize a V2X system to develop Automated Driving (AD) features in a Robot Operating System (ROS) environment. This was achieved by developing ROS drivers and creating custom messages to enable the communication between the V2X system and vehicle sensors. The developed algorithms were tested on FEV’s Smart Vehicle Demonstrator. The test results show that the proposed V2X automated driving approach has increased reliability compared to that of camera, Radar and Lidar based autonomous driving.
Yedida, Siddhartha, Paudyal, Ajay, Matta, Sherif, Tasky, Tom
Techno-Economic Analysis of Fixed-Route Autonomous and Electric Shuttles2021-01-00614/6/2021
This paper takes a realistic approach to develop a techno-economic analysis for fixed-route autonomous shuttles. To develop a model for analysis, the current state of technology was used to approximate three timelines for achieving SAE level 5 capabilities: progressive, realistic, and conservative. Within these timelines, there are four different increments for advancements in the technology laid out as follows: SAE Level 0 - human driver, SAE Level 4 - in-vehicle safety operator, SAE Level 4 - remote safety operator, and SAE Level 5 - no safety operator. These increments in the changes of the technology were chosen based on the trends in the industry. Various shuttle models were used based on different rider quantities and drive-train requirements (electric vs gas) in this analysis. This allows for further understanding of how these deployment plans will vary the cost for shuttles operating in high, mid, and low ridership demand environments. Additional drive-train comparison shows the savings based on the choice of electric vs ICE vehicles. Taking these parameters into consideration, simulations were run for the various vehicle models in the various ridership demand environments to produce the economic costs for each situation. It was found that in 15 years there is an economic savings of 72%, 68%, 43%, and 35% for small, medium, large, and extra-large shuttles, respectively if deployed with the conservative plan of becoming SAE Level 4 with an in-vehicle safety operator in 2 years, SAE Level 4 with a remote safety operator in 4 years, and SAE Level 5 in 8 years.
Goberville, Nick, Zoardar, Md Marsad, Rojas, Johan, Brown, Nicolas, Motallebiaraghi, Farhang, Navarro, Anthony, Asher, Zachary
System Architecture Design Suitable for Automated Driving Vehicle: Hardware Configuration and Software Architecture Design2021-01-00734/6/2021
Our L2-automated driving system enabling a driver to take his/her hands off from the steering wheel is self-operating on a highway, allowing the vehicle to automatically change lanes and overtake slow-speed leading vehicles. It includes an OTA function, which can extend the ODD after the market launch. To realize these features in reasonably safer and more reliable ways, system architecture must be designed well under hardware and software implementation constraints. One such major constraint is the system must be designed to make the most out of the existing sensor configuration on the vehicle, where five peripheral radars and a front camera for ADAS as well as panoramic-view and rear-view cameras for monitoring are available. In addition, four LiDARs and a telephoto camera are newly adopted for ADS. Another constraint is the system must consist of reliable redundant components for fail-safe operation. When one component is dysfunctional due to a malfunction or temporal system limitation, others must keep the functionalities properly so that vehicle control is maintained without loss of sight of the surrounding objects for at least four seconds so that the driver can reasonably safely resume manual driving. To attain a high-level of backup controllability and visibility, we employ the redundant sensor configuration along with a redundant battery, steering and break actuators, and communication channels. We have also designed the ECU where a high-performance SoCs and highly-reliable MCUs are mounted to achieve ASIL-D. A further constraint is the limited computational resources for embedded systems. Our ADS constitutes many functions: localization, object recognition, map-based lane generation, path planning, vehicle controlling, backup vehicle controlling, and HMI. It is designed so that each function can take advantage of the CPU core exclusively as much as possible so as to be less disrupted by other working functions.
