Browse Topic: Highly automated vehicles

Items (128)
New forms of highly automated Advanced Air Mobility (AAM) aircraft, such as electric vertical take-off and landing (eVTOL) vehicles, could transform transportation, cargo delivery, and a variety of public services. The National Aeronautics and Space Administration (NASA) conducted a series of flight demonstrations in collaboration with the Defense Advanced Research Projects Agency (DARPA) and Sikorsky Aircraft (a Lockheed Martin company) to progressively evaluate autonomous technologies. The autoland flight test research is a first in series for investigating the world’s first procedural descending-decelerating automated landing with vertical guidance Instrument Flight Procedures (IFP). The Sikorsky Optionally Piloted Vehicle (OPV) experimental UH-60 Black Hawk was used to evaluate a flight path’s four-dimensional trajectory (4DT) management into primitive commands and then follow those commands to a Point-in-Space (PinS) landing to the ground. All flight procedures were manually flown to the ground at 12 degrees with a 20-knot tail wind to ensure flight safety before automation was engaged. New and novel high precision approach procedures could pave the way for all future VTOL operations.
Zahn, DavidPatterson, GayleWilliams, EthanEggum, SarahFettrow, Tyler
csp1071 test Construction of The Traffic Law and Regulation Framework for Automated DrivingSAE-PP-002902/18/2021
Road automated driving as a new generation of information technology and the integration of the transport industry's development has become a new round of global scientific and technological innovation and industrial transformation. This technology will promote the continuous upgrading of the field of road traffic. At present, the government, enterprises, and investors all take this as the goal and direction to accelerate automated driving in China. A reasonable traffic law and regulation system is required to promote the healthy development of automatic driving and fully release scientific and technological innovation subjects' vitality. Until now, China has formulated an official rule concerning the road testing of automated driving. According to this rule, no passenger and freight transportation can be officially applied using automatic vehicles. Therefore, this paper tries to construct the traffic law and regulation framework to promote automated driving development. This paper firstly summarizes the profound reform of automated driving on the road traffic industry in terms of vehicles, infrastructure, practitioners, and transportation services. Based on China's current administrative rules and traffic regulations, the legal and institutional obstacles in automatic driving are analyzed. This paper proposes a traffic law and regulation framework to promote the development of automated driving. The proposed framework can help the transport authority administrate automated driving in legal identity, demonstration application, transportation operation, practitioner management, and scene management. Finally, the policy suggestions to help develop automated driving are put forward. Through enhanced supervision, mutual recognition of qualification, regulation mode innovation, ecosystem construction, and multi-party cooperation, the automated driving market and partners' vitality can be significantly stimulated
SintzADMIN, JeneaneAnthony, Lindsay
7.0.108 - Challenges Faced for Parameterization & Validation of a Small Gasoline Engine Plant Model for Application of EMS DevelopmentSAE-PP-002842/4/2021
Control algorithm development for typical Engine Management System is a challenging task. To develop a reliable control algorithm, proper closed loop testing environment is required. In such development activity, it is of prime importance to validate the algorithm on a standalone target engine. This can be achieved in engine test cell where the actual engine will be controlled by prototype ECU. But this process has drawbacks like higher testing cost, time consuming, non-reusability of test bed etc. Simulation based engine plant model development for closed loop ECU testing is an effective technique for such application. Various generic engine models are available for such application.to suit a particular target engine these model need to be parameterized with precise engine data. The vehicle parameters used for parameterization are typically obtained from actual test and engine design data. This paper elaborates the process and challenges faced while parameterization and validation of engine plant model in simulation environment and steps followed while parameterizing a two cylinder gasoline engine to suit EMS development. Simulations were carried out in Model In Loop (MIL) and Hardware In Loop (HIL). Validation results were compared with actual vehicle data from dynamometer trials and are presented in corresponding sections.
Lname, Fname
7.0.107 - Design and Development of Capacitance Type Level Sensor for Automotive Vehicle ApplicationSAE-PP-002832/4/2021
Fuel level sensor is a device to indicate the level of the fuel in fuel tank fitted in an automobile. This will have features to communicate the fuel level to the dashboard of the vehicle and is of significant attention to the driver during vehicle usage. The advanced instrumentation provides a lot of information on the dashboard display such as information about fuel level, computing mileage, miles to go or miles to empty, fuel economy, average mileage, etc. Presently, the float arm type with Thick Film Resistor(TFR) and Reed switch type fuel level sensors are being used. To have accurate information for computing, the present sensors are not supporting due to its limitations like nonlinearity, fluctuating output due to slosh, output variations in steps and not continuous. The measurement accuracy of the fuel level sensor needs to be focused to rely on the information available on the dashboard instrument. Hence, it is vital to have a sensor with better reliability, accuracy and adaptability. Capacitance technology based level sensor is identified for development as one of the solutions to meet the demands of the above requirements and this paper portrays the complete perspective and design methodology of capacitance based fuel level sensor. The basics of capacitance measurement, design concepts, design validations, proto-type results are elaborated in this paper.
