Browse Topic: Driver behavior

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EVOLUTION OF 360 DEGREE LOCAL SITUATIONAL AWARENESS (LSA) TO AID THE WARFIGHTER2024-01-345111/15/2024
ABSTRACT Northrop Grumman has developed a software and hardware solution to provide enhanced 360 degree local situational awareness (LSA) to enable the warfighter with an overmatch capability on today’s modern battlefield. The architecture exploits technological gains in cameras, video processing, and video compression. The approach allows rapid comprehension of local and remote situational views presented with operational relevance for a ground combat platform or tactical wheeled platform crew. The 360 Degree LSA approach provides direct visualization of relative positioning of targets, threats, and lines of fire; and additionally offers common situational understanding / operational picture from the dismounted soldier to higher echelon commands. The approach provides prioritized information through LSA software to provide an enhanced view to the warfighter whereas the squad leader becomes an integral part of the crew with a view of the common operating picture (mounted) and additional sensors on tablet or handheld device (dismounted via wireless). The approach uses a platform agnostic form factor with components that can be selected and applied to legacy or new platforms based on their size, weight, power, and mission constraints.
Viscovich, Christopher, Geoghegan, Susan, Worthy, David
Engine-in-the-Loop Analysis of the Influence of Manual Gearshift Duration on Vehicle Consumption and Emissions15-16-01-00039/27/2022
Abstract The tightening of emission standards and homologation rules lead car manufacturers to rely on simulation testing in early development phases. Coupling an engine to a testbench controlled by a real-time simulation environment allows flexible, reliable, and reproducible testing for consumption and emission studies. However, interest in this method referred to as engine-in-the-loop (EiL) is relatively recent and few details can be found regarding the simulation environment. Following previous work, this study details a driver model based on the PI structure and augmented with preview and anti-windup. The focus is set on a conventional powertrain with a manual transmission for which the driver must also manage the clutch pedal during gearshift and take-off phases. Extended analysis of vehicle tests allows defining the driver’s behavior during these phases for different profiles. The driver model is then tested in the EiL environment and the impact of the gearshift profile on fuel consumption and pollutant emissions can be assessed. Besides the slight increase in fuel consumption, results show that increasing the gearshift duration degrades the regulation of the richness by the ECU, thus increasing CO engine-out emissions as well as decreasing NOx emissions. Finally, results suggest that a longer gearshift also affects the catalyst efficiency, which results in higher NOx tailpipe emissions.
Gilormini, Thomas, Chessé, Pascal, Tauzia, Xavier, Colin, Hervé
2.0.105 - Piston Sealing System Structure Design for Automobile's Lightweight Auto-TransmissionSAE-PP-004359/24/2021
Current automobile's auto-transmission has problems of defects and cost reduction because of welding process and very complicated assembly process due to individualized transmission piston and sealing components. Also, size and heavy weight of transmission piston components are the source of low mileage because they are made of aluminum, steel material. In this study, therefore, we perform structure design for piston sealing system which integrates piston and sealing material for automobile's lightweight auto-transmission. Also performed stress analysis through finite element analysis to secure required suitable strength when internal pressure is applied after assemble.
Mutagaana, Festo
0071 - Testing DownloadSAE-PP-004209/13/2021
The combustion occurring in an internal combustion engine subsequently emits high-intensity acoustic pulse along with exhaust gas flow. Formula SAE competition is imposing restrictions on acoustic emissions from an engine, which necessitates the activity of design and optimization of a high-performance muffler. The muffler has to be designed with the objectives of satisfying acoustic emission norms imposed and as well strategically designed to have less obstruction to exhaust flow and being lightweight to maintain the integrity of a Formula Student car. A novel approach of combining the effect of adsorptive and resonating muffler design has been inculcated in this work after the estimation of muffler size and resonance. The acoustic pressure analysis and exhaust flow efficiency are carried out using Ricardo WAVE. These simulation results are validated with the developed prototype. The developed prototype is ascertained to fulfil the requirement of acoustic emission norms (103 dB[C] - 110 dB[C]) without much compromise on exhaust flow efficiency. **testing**
SintzADMIN, Jeneane, SintzUSER, Jeneane, Anthony, Lindsay, Mutagaana, Festo, Mutz, Jennifer
Robust Behavioral Cloning for Autonomous Vehicles Using End-to-End Imitation Learning12-04-03-00238/19/2021
In this work, we present a lightweight pipeline for robust behavioral cloning of a human driver using end-to-end imitation learning. The proposed pipeline was employed to train and deploy three distinct driving behavior models onto a simulated vehicle. The training phase comprised of data collection, balancing, augmentation, preprocessing, and training a neural network, following which the trained model was deployed onto the ego vehicle to predict steering commands based on the feed from an onboard camera. A novel coupled control law was formulated to generate longitudinal control commands on the go based on the predicted steering angle and other parameters such as the actual speed of the ego vehicle and the prescribed constraints for speed and steering. We analyzed the computational efficiency of the pipeline and evaluated the robustness of the trained models through exhaustive experimentation during the deployment phase. We also compared our approach against state-of-the-art implementation in order to comment on its validity.