Kunisa, Akiomi, Nemoto, Yusuke, Kato, Hiroshi, Hasegawa, Tomonori, Kato, Masanori, Mashima, Tomohisa
Human Body Orientation from 2D Images2021-01-00824/6/2021
This work presents a method to estimate the human body orientation using 2D images from a person view; the challenge comes from the variety of human body poses and appearances. The method utilizes OpenPose neural network as a human pose detector module and depth sensing module. The modules work together to extract the body orientation from 2D stereo images. OpenPose is proven to be efficient in detecting human body joints, defined by COCO dataset, OpenPose can detect the visible body joints without being affected by backgrounds or other challenging factors. Adding the depth data for each point can produce rich information to the process of 3D construction for the detected humans. This 3D point’s setup can tell more about the body orientation and walking direction for example. The depth module used in this work is the ZED camera stereo system which uses CUDA for high performance depth computation. One of the possible applications for this method is for social robots where the robot has to navigate between crowds; the human body orientation can be an important input for the path planner here. Other application might require the robot to face the human user for interaction, this method provides the robot with the info required to face the human user. This method is aimed for indoors activity to ensure higher accuracy.
Abughalieh, Karam, Alawneh, Shadi
Speed Limiter Using Disturbance Observer2021-01-01024/6/2021
This paper suggests disturbance observer which improves performance of speed limit assist control. The nonlinear disturbance observer was designed so that disturbance caused by parameter and load uncertainties is able to be estimated exponentially. With the contribution of the observer, feed-forward and integral controllers can be omitted while improving steady-state error elimination and overshoot reduction. The acceleration observer is also designed to reduce the effect of wheel slip and changing slope. The performance of the controllers has been verified not only on flat roads, but also on wave road and rapidly changing ramps.
Son, Huiun, Jo, Kyuhwan, Kim, Sangjoon, Cho, Jinkyeom, Jeon, Sungbae
A Method of Filter Implementation Using Heterogeneous Computing System for Driver Health Monitoring2021-01-01034/6/2021
Research in any field of study requires analysis and comparisons or real-time predictions to extract useful information. To prove that the results have practical potential, various filtering techniques and methodologies should be designed and implemented. Filters being a class of signal processing helps innovate new technologies with various kinds of outcomes, using filters there are always various methods to solve a problem. Considering the current COVID-19 situation, researchers are working on sequencing the novel coronavirus and the genomes of people afflicted with COVID-19 using CPUs and GPUs along with various filtering techniques. In this paper we are using a method of filter implementation to collect raw heart rate data samples from fingertip and ear lobe and process those results on CPUs and GPUs. Our method of implementation to collect raw heart rate data is using a photoplethysmography method. We all know that the moving average filtering technique is the most commonly usedfor averaging an array of sampled data but in this paper we reconstructed the entire moving average filter with a slightly different averaging method where we will prove how our filter technique is better than the traditional moving average filter. This filtering technique is implemented and compared on both GPUs and CPUs. However, the filters on GPUs are slightly altered as per the GPU framework and CUDA programming techniques to optimize and output challenging results. We will also conduct Human trials for this concept and talk about how the heart rate changes while driving and also considering environmental conditions and scenarios. The findings of this work are also compared with apple watch heart rate data as it is the most accurate heart rate sensing device in the market with less than 2% error rate.
Sinnapolu, Giribabu, Alawneh, Shadi
Fusing Offline and Online Trajectory Optimization Techniques for Goal-to-Goal Navigation of a Scaled Autonomous Vehicle2021-01-00974/6/2021
Enabling self-driving vehicles to efficiently and autonomously navigate through an obstacle-filled environment remains a topic of significant contemporary research interest. Motion-planning frameworks, encapsulating both path- and trajectory-planning, have played a dominant role in realizing the deployment of a “sense-think-act” intelligence for autonomous vehicles. However, verification and validation of such intelligence on actual self-driving autonomous vehicles has been limited. Simulation-based verification and validation has the advantage of permitting diverse scenario-based testing and comprehensive “what-if” analyses - but is ultimately limited by the simulation fidelity and realism. In contrast, testing on full-scale real-world systems is constrained by the usual challenges of time, space, and cost engendered in reproducing diverse scenarios in practice. Further, motion-planning frameworks often engender a mixture of global-planning (typically performed offline) coupled with a sensor-based local-planning (typically done online), which requires both simulation and physical testing. Thus, scaled vehicle experimentation provides researchers with an exciting via-media to evaluate the performance and robustness of motion-planning algorithms on actual physical hardware - especially in real-time sensor-based motion planning settings. In this paper, we analyze a 1/10th scale F1/10 vehicle's performance in simulation and the actual hardware. A global planning algorithm is used to provide the waypoints for a feasible collision-free path between the start and goal configurations in the environment. We explored the deployment of Rapidly exploring Random Tree (RRT) and Rapidly exploring Random Tree* (RRT*). The Time Elastic Band local trajectory planner in ROS is then used for the realization of smooth, feasible paths between the waypoints. A comparison of validation in simulation has been provided with a detailed discussion of the parametric tuning for improving each case's performance.