Lname, Fname
Construction of The Traffic Law and Regulation Framework for Automated DrivingSAE-PP-002462/3/2021
Road automated driving as a new generation of information technology and the integration of the transport industry's development has become a new round of global scientific and technological innovation and industrial transformation. This technology will promote the continuous upgrading of the field of road traffic. At present, the government, enterprises, and investors all take this as the goal and direction to accelerate automated driving in China. A reasonable traffic law and regulation system is required to promote the healthy development of automatic driving and fully release scientific and technological innovation subjects' vitality. Until now, China has formulated an official rule concerning the road testing of automated driving. According to this rule, no passenger and freight transportation can be officially applied using automatic vehicles. Therefore, this paper tries to construct the traffic law and regulation framework to promote automated driving development. This paper firstly summarizes the profound reform of automated driving on the road traffic industry in terms of vehicles, infrastructure, practitioners, and transportation services. Based on China's current administrative rules and traffic regulations, the legal and institutional obstacles in automatic driving are analyzed. This paper proposes a traffic law and regulation framework to promote the development of automated driving. The proposed framework can help the transport authority administrate automated driving in legal identity, demonstration application, transportation operation, practitioner management, and scene management. Finally, the policy suggestions to help develop automated driving are put forward. Through enhanced supervision, mutual recognition of qualification, regulation mode innovation, ecosystem construction, and multi-party cooperation, the automated driving market and partners' vitality can be significantly stimulated. Keywords: Traffic Law and Regulation, Automated Driving, Administrative Rules and regulations, Road Testing, Demonstration Application, Commercial Operation
MobrxivNonAdmin, Lindsay
1.1.216 - Tailored Design and Layout for Loss Minimization or Cost-Effective Commonality of Parts - A Contradictory ConflictSAE-PP-002422/3/2021
In order to minimize the development and production costs in the automotive industry, despite steadily increasing variety of models and applications offered by the OEMs, the pressure on standardization of components and production processes is increasing continuously. As a direct consequence, modular engine families are already established with high degrees of common parts and kits as well as standardized interfaces for all vehicle platforms by most manufacturers these days. At the same time, the world adopted and announced massive legal demands concerning the reduction of CO2 emissions for the entire vehicle fleet. In addition to the optimization of the combustion process, the exhaust gas aftertreatment and thermal management, the use of improved and more resilient materials for higher reduction of mechanical friction leads to a significant amount of the realized lowering in fuel consumption respective CO2 emissions. Significant future potential for friction reduction and loss minimization is expected to result from, for example, one for the particular application optimized, on-demand component dimensioning and tailored calibrations. This dedicated fine-tuning approach is contrary to the widely spread application of a clear common part strategy. In the course of this paper the question will be discussed whether the additional cost of a component diversification can be justified within an engine family in contradiction to a best cost approach by using the scaling effects of parts communization.
Mutagaana, Festo
2.0.104 - Tackling Three Critical Issues of Transportation: Environment, Safety and Congestion Via Semi-autonomous PlatooningSAE-PP-002142/1/2021
In recent years, platooning emerged as a realistic configuration for semi-autonomous driving. In the SARTRE project, simulation and physical tests were performed to validate the platooning system not only in testing facilities but also in conventional highways. Five vehicles were adapted with autonomous driving systems to have platooning functionalities, enabling to perform platoon tests and assess the feasibility, safety and benefits. Although the tested system was in a prototype, it demonstrated sturdiness and good functionality, allowing performing conventional road tests. First of all the fuel consumption decreased up to 16% in some configurations and different gaps between the vehicles were tested in order to establish the most suitable for platooning in terms of safety and economy. Additionally, the platooning technology enables a new level of safety in highways. Around 85% of the accident causation is the human factor. With platooning, the human factor is reduced almost entirely, making it a more efficient and safer system. With platooning, the traffic flow is more homogeneous with several vehicles travelling at the same speed and therefore accident situations are less probable while helping to maintain a steady traffic flow with no stop and go situations. For the same reason, the traffic flow is more manageable enabling advanced traffic management. Thus, the traffic congestion can be reduced and, again, reducing another source of emissions. All the potential advantages of a platooning technology which has been developed and tested are studied in this paper through test results and simulations.
Mutagaana, Festo
Automated vehicles require some level of subsystem redundancy, whether to allow a transition time for driver re-engagement (L3) or continued operation in a faulted state (L4+). Highly automated vehicle developers need to have safe miles accumulated by vehicles to assess system maturity and experience new environments. This article presents a conceptual framework suggesting that hardware newly available to commercial vehicle application can be used to form a steering system that will remain operational upon a failure. The key points of a provisional safety case are presented, giving hope that a complete safety case is possible. This article will provide autonomous vehicle developers a view of a near term possibility for a highly automated commercial vehicle steering solution.