Samak, Tanmay Vilas, Samak, Chinmay Vilas, Kandhasamy, Sivanathan
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
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
rtyeuy testing testing testingSAE-PP-003593/3/2021
etyirui
SintzADMIN, Jeneane
workflow - take 2SAE-PP-003172/19/2021
workflow - take 2
2.0.116 - Emission Optimization Approach to Meet the Current Indian Emission Norm Without EGR Cooling for a Vehicle Equipped with Common Rail Diesel EngineSAE-PP-003142/19/2021
In India, diesel engine powered vehicles are finding rising demand due to the subsidy offered on diesel. Currently, BS-IV emission norm (equivalent to E-IV in Europe) is in existence. To meet this emission norm, OEM look for improved engine design, use of common rail injection system, advanced after treatment. In the current article, a methodology is demonstrated by which the required emissions on multipurpose vehicle (MPV) powered with 2.2L common rail injection system was met with no need of EGR cooling. This was achieved by identifying the operating points from the BS-IV emission cycle where EGR cooling is beneficial. The next step involves assessing the loss of function due to its removal. The final step involves strategies which can bring the original optimized value of NOx-PM. Removal of EGR cooling avoids the cooling of intake charge and reduces the HC and CO emission. Also, it gets rid of complication in the under bonnet packaging and leads to maintenance free operation. This resulted in overall reduction of the precious metal loading on the catalytic convertor by 50% from its value in the production. Thus, the overall cost saving of 3.5% of the total engine cost was achieved without losing the functional requirement.
Mutagaana, Festo
testing rc-2255SAE-PP-003132/19/2021
testing rc-2255
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, Jeneane, Anthony, 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
6.0.104 - Warm Forming of 3t Mg Alloy Sheet for An Automotive Electronic Compressor CaseSAE-PP-002602/4/2021
Recently, the applications of magnesium alloy to automobile and electric parts have been increased because of its high specific strength, excellent machinability, high electrical and thermal conductivity. The efforts of automobile industry to reduce fuel consumption by using lightweight structural materials have accelerated the deep drawing technology of magnesium alloy sheet. In the present study, the basic study to fabricate an automotive compressor case have been carried out. In order to apply ductile fracture criterion to predict the forming failure, critical damage values were determined from uniaxial tensile tests and FE simulations, and then they were expressed as the function of strain rate and temperature. The proposed methodology was applied to design the deep drawing process for fabrication of magnesium automotive compressor case without any defect. Based on the simulation and experimental results, AZ31 EL-cover part 39% lighter than ADC12 die casting EL-cover could be fabricated by warm deep drawing process.
Mutagaana, Festo
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
1.1.204 - Cost Effective Emergency Intimation System Design for AutomobilesSAE-PP-002192/2/2021
The death toll due to traffic accidents in India is on a rise, according to the latest Road Transport ministry report, a total of 4.97 lakh road accident was reported in 2011. Though compared to 2010, the accidents have gone down by 1,945, the number of deaths at 1,42,485 has increased by over 7,000.[1] This paper proposes a design of an Emergency Intimation System (EIS) tailored to fit for Indian consumer needs and available infrastructure. EIS is an emergency alert technology devised to assist drivers and passenger in an event of vehicle crash. Majority of deaths are caused by slow accident response time. EIS is aimed to lower this response time and ensure that the required rescue and medical services are made available in time. This device employed to make this emergency alerts will be fitted into the vehicle Electrical and Electronics (E/E) architecture and will have interfaces with crash sensor network, CAN network and GSM etc. In an event of crash, this device shall send an SMS to In Case of Emergency contacts identified by the vehicle owner. The SMS shall comprise of information like location (Vehicle co-ordinates), airbag deployment status and time stamp (Minimum Set of Data).