Joglekar, Ajinkya, Deshpande, Bhooshan, Basuthakur, Mugdha, Krovi, Venkat N
Integrating Fuzz Testing into the Cybersecurity Validation Strategy2021-01-01394/6/2021
Automotive systems have become increasingly more complex, interconnected and prone to cyberattacks in recent years. With larger software bases and multiple external communication interfaces, the risks for new vulnerabilities and attack vectors on vehicles also increase. Therefore, modern cybersecurity validation is highly stressed for finding security vulnerabilities and robustness issues early and systematically at every stage of the product development process. The integration of a sophisticated fuzz testing program within the overall cybersecurity validation strategy allows for accommodating towards these challenging demands. In this paper, we review a general automotive cybersecurity engineering process containing functional testing, vulnerability scanning and penetration testing, and highlight shortcomings that can be complemented by fuzz testing. We present how fuzz testing is not only beneficial to improve product security directly by detecting weaknesses, but also indirectly by providing input to allow enhancing other testing activities. Finally, we provide a suggestion for an updated cybersecurity engineering process, which gives guidance on when fuzz testing should be performed and how fuzz testing should interface with other testing activities. Our approach is compliant to the ISO/SAE DIS 21434 cybersecurity engineering process. The approach uses Threat Analysis and Risk Assessment (TARA) together with Cybersecurity Assurance Levels (CALs) for the systematic identification of high-priority attack vectors and assignment of testing priorities. With this knowledge, it is possible to decide where, when and how often fuzz testing shall be applied for both finding unknown vulnerabilities and regressions in an automatized manner. This approach identifies issues earlier and with greater coverage than functional testing, vulnerability scanning and penetration testing could achieve on their own. As a result, by following this approach, the overall cybersecurity engineering process is more comprehensive, security remediation costs are lower, and resources for manual activities such as penetration testing are used more efficiently.
Vinzenz, Nico, Oka, Dennis Kengo
No Cost Autonomous Vehicle Advancements in CARLA through ROS2021-01-01064/6/2021
Development of autonomous vehicle technology is expensive and perhaps more complicated than initially thought, as evidenced by the recent rollback of anticipated delivery dates from companies such as Tesla, Waymo, GM, and more. One of the most effective techniques to reduce research and development costs and speed up implementation is rigorous analysis through simulation. In this paper, we present multiple autonomous vehicle perception and control strategies that are rigorously investigated in the user friendly, free, and open-source simulation environment, CARLA. Overall, we successfully formulated potential solutions to the autonomous navigation problem and assessed their advantages and disadvantages in simulation at no cost. First, a lane finding method utilizing polynomial fitting and machine learning is proposed. Then, the waypoint navigation strategy is described, along with route planning. Object detection is then implemented using pre-trained convolutional neural networks. A classic PID control strategy and the Stanley Method were investigated for lateral and longitudinal control of the vehicle. Finally, each of these components are simultaneously applied in the simulation environment using the robot operating system (ROS). As a result, we have achieved successful self-driving simulation. The key takeaway is that the perception and control strategies proposed can be easily transitioned towards physical implementation, through the use of ROS. The overall conclusion is that the CARLA simulation environment is a reliable workbench to test innovative solutions that could become technology enablers for the autonomous vehicle industry.