Pandy, AnandaPathuri, NagamaniSalunke, PranavSubba, Srujana SreeWilliams, Dan
AVSC Best Practice for Describing an Operational Design Domain: Conceptual Framework and LexiconAVSC000022020044/15/2020
An ADS-operated vehicle’s operational design domain (ODD) is defined by the manufacturer based on numerous factors. Research is underway at other organizations to define and organize ODD elements into taxonomies and other relational constructs. In order to enhance collaboration and communication between manufacturers and developers and transportation authorities, common terms and consistent frameworks are needed. The conceptual framework presented by Automated Vehicle Safety Consortium establishes a lexicon that can be used consistently by ADS developers and manufacturers responsible for defining their ADS ODD. A common framework and lexicon will reduce confusion, align expectations, and therefore build public trust, acceptance, and confidence. The guidance in this document is intended for: The technical community (e.g. manufacturers and developers) Public agencies (e.g. regulatory authorities) Infrastructure owner-operators The public This document, Best Practice for Describing an Operational Design Domain: Conceptual Framework and Lexicon is a critical first step. It offers a conceptual framework for manufacturers and developers to use when communicating with public agencies and the general public about their ADS’s ODD. It also details a list of potential variables with definitions that manufacturers and developers might use to describe certain aspects of the ODDs of their ADS-operated vehicles. It was developed with fleet-managed, SAE Level 4 vehicles in mind — i.e. vehicles requiring no human intervention to operate within their ODD. These vehicles are NOT privately owned.
Automated Vehicle Safety Consortium
Modes of Automated Driving System Scenario Testing: Experience Report and Recommendations2020-01-12044/14/2020
With the widespread development of automated driving systems (ADS), it is imperative that standardized testing methodologies be developed to assure safety and functionality. Scenario testing evaluates the behavior of an ADS-equipped subject vehicle (SV) in predefined driving scenarios. This paper compares four modes of performing such tests: closed-course testing with real actors, closed-course testing with surrogate actors, simulation testing, and closed-course testing with mixed reality. In a collaboration between the Waterloo Intelligent Systems Engineering (WISE) Lab and AAA, six automated driving scenario tests were executed on a closed course, in simulation, and in mixed reality. These tests involved the University of Waterloo’s automated vehicle, dubbed the “UW Moose”, as the SV, as well as pedestrians, other vehicles, and road debris. Drawing on both data and the experience gained from executing these test scenarios, the paper reports on the advantages and disadvantages of the four scenario testing modes, and compares them using eight criteria. It also identifies several possible implementations of mixed-reality scenario testing, including different strategies for data mixing. The paper closes with twelve recommendations for choosing among the four modes.
Antkiewicz, MichałKahn, MaximilianAla, MichaelCzarnecki, KrzysztofWells, PaulAcharya, AtulBeiker, Sven
Driving Safety Performance Assessment Metrics for ADS-Equipped Vehicles2020-01-12064/14/2020
The driving safety performance of automated driving system (ADS)-equipped vehicles (AVs) must be quantified using metrics in order to be able to assess the driving safety performance and compare it to that of human-driven vehicles. In this research, driving safety performance metrics and methods for the measurement and analysis of said metrics are defined and/or developed. A comprehensive literature review of metrics that have been proposed for measuring the driving safety performance of both human-driven vehicles and AVs was conducted. A list of proposed metrics, including novel contributions to the literature, that collectively, quantitatively describe the driving safety performance of an AV was then compiled, including proximal surrogate indicators, driving behaviors, and rules-of-the-road violations. These metrics, which include metrics from on- and off-board data sources, allow the driving safety performance of an AV to be measured in a variety of situations, including crashes, potential conflicts, and near misses. These measurements enable the evaluation of temporal flows and the quantification of key aspects of driving safety performance. The identification and exploration of metrics focusing explicitly on AVs as well as proposing a comprehensive set of metrics is a unique contribution to the literature. The objective is to develop a concise set of metrics that allow driving safety performance assessments to be effectively made and that align with the needs of both the ADS development and transportation engineering communities and accommodate differences in cultural/regional norms. Concurrent project work includes equipping an intersection with a sensor suite of cameras, LIDAR, and RADAR to collect data requiring off-board sources and employing test AVs to collect data requiring on-board sources. Additional concurrent work includes development of artificial intelligence and computer vision-based algorithms to automatically calculate the metrics using the collected data. Future work includes using the collected data and algorithms to finalize the list of metrics and then develop a methodology that uses the metrics to provide an overall driving safety performance assessment score for an AV.