Prescinotti Vivan, Gabriel, Goberville, Nick, Asher, Zachary, Brown, Nicolas, Rojas, Johan
Stability Criteria for Accurate Path Tracking in Automated Guided Vehicle Systems2021-01-00934/6/2021
Satisfactory performance of intelligent vehicles systems in tracking a predefined trajectory requires an efficient control scheme to generate steering control signals from posture errors (i.e., errors in position and orientation). For such systems, it is necessary at each instant to control steering action so that any deviation from the path is corrected in a stable manner, in a reasonable time and without any oscillation about the desired path. This paper deals with stability of motion and motion control of intelligent vehicle systems. In this regard, the general control structure and specification of an optimum range of predefined control parameters for accurate path tracking of these systems are determined. A two degree of freedom (DOF) nonlinear dynamic model is developed to represent their plane motion. Path tracking of the vehicle is attained by controlling the position and orientation errors about the trajectory, which is accomplished by modifying the steering input signal on the basis of error feedbacks to the controller. Employment of various stability criteria and other constraints such as applying the physical limits of the vehicle to the controlled system narrows down the range of control parameters, within which the controlled system would remain stable. Experimental results demonstrating the performance of the system are reported.
Mehrabi, Mostafa
Motion Estimation of Connected and Automated Vehicles under Communication Delay and Packet Loss of V2X Communications2021-01-01074/6/2021
The emergence of the connected and automated vehicle (CAV) technology enables numerous advanced applications in our transportation system, benefiting our daily travels in terms of safety, mobility, and sustainability. However, vehicular communication technologies such as Dedicated Short-Range Communications (DSRC) or Cellular-Based Vehicle-to-Everything (C-V2X) communications unavoidably introduce issues like communication delay and packet loss, which will downgrade the performances of any CAV applications. In this study, we propose a consensus-based motion estimation methodology to estimate the vehicle motion when the vehicular communication environment is not ideal. This methodology is developed based on the consensus-based feedforward/feedback motion control algorithm, estimating the position and speed of a CAV in the presence of communication delay and packet loss. The simulation study is conducted in a traffic scenario of unsignalized intersections, where CAVs coordinate with each other through V2X communications and cross intersections without any full stop. Game engine-based human-in-the-loop simulation results shows the proposed motion estimation methodology can cap the position estimation error to ±0.5 m during periodic packet loss and time-variant communication delay.
Wang, Ziran
Predicting Desired Temporal Waypoints from Camera and Route Planner Images using End-To-Mid Imitation Learning2021-01-00884/6/2021
This study is focused on exploring the possibilities of using camera and route planner images for autonomous driving in an end-to-mid learning fashion. The overall idea is to clone the humans’ driving behavior, in particular, their use of vision for ‘driving’ and map for ‘navigating’. The notion is that we humans use our vision to ‘drive’ and sometimes, we also use a map such as Google/Apple maps to find direction in order to ‘navigate’. We replicated this notion by using end-to-mid imitation learning. In particular, we imitated human driving behavior by using camera and route planner images for predicting the desired waypoints and by using a dedicated control to follow those predicted waypoints. Besides, this work also places emphasis on using minimal and cheaper sensors such as camera and basic map for autonomous driving rather than expensive sensors such Lidar or HD Maps as we humans do not use such sophisticated sensors for driving. Also, even after decades of research, the reasonable place for ‘mid’ in the End-to-End approach, as well as, the trade-off between data-driven and math-based approach is not fully understood. Therefore, we focused on the end-to-mid learning approach and tried to identify the reasonable place for ‘mid’ in the end-to-end pipeline.
Arul Doss, Aravind Chandradoss, Guvenc, Levent
Studies on Simulation and Real Time Implementation of LQG Controller for Autonomous Navigation2021-01-01084/6/2021
The advancement in embedded systems and positional accuracy with base station GPS modules created opportunity to develop high performance autonomous ground vehicles. However, the development of vehicle model and making accurate state estimations play vital role in reducing the cross track error. The present research focus on developing Linear Quadratic Gaussian (LQG) with Kalman estimator for autonomous ground vehicle to track various routes, that are made with the series of waypoints. The model developed in the LQG controller is a kinematic bicycle model, which mimics 1/5th scale truck. Further, the cubic spline fit has been used to connect the waypoints and generate the continuous desired/target path. The testing and implementation has been done at APS labs, MTU on the mentioned vehicle to study the performance of controller. Python has been used for simulations, controller coding and interfacing the sensors with controller. From the results, it has been confirmed that, the vehicle is able to track the given path within the cross track error of ±0.2m.