Wishart, JeffreyComo, StevenElli, MariaRusso, BrendanWeast, JackAltekar, NirajJames, Emmanuel
Perceptions of Two Unique Lane Centering Systems: An FOT Interview Analysis2020-01-01084/14/2020
The goal of this interview analysis was to explore and document the perceptions of two unique lane centering systems (S90’s Pilot Assist and CT6’s Super Cruise). Both systems offer a similar type of functionality (adaptive cruise control and lane centering), but have significantly different design philosophies and HMI (Human-Machine Interface) implementations. Twenty-four drivers drove one of the two vehicle models for a month as part of a field operational test (FOT) study. Upon vehicle return, drivers took part in a 60-minute semi-structured interview covering their perceptions of the vehicle’s various advanced driver-assistance systems (ADAS). Transcripts of the interviews were coded by two researchers, who tagged each statement with relevant system and perception code labels. For analysis, the perception codes were grouped into larger thematic bins of safety, comfort, driver attention, and system performance. Perceptions of adaptive cruise control (ACC) were similar across vehicles. Almost all participants mentioned benefits of comfort and safety associated with ACC use. Participants cited different benefits between the two vehicle’s implementations of lane centering. A majority of participants (75%) described comfort benefits associated with Super Cruise, while less than half (41%) cited comfort benefits associated with Pilot Assist. Only a few participants (25%) mentioned safety benefits associated with Super Cruise. Half (50%) of the participants mentioned safety benefits associated with Pilot Assist. Almost all participants cited fears of potential misuse of the system in which drivers might pay less attention to the driving task. Results suggest that drivers’ comprehension and expectation of these systems’ behavior are strongly influenced by their design philosophies, specifically in terms of the difference in hands-on versus hands-off-wheel implementation. The perceived role of the driver – as either a fallback driver or as an assisted driver - may be influenced by the design implementation.
Landry, StevenSeppelt, BobbieRusso, LucaMehler, BruceAngell, LindaGershon, PninaReimer, Bryan
The Design of Safe-Reliable-Optimal Performance for Automated Driving Systems on Multiple Lanes with Merging Features2020-01-01224/14/2020
Safety function for automated driving systems including advanced driver assistance systems and autonomous vehicle systems is very important. Inside safety function, predictive judge sub-function should be designed with the consideration of more and more penetration of automated driving vehicles. This paper presents the design on multiple lanes with merging features based on the author's previous Patent JP2019-147944 using predictive time-head-way and time-to-collision maps. In the author's previous work (Model Predictive Control for Hybrid Electric Vehicle Platooning Using Slope Information-Published on IEEE Transactions on Intelligent Transportation Systems), a model predictive control framework was designed. Due to the difficulty to detail the sub-safety function deeply with merging features, few works are found to deal with sensor platforms focusing on rear side, and situations of merging lane side with the consideration of relative relation variations with other vehicles and road border markers. However, performance enhancement is needed assuring 100% safety-reliability-optimality and single-objectivity. Also, platforms of on-board sensors including side and rear view are needed to deal with false negative operations and false positive operations. The optimal operation line model of human factors is designed based on time-head-way (reliability), time-to-collision (safety), and combinations of time-head-way and time-to-collision (optimality). The general theory of model predictive control is used to find the target. The model based methodology is applied to solve the human factor model of risk feeling based on only time-head-way and time-to-collision for the human reaction and acceptance metric. Experimental results validated the effectiveness of the proposed approach. The model parameters can be calibrated internationally by tuning the metric of cooperativeness. The target of the predictive judge sub-function is to move the operation point to the specified area. The predictive judge sub-function on high level is decisive for regulation control to move the operation point from difficult areas to the target area in future.
Yu, Kaijiang
Runtime Active Safety Risk-Assessment of Highly Autonomous Vehicles for Safe Nominal Behavior2020-01-01074/14/2020
Fatal crashes involving automated driving systems, has been raising the concern of minimum standard requirement for safety, reliability and performance required for Autonomous Driving System (ADS)/Advanced Driver Assistance System (ADAS) before this cutting-edge technology takes on public roads. Hence, in order to ensure necessary safety requirements of ADS/ADAS systems we propose a runtime active safety assurance module known as SConSert. SConSert performs dynamic risk assessment of “Sensing, Planning and Action module of ADS/ADAS”; to provide minimal risk maneuver in any given driving scenario. The dynamic risk assessment of ADS/ADAS system is based on the operational design domain (ODD) knowledge of the driving scenario plus the sensor capability, ADS/ADAS algorithm requirement and capability, and finally smooth and collision free maneuver requirement. So, the main concept behind SConSert is runtime derivation of situational and conditional set of contracts for a given driving scenario and ADS/ADAS system ODD; fulfillment or violation of which can help in runtime dynamic risk assessment of ADS/ADAS to plan minimal safe behavior such that necessary safety requirements can be achieved. Finally, through experiment we show that proposed runtime active assurance safety module can handle complex driving scenario, and present simulation and experimental results that emphasizes the importance of the proposed runtime safety assurance module and shows that the proposed system is capable of performing runtime dynamic risk assessment in order to keep the automated driving systems always within the safe sate that is the automated driving system always perform within its ODD.
Rathour, Swarn SinghIshigooka, TasukuOtsuka, SatoshiMARTIN, RAUL
The Effects of Small Seat Swiveling Angles on Occupant Responses during a Frontal Impact2020-01-05714/14/2020
In highly automated vehicles (HAVs), new seat configurations may be desirable to allow occupants to perform new activities. One of the current HAV concepts is the swiveled seat layout, which might facilitate communication between occupants. The main objective of this study was to investigate the effects of seat swiveling angles on occupant kinematics and injury risk predicted by a Human Body Model (HBM) during a frontal impact. A detailed 50th percentile male HBM (GHBMC M50-O) was subjected to two frontal crash pulses in a sled setup. The model was positioned on a semi-rigid seat and restrained using a pre-inflated airbag and a three-point seatbelt. Simulations included four seat swiveling angles (0, -10, -20, and -30 degrees), three occupant positions (Sedan driver, large VAN driver or Laptop user), two airbag initial locations (nominal or matching the head Y location), and the inclusion of lateral supports on the seat pan. The effects of the seat swiveling angle were similar for all occupant positions. With the airbag in the nominal location, higher seat swiveling angles led to a higher head lateral displacement and a higher risk of head injury, especially for the BrIC criterion. The Sedan driver position had higher BrIC and a larger head lateral excursion than the other two positions. This could be mitigated by aligning the airbag location with the head. Pelvic fractures were also predicted for the configurations with the highest swiveling angles. These fractures were limited by the use of seat pan lateral supports. Overall, the model responses were sensitive to both seating configurations and occupant postures, and the results suggest that swiveled seating may increase the injury risk, especially for the head and pelvis. However, simple countermeasures, such as adapted airbag location or adding lateral seat pan supports, seemed possible to mitigate the risk.
Grébonval, CyrilleTrosseille, XavierPetit, PhilippeWang, XuguangBeillas, Philippe
Unsettled Issues Concerning Semi-Automated Vehicles: Safety and Human Interactions on the Road to Full AutonomyEPR20200012/28/2020
Across the span of the SAE International-defined Levels of Driving Automation, human drivers occupy a diverse range of responsibilities and authority on the vehicle movement and the monitoring of the outside environment. From both a technological and a regulatory perspective, there is a gap that divides lower levels of automation (L1 through L3) and higher levels of automation (L4 and L5). For those vehicles that require the cooperation between a human driver and the autonomous technology, it is important to ascertain the safety consequences of such a design choice. It is also important to understand what the transition between automated driving and manual driving entails for the human driver, as well as for the surrounding traffic. This SAE EDGE™ Research Report investigates unsettled issues concerning what is commonly referred to as “semi-automation,” including an overview of the role of human drivers, the quantification of the “transition-to-manual” problem, the role played by L3 toward full automation, and regulatory and moral considerations surrounding the deployment of these vehicles. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny.
Favaro, Francesca
Taking over vehicle control from a Level 3 conditionally automated vehicle can be a demanding task for a driver, to which great research effort has been contributed in recent years. Nevertheless, more attention should be given to the following aspects. The present research of take-over either only considers the influence of drivers’ visual and second task in single scenarios. However, the drivers’ NMS (Neuromuscular) characteristic hasn’t been investigated yet, especially in complex traffic scenarios. In this paper, a take-over experiment with complex traffic scenarios are conducted to observe the state of vehicle state and arm’ EMG (Electromyography) signal. After that, the driving styles are recognized based on the experimental data. Finally, a take-over level with driving style is proposed by clustering based on the condition of human-vehicle-road.
Hanbing, WeiYanhong, WuYuxuan, ZhangRui, Xu
Unsettled Issues in Balancing Virtual, Closed-Course, and Public-Road Testing of Automated Driving SystemsEPR201901112/19/2019
This SAE EDGE™ Research Report identifies key unsettled issues of interest to the automotive industry regarding the challenges of determining the optimal balance for testing automated driving systems (ADS). Three main issues are outlined that merit immediate interest: First, determining what kind of testing an ADS needs before it is ready to go on the road. Second, the current, optimal, and realistic balance of simulation testing and real-world testing. Third, the challenges of sharing data in the industry. SAE EDGE™ Research Reports are preliminary investigations of new technologies. The three technical issues identified in this report should be discussed in greater depth with the aims of, first, clarifying the scope of the industry-wide alignment needed; second, prioritizing the issues requiring resolution; and, third, creating a plan to generate the necessary frameworks, practices, and protocols. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny.