Dudekula, Ahammad Basha, Naber, Jeffrey
Mechanism for Secure Storage without a Trusted Execution Environment for Low/Mid Automotive Segments2021-01-01454/6/2021
Increasing adoption of connected vehicles has led the vehicle manufacturers to deal with security issues in a vehicle-embedded system. In order to secure the security critical instructions/operations such as security functions, cryptographic credentials in a connected embedded system Arm Trustzone Technology is widely used in automotive embedded system across Cockpit, ADAS, V2X, etc. The Arm Trustzone technology protects the security critical operations by executing them in a trusted execution environment (TEE) parallelly by isolating them through hardware from classic rich execution environment (REE) using the shared hardware resources by protecting the confidentiality and integrity of the system. The Arm Trustzone technology uses secure configuration register (SCR) to switch between secure and non-secure worlds by providing two execution environments with different privileges through secure monitor call (SMC) and arm trusted firmware (ATF) across the resources e.g., memory, interrupts, peripherals etc. with different exception levels (EL). The enhanced security provided by Arm Trustzone technology is biased by resource constraints to the operations running in the REE when the resource isolation switches to the TEE through SCR. Hence, for the limited resource embedded automotive cockpits the driver assisting functions such as navigation system, which are running, in the REE gets void of resources due to the TEE, which in turn affects the functional safety of the overall driving system. Here, in order to eliminate the ambiguity between security and safety for the limited resource automotive cockpits where the addition of TEE is cannot be done, an efficient secure storage system is proposed without TEE in Arm Trustzone technology. The proposed approach stores the RPMB (Replay Protected Memory Block) key in the specialized memory of Arm Trustzone Technology during the vehicle provisioning with its encrypted version stored in the RPMB block of MMC. During the Harman secured boot loader based booting of the cockpit system, the derived key is generated from this key after decryption, and the application data based operations are executed in kernel space through an introduced secure storage kernel module in kernel, thereby providing the secured storage of the security critical operations in the Arm Trustzone Technology without TEE.
Ansari, Asadullah, Thekkumbadan, Shyju, Das, Sourabh, JOSE, JIPIN, Sana, Iflaha
Intelligent Voice Activated Drone(s) for in-Vehicle Services and Real-Time Predictions2021-01-00634/6/2021
Today, commercially available drones have limited use-cases in the rapidly evolving community. However, with advances in drone and software technology, it is possible to utilize these aerial machines to solve problems in a variety of industries such as mining, medical, construction, and law enforcement. For example, in order to reduce time of investigation, Indiana State Police are currently utilizing ad-hoc commercial drones to reconstruct crash scenes for insurance and legal purposes. In this paper, we illustrate how to effectively integrate drones for in-vehicle services and real-time prediction for automotive applications. In order to accomplish this, we first integrate simpler controls such as voice-commands to control the drone from the vehicle. Next, we build smart prediction software that monitors vehicle behavior and reacts in real-time to collisions. Furthermore, we employ object recognition techniques through In-Vehicle Infotainment (IVI) systems to identify the surroundings based on inputs from drone-mounted camera sensors. Consequently, we implement object identification and smart maneuver of the drone in relation to the vehicle; as well, employ timely deployment of the drone prior to collision for emergency assistance and crash reconstruction purposes. The goal is to optimize performance and amplify safety and security of the vehicle. The prototype detailed in this paper was tested on a vehicle moving at a speed of 45 mph. The driver of the vehicle can deploy and control the drone using voice commands. The drone follows the vehicle and is in-sync with the vehicle and performs tasks to aid in post-collision assistance and crash reconstruction.