Beiker, Sven
Pedestrian Collision Avoidance System for Autonomous Vehicles12-02-04-002112/18/2019
Advanced driver assistance systems (ADAS) are state of the art in modern vehicles (SAE level 1-2). They support the driver and improve thereby the vehicle safety during manual driving. In critical situations, collision avoidance systems warn the driver or trigger an autonomous emergency braking maneuver to mitigate or avoid a collision. Also, automated driving vehicles (SAE level 3+) must be able to avoid critical situations and must be more capable than currently available systems. During automated driving, the vehicle is responsible for the driving task instead of the driver. Therefore, safe automated driving requires robust algorithms to avoid collisions with other traffic participants in every situation, especially in critical situations with pedestrians and a limited perception ability. In this work, we investigate how automated driving vehicles can handle critical situations with pedestrians on multilane roads with an emergency braking or evasion maneuver. We focus in detail on very critical situations, where pedestrians are crossing behind an occluded area, e.g. from behind a parked car on the side of the road. In these critical situations, a collision avoidance system is not enough anymore because of the limited time-to-react. It is not acceptable that an automated driving vehicle passes obstacles very slowly. Therefore, a collision avoidance system is combined with a situation awareness planner to optimize the driving velocity. The situation awareness planner considers the sensor’s visibility and the capability of the collision avoidance system to provide a set of collision-free trajectories. This combination has the advantage that the vehicle does not need to pass objects on the side very conservative. We evaluate the approach rigorously on a set of well-defined scenarios from the Euro NCAP test protocol.
Schratter, MarkusHartmann, MichaelWatzenig, Daniel
This SAE EDGE™ Research Report identifies key unsettled issues of interest to the automotive industry regarding the challenges of achieving optimal model fidelity for developing, validating, and verifying vehicles capable of automated driving. Three main issues are outlined that merit immediate interest: First, assuring that simulation models represent their real-world counterparts, how to quantify simulation model fidelity, and how to assess system risk. Second, developing a universal simulation model interface and language for verifying, simulating, and calibrating automated driving sensors. Third, characterizing and determining the different requirements for sensor, vehicle, environment, and human driver models. SAE EDGE™ Research Reports are preliminary investigations of new technologies. The three technical issues identified in this report need to be discussed in greater depth with the aims of, first, clarifying the scope of the industry-wide alignment needed; second, prioritizing the issues requiring resolution; and, third, creating a plan to generate the necessary frameworks, practices, and protocols. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny. Click here to access the full SAE EDGETM Research Report portfolio.
Beiker, Sven
Eco-Driving Strategies for Different Powertrain Types and Scenarios2019-01-260810/22/2019
Connected automated vehicles (CAVs) are quickly becoming a reality, and their potential ability to communicate with each other and the infrastructure around them has big potential impacts on future mobility systems. Perhaps one of the most important impacts could be on network wide energy consumption. A lot of research has already been performed on the topic of eco-driving and the potential fuel and energy consumption benefits for CAVs. However, most of the efforts to date have been based on simulation studies only, and have only considered conventional vehicle powertrains. In this study, experimental data is presented for the potential eco-driving benefits of two specific intersection approach scenarios, for four different powertrain types. The two intersection approach scenarios considered in this study include an approach to a red light where coming to a complete stop is avoidable (short red light) and one where a complete stop is determined necessary (long red light) thanks to advance information from vehicle-to-infrastructure communication (V2I). The four powertrain types tested in this study include an advanced conventional vehicle, a conventional vehicle with idle stop-start capability, a hybrid electric vehicle (HEV), and a battery electric vehicle (BEV). The experimental results are compared to simulation results for the same intersection approach scenarios and eco-driving strategies, and show the difference in benefits for different powertrain types. Based on the eco-approach strategies for these two scenarios, a maximum fuel/energy consumption benefit of almost 8% was observed for the intersection with a short red light and almost 20% for the intersection with a long red light, in both cases by the HEV.
Iliev, SimeonRask, EricStutenberg, KevinDuoba, Michael
Test Methodology to Quantify and Analyze Energy Consumption of Connected and Automated Vehicles2019-01-01164/2/2019
A new generation of vehicle dynamics and powertrain control technologies are being developed to leverage information streams enabled via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connectivity [1, 2, 3, 4, 5]. While algorithms that use these connected information streams to enable improvements in energy efficiency are being studied in detail, methodologies to quantify and analyze these improvements on a vehicle have not yet been explored fully. A procedure to test and accurately measure energy-consumption benefits of a connected and automated vehicle (CAV) is presented. The first part of the test methodology enables testing in a controlled environment. A traffic simulator is built to model traffic flow in Fort Worth, Texas with sufficient accuracy. The benefits of a traffic simulator are two-fold: (1) generation of repeatable traffic scenarios and (2) evaluation of the robustness of control algorithms by introducing disturbances. The traffic simulator is interfaced with a chassis dynamometer on which the real vehicle will be tested. Algorithms leverage information from the traffic simulator to produce control policies that are optimal in energy consumption. The control policy results in a specific speed of the “ego” vehicle. This speed is relayed back to the traffic simulator, which coordinates movement of the vehicles surrounding the ego vehicle. The second part of the test methodology analyzes energy consumption improvements enabled via CAV technologies. It is expected that the energy consumption reduction realized on a vehicle will differ from simulation studies that rely on simplified models. An advanced instrumentation and measurement scheme enables in-situ efficiency calculations across the powertrain by analyzing energy flows during transient operation of the vehicle. Preliminary results from vehicle testing on a chassis dynamometer are presented.
Rengarajan, Sankar B.Hotz, ScottHirsch, CharlesLobato, PeterGross, MichaelSturgeon, PurserSarlashkar, Jayant
A Trajectory-Based Method for Scenario Analysis and Test Effort Reduction for Highly Automated Vehicle2019-01-01394/2/2019
Unlike the test of passive safety of traditional vehicles, highly automated vehicles (HAV) need more capabilities to be tested. Besides, there are more parameter combinations for the scenarios that need to be tested for each capability, resulting in a high time-consuming and costs for the autonomous vehicle tests. This paper proposes a method for scenario analysis and test effort reduction. Firstly, the trajectories of the vehicle under test (VUT) in the scenario are analyzed, and the trajectories which lead to the test mission failure are obtained. Based on the above trajectories, the threshold that lead to the test mission failure, or a combination of thresholds are analyzed. The above thresholds or a combination of thresholds values are defined as Scenario Character Parameter (SCP). The process of the analysis of the SCPs are related to the abilities of the HAV, but does not depend on the specific algorithm of the HAV. Therefore, through the above analysis of trajectories and SCPs, the ability of the scenario to measure the performance of HAVs can be quantized. After completing the analysis of scenarios that are used in HAVs evaluation, the SCPs corresponding to each scenario are obtained. The SCPs have the relationships such as overlapping or inclusive. Then, a set of scenarios with minimum number but still cover all SCPs can be searched. Use this set of scenarios to replace the original combination of test scenarios, the number of scenarios that need to be tested can be reduced. The method proposed in this paper reduces the amount of tests and costs for HAVs, which will be a promote to the development of the HAV technology.
Qi, YunlongLuo, YugongLi, KeqiangKong, WeiWang, Yongsheng
Effects of Innovation in Automated Vehicles on Occupant Compartment Designs, Evaluation, and Safety: A Review of Public Marketing, Literature, and Standards2019-01-12234/2/2019
In recent years, the discussion around the advent of highly automated vehicles has shifted from “if” to “when.” Commercially available vehicles already incorporate automated vehicle (AV) technologies of varying capability, and the eventual transition to fully automated systems, at least within certain predefined Operational Design Domains, is largely considered inevitable. While the full ramifications of this shift and the eventual depreciation of human driver control are still under intense debate, there is broad agreement on one issue -the advent of driverless systems will remove several constraints on the design of vehicle interior spaces, creating the opportunity for innovation. Even at this early stage, ambitious design concepts of purpose specific vehicles - mobile gyms, offices, bedrooms - have been proposed. More grounded designs, such as rotating passenger seats, have also been put forward. However, there are two other points on which general agreement exists - future AVs will still carry human passengers, and crashes will still occur, however infrequent or less severe. The uncertainty of the future occupant compartment design and crash population will introduce a new set of challenges for occupant protection and predicting injury risk in the future vehicle fleet. This paper explores various proposed design changes to the space of the interior of future automated vehicles, the effects of potential changes on occupant safety during collisions, and the capabilities of the existing testing approaches, design tools, and databases to address questions arising from these developments.
Filatov, AntonScanlon, John M.Bruno, AlexanderDanthurthi, Sri Sai KameshwariFisher, Jacob
Safety Argument Considerations for Public Road Testing of Autonomous Vehicles2019-01-01234/2/2019
Autonomous vehicle (AV) developers test extensively on public roads, potentially putting other road users at risk. A safety case for human supervision of road testing could improve safety transparency. A credible safety case should include: (1) the supervisor must be alert and able to respond to an autonomy failure in a timely manner, (2) the supervisor must adequately manage autonomy failures, and (3) the autonomy failure profile must be compatible with effective human supervision. Human supervisors and autonomous test vehicles form a combined human-autonomy system, with the total rate of observed failures including the product of the autonomy failure rate and the rate of unsuccessful failure mitigation by the supervisor. A difficulty is that human ability varies in a nonlinear way with autonomy failure rates, counter-intuitively making it more difficult for a supervisor to assure safety as autonomy maturity improves. Thus, road testing safety cases must account for both the expected failures during testing and the practical effectiveness of human supervisors given that failure profile. This paper outlines a high level safety case that identifies key factors for credibly arguing the safety of an on-road AV test program. A similar approach could be used to analyze potential safety issues for high capability semi-autonomous production vehicles.