Nithiyanantham, Mayunthan, Sinnapolu, Giribabu
Secure Controller Area Network Logging2021-01-01364/6/2021
Practical encryption is an important tool in improving the cybersecurity posture of vehicle data loggers and engineering tools. However, low-cost embedded systems struggle with reliably capturing and encrypting all frames on the vehicle networks. In this paper, implementations of symmetric and asymmetric algorithms were used to perform envelope encryption of session keys with symmetric encryption algorithms while logging vehicle controller area network (CAN) traffic. Maintaining determinism and minimizing latency are primary considerations when implementing cryptographic solutions in an embedded system. To satisfy the timing requirements for vehicle systems, the memory-mapped Cryptographic Acceleration Unit (mmCAU) on the NXP K66 processor enabled 6.4Mb/sec symmetric encryption rates, which enables logging of multiple channels at 100% bus load. Using AES-128 in Cipher Block Chaining (CBC) mode provides the encryption for data confidentiality. Errors and integrity checks are handled by a Cyclic Redundancy Check (CRC) checksum withing the data and digitally signed SHA256 hash values of the overall encrypted record secured the integrity of the data. A hardware security module (HSM) is utilized to store asymmetric key pairs for key management. The HSM implements Elliptic-Curve Cryptography (ECC) algorithms for key exchanges and digital signatures. Secure collection and secure data uploads to a central server are demonstrated. This work and the source code are open source with the goal of inspiring improved secure communications for vehicle networks.
Daily, Jeremy, Van, Duy
Windshield with Enhanced Infrared Reflectivity Enables Packaging a Driver Monitor System in a Head-Up Display2021-01-01054/6/2021
Integration of a driver monitor system (DMS) in a head-up display (HUD) gives the monitor camera a continuous view of the driver’s face, since the driver always faces the road ahead. However, with both infrared (IR) illuminator and IR camera packaged in the HUD, reflectivity of the windshield is important at IR wavelengths used by the camera. Not only is windshield IR reflectivity important for a clear camera image of the driver’s face, but increasing windshield reflectivity also decreases the effect of ambient sunlight on the camera image of the driver’s face. We describe a method to measure windshield reflectivity, both for the 940 nm band used by a DMS, and for visible light for the HUD. The measurement method uses a fiber-optic spectrometer, two collimating lenses, and a method to compensate for sample tilt. The lenses are mounted on a stage that adjusts the height above the sample. As an example, this method was used to characterize an IR reflecting windshield, prepared for a prototype automotive HUD. At 940 nm, and 45° angle of incidence, the measured reflectivity is > 85% for unpolarized incident light. For visible light at 550 nm, and 62° angle of incidence, the measured reflectivity is 13.9% for both an IR reflecting windshield and for a reference windshield, for unpolarized incident light. The prototype windshield gives a good reflected image for the DMS IR camera and a good HUD image as seen by the driver. The method used to prepare this prototype windshield is suitable for high-volume production.
Lambert, David K., Itsede, Fidelis, Tomura, Kazuhiro, Nohara, Atsushi, Chou, Kinryo, Carty, Dylan
Accurate Pressure Control Based on Driver Braking Intention Identification for a Novel Integrated Braking System2021-01-01004/6/2021
With the development of intelligent and electric vehicles, higher requirements are put forward for the active braking and regenerative braking ability of the braking system. The traditional braking system equipped with vacuum booster has difficulty meeting the demand, therefore it has gradually been replaced by the integrated braking system. In this paper, a novel Integrated Braking System (IBS) is presented, which mainly contains a pedal feel simulator, a permanent magnet synchronous motor (PMSM), a series of transmission mechanisms, and the hydraulic control unit. As an integrative system of mechanics-electronics-hydraulics, the IBS has complex nonlinear characteristics, which challenge the accurate pressure control. Furthermore, it is a completely decoupled braking system, the pedal force doesn’t participate in pressure-building, so it is necessary to precisely identify driver’s braking intention. To improve the control accuracy of the system, this paper proposed a novel pressure control strategy based on driver braking intention identification. Firstly, the structure and working principle of the novel integrated braking system was introduced. Secondly, the driver's braking intention identification strategy was designed. Thirdly, Considering the nonlinear and dynamic characteristics of the system, a cascade closed-loop control strategy including a pressure loop by the feedforward-feedback method, a position loop by the sliding-mode control method, and current loop with friction compensation was proposed. Finally, based on dSPACE products, a hardware-in-the-loop (HiL) experimental bench was built for algorithm verification. The HiL experiment results show that the pressure control strategy has the advantages of accurate response, the braking system pressure follows the driver's expected pressure well.