Koopman, PhilipOsyk, Beth
Simulation and Its Contribution to Evaluate Highly Automated Driving Functions2019-01-01404/2/2019
A key criterion for launching autonomous vehicles on real roads is the knowledge of their capability to ensure traffic safety. In contrast to ADAS, deriving this measure of safety is difficult to achieve as the functional scope of an autonomous driving function exceeds by far the one of ADAS. As a consequence, real-world testing solely is not sufficient enough to cover the required test volume. This assessment problem imposes new requirements on a valid test concept for automated driving. A possible solution represents simulation by enabling it to generate reliable test kilometers. As a first step, we discuss in this paper the feasibility of simulation frameworks to re-simulate a real-world test in certain scenarios. We will demonstrate that even with ground truth information of the vehicle odometry and corresponding environment model an acceptable accordance of functional behavior is not guaranteed. Hence, to yield a reliable degree of confidence in a risk assessment a single scenario has to be represented by an ensemble generated from a local variation considering both, ground truth information and odometry including the environment model. In order to achieve these statements we first introduce a valid representation of traffic scenarios acting as a test case description for an autonomous driving function. Afterwards, the description based on the vehicle odometry and created environment model as well as the description based on the ground truth measured via Differential GPS are re-simulated using the same autonomous driving function as deployed in the test vehicle. The reprocessed traces are compared to the corresponding real-world data to illustrate resulting behavior changes in the autonomous driving function. To make the behavior changes interpretable for the assessment process a sensitive risk value is deployed containing information about the reprocessing quality of the chosen description and simulation.
Groh, KorbinianWagner, SebastianKuehbeck, ThomasKnoll, Alois
Analyze This! Sound Static Analysis for Integration Verification of Large-Scale Automotive Software2019-01-12464/2/2019
Safety-critical embedded software has to satisfy stringent quality requirements. One such requirement, imposed by all contemporary safety standards, is that no critical run-time errors must occur. Runtime errors can be caused by undefined or unspecified behavior of the programming language; examples are buffer overflows or data races. They may cause erroneous or erratic behavior, induce system failures, and constitute security vulnerabilities. A sound static analyzer reports all such defects in the code, or proves their absence. Sound static program analysis is a verification technique recommended by ISO/FDIS 26262 for software unit verification and for the verification of software integration. In this article we propose an analysis methodology that has been implemented with the static analyzer Astrée. It supports quick turn-around times and gives highly precise whole-program results. We give an overview of the key concepts of Astrée that enable it to efficiently handle large-scale code, and describe a pre-analysis which transforms the source code to make it better amenable to static analysis. The experimental results confirm that sound static analysis can be successfully applied for integration verification of large-scale automotive software.
Kaestner, DanielSchmidt, BernardSchlund, MaximilianMauborgne, LaurentWilhelm, StephanFerdinand, Christian
Virtual Traffic Simulator for Connected and Automated Vehicles2019-01-06764/2/2019
Connected and automated vehicle (CAV) technologies promise a substantial decrease in traffic accidents and traffic jams, and bring new opportunities for improving vehicle’s fuel economy. However, testing autonomous vehicles in a real world traffic environment is costly, and covering all corner cases is nearly impossible. Furthermore, it is very challenging to create a controlled real traffic environment that vehicle tests can be conducted repeatedly and compared fairly. With the capability of allowing testing more scenarios than those that would be possible with real world testing, simulations are deemed safer, more efficient, and more cost-effective. In this work, a full-scale simulation platform was developed to simulate the infrastructure, traffic, vehicle, powertrain, and their interactions. It is used as an effective tool to facilitate control algorithm development for improving CAV’s fuel economy in real world driving scenarios. The simulator integrates a 3D traffic model with a high-fidelity vehicle model using a modular architecture, which supports hardware-in-the-loop (HIL) and vehicle-in-the-loop (VIL) testing. Sensor models, perception module and manual/autonomous driving modules can be customized for the test vehicle. Smart and scalable traffic scenarios can be easily generated on the road network using statistically representative trip data. The design, implementation, and usage of the simulator will be described.
Zhao, JunfengWu, HaiChang, ChenFang
AD-EYE: A Co-Simulation Platform for Early Verification of Functional Safety Concepts2019-01-01264/2/2019
Automated Driving is revolutionizing many of the traditional ways of operation in the automotive industry. The impact on safety engineering of automotive functions is arguably one of the most important changes. There has been a need to re-think the impact of the partial or complete absence of the human driver (in terms of a supervisory entity) in not only newly developed functions but also in the qualification of the use of legacy functions in new contexts. The scope of the variety of scenarios that a vehicle may encounter even within a constrained Operational Design Domain, and the highly dynamic nature of Automated Driving, mean that new methods such as simulation can greatly aid the process of safety engineering. This paper discusses the need for early verification of the Functional Safety Concepts (FSCs), details the information typically available at this stage in the product lifecycle, and proposes a co-simulation platform named AD-EYE designed for exploiting the possibilities in an industrial context by evaluating design decisions and refining Functional Safety Requirements based on a reusable scenario database. Leveraging our prior experiences in developing FSCs for Automated Driving functions, and the preliminary implementation of co-simulation platform, we demonstrate the advantages and identify the limitations of using simulations for refinement and early FSC verification using examples of types of requirements that could benefit from our methodology.
Mohan, NaveenTörngren, Martin
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