Zhu, Bing, Zhang, Yihan, Zhao, Jian, Chen, Zhicheng, Jin, Wanli
Model Predictive Control-Based Lateral Control of Autonomous Large-Size Bus on Road with Large Curvature2021-01-00994/6/2021
This paper describes a lateral control of autonomous large size buses on road with large curvature. In the case of long and wide commercial vehicle such as large bus, applying centerline tracking controllers in constrained environments such as large curved road (e.g. turning at intersection) may cause some concerns. Two concerns are considered: inner lane crossing related to collisions with curb and opposite lane crossing related to threatening surrounding vehicles. Considering relations between width and curvature of the road and length and width of the large size bus, the curvature of road at which inner or outer lane crossing begin to occur was calculated when centerline tracking controller was applied. Thus, the proposed algorithm optimizes motion of the bus by using model predictive control (MPC) using road geometry as constraints. Based on geometric relations of curved road and vehicle, distance from the lane to each corner of the vehicle is defined using relative lateral position and relative heading angle of the vehicle and road center line, which is used in the MPC formulation. A slack variables are used to solve feasibility problem caused by the difference between open loop prediction and closed loop trajectory in receding horizon optimal control. Performance indexes are defined to evaluate performance of the algorithms. The proposed algorithm was evaluated via computer simulation. The performance of the proposed algorithm was compared with the centerline tracking controller. It is shown that the proposed algorithm allows the large size bus to cope well with steering on road with large curvature.
Lim, Hyeongho, Kim, Changhee, Jo, Ara
DA-IVE: MLP Based Data Association Method for Instantaneous Velocity Estimation Using Multi-Radar: An Experimental Validation Study2021-01-00924/6/2021
This paper describes a novel Multi-Layer Perceptrons (MLP) learning-based association algorithm that is used in conjunction with an Instantaneous Velocity Estimator (IVE) to estimate the velocity of a surrounding vehicle using multi-radar sensors. The IVE algorithm requires at least two targets to be able to provide a velocity estimate. The approach suggested in this paper performs three stages of filtering on a list of targets available for the association to a given track. The algorithm identifies the one pair of targets that will provide the best instantaneous velocity estimation from all possible pairs. The three stages of filtering described ahead are, I - Semantic gating, II - MLP scoring, and III - Algebraic scoring. The IVE algorithm performs linear regression on the pair of targets it is finally provided to come up with a velocity estimation. This research also describes a novel method of labeling radar targets for use in the training of the neural network in association stage II. A thorough analysis of the correlation between a radar target’s quality and attributes is performed and presented here. The performance of the proposed algorithm is evaluated using real-world data collected through the ZF Automated Driving prototype vehicle.
Shakibajahromi, Bahareh, Krishnan, Anirudh Sarathy, Ati, Dilip, Jabalameli, Amirhossein, Kanzler, Steven, Shayestehmanesh, Saeed
Communication for Plug-in Vehicles as a Distributed Energy SourceJ2847/3_202103 (Historical)3/23/2021
This document applies to a plug-in electric vehicle (PEV) which is equipped with an onboard inverter and communicates using IEEE 2030.5-2018. It is a supplement to the SEP2 standard, which supports the use cases defined by SAE J2836/3. It provides guidance for the use of the SEP2 distributed energy resource function set with a PEV. It also provides guidance for the use of the SEP2 flow reservation function set, when used for discharging. It is not intended to be a comprehensive guide to the use of SEP2 in a PEV. Note that in this document, SEP2 is used interchangeably with IEEE 2030.5-2018.
Hybrid - EV Committee
Interconnection Requirements for Onboard, Grid Support Inverter SystemsJ3072_202103 (Historical)3/10/2021
This SAE J3072 Standard establishes requirements for a grid support inverter system function which is integrated into a plug-in electric vehicle (PEV) which connects in parallel with an electric power system (EPS) by way of conductively coupled, electric vehicle supply equipment (EVSE). This standard also defines the communication between the PEV and the EVSE required for the PEV onboard inverter function to be configured and authorized by the EVSE for discharging at a site. The requirements herein are intended to be used in conjunction with IEEE 1547 and IEEE 1547.1. This standard shall also support interactive inverters which conform to the requirements of IEEE 1547-2003 and IEEE 1547.1-2005, recognizing that many utility jurisdictions may not authorize interconnection.
Hybrid - EV Committee
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