Mutagaana, Festo
050 - Diesel Combustion Characteristics of Coconut Oil Ester FuelsSAE-PP-001881/30/2021
In order to improve the cold flow properties of coconut oil biodiesel and to reduce the lifecycle CO2 emission by using bio-alcohol at biodiesel manufacturing, varying the types of alcohol used at transesterification was examined. The pour point of coconut oil ester decreases as the carbon number of alcohol increases. Among 5 ester fuels, the pour point of coconut oil isobutyl ester (CiBE) made from isobutanol is lowest, −12.5 °C, compared to that of coconut oil methyl ester (CME), highest, −5 °C. The pour point of coconut oil 1-butyl ester (CBE) is −10 °C, second lowest. Furthermore, CBE, CiBE, CME and JIS No.2 diesel fuel (gas oil) were tested using a DI diesel engine. CBE and CiBE have shorter ignition delay compared to the gas oil although slightly longer than CME. CBE and CiBE have the same thermal efficiency and NOx emissions compared to the gas oil. HC, CO and Smoke emissions of coconut oil ester fuels slightly increase when the ester molecule carbon number increases. However, these exhaust emissions are lower than that of the gas oil. From the experimental results, it is concluded that CBE and CiBE are good alternative diesel fuels.
Mutagaana, Festo
Breath-Based Alcohol Detection SystemJ3214_202101 (Historical)1/27/2021
This standard establishes the performance specifications for the zero-tolerance breath alcohol detection system to reduce the risks of driving under the influence of alcohol. It defines the accuracy and precision requirements of the BrAC measurement, as well as the acceptability criteria and key parameters to test these requirements. Additionally, this standard sets the performance requirements of the system for ethanol sensitivity, the response time, and the electrical, mechanical, and environmental conditions the system may encounter throughout the lifespan of the vehicle.
Driver Alcohol Detection System for Safety Committee
Driver Drowsiness and Fatigue in the Safe Operation of Vehicles - Definition of Terms and ConceptsJ3198_202010 (Current)10/26/2020
This SAE Information Report provides definitions and discussions of key terms concerning driver drowsiness and fatigue, and basic information on measuring drowsiness and fatigue. It also includes information and concepts for driver drowsiness as they relate to the safe operation of a vehicle. The key driver drowsiness and fatigue causal factors include the following: (1) sleep quality and quantity, (2) time of day, (3) time awake, (4) time on task (modulated by characteristics of the driving task), (5) task-related fatigue (variations of arousal levels related to task underload and overload), and (6) combinations of these factors. Medical conditions, medication, alcohol, or drugs exacerbate drowsiness; however, the discussion in this report is limited to fatigue concepts. This report has two primary outputs: (1) definitions and discussions of key terms concerning driver drowsiness and fatigue, and (2) basic information on measuring drowsiness and fatigue and its effects on the safe operation of a vehicle. These include the physiological and cognitive effects of driver drowsiness and fatigue on driving safety. Examples of effect of driver drowsiness and fatigue on driving safety include those related to vehicle control, operator vigilance (sustained attention), reaction times (object and event detection and response), situational awareness, physiological indicators, subjective assessments, and combinations thereof. For definitions of driving performance measures, refer to SAE J2944. This report applies to all worldwide motor vehicle passenger cars and light trucks, as well as heavy trucks, buses, motorcycles, and mopeds. The intended users of the document are practitioners and researchers in the automotive industry, academia, and other organizations with interest in driver drowsiness and fatigue, driving and driver performance assessment, and road safety.
Driver Metrics, Performance, Behaviors and States Committee
Comparative Analysis of Emergency Evasive Steering for Long Combination Vehicles02-13-03-001810/10/2020
This study provides a simulation-based comparative analysis of the distance and time needed for long combination vehicles (LCVs) - namely, A-doubles with 28-, 33-, and 48-ft trailers - to safely exercise an emergency, evasive steering maneuver such as required for obstacle avoidance. The results are also compared with conventional tractor-semitrailers with a single 53-ft trailer. A multi-body dynamic model for each vehicle combination is developed in TruckSim® with an attempt to assess the last point to steer (LPTS) and evasive time (ET) at various highway speeds under both dry and wet road conditions. The results indicate that the minimum avoidance distance and time required for the 28-ft doubles vary from 206 ft (60 mph) to 312 ft (80 mph) and 2.3 s to 2.6 s, respectively. The required LPTS represents a 6% to 31% increase when compared with 53-ft semitrucks. When driving below 76 mph on a dry road and below 75 mph on a wet road, the 28-ft doubles exhibit LPTS and ET that are larger than 33-ft doubles. In addition, the 33-ft doubles exhibit larger LPTS and ET than 48-ft doubles for the highway speeds considered. This is mainly attributed to the longer trailer wheelbase that causes smaller rear trailer amplifications. At speeds higher than 76 mph on dry roads and 75 mph on wet roads, however, an opposite trend is observed. As the trailer length increases, the distance and time needed to safely avoid an obstacle also increase. A comparison between dry and wet road conditions is also conducted, with the results indicating that more time and distance would be needed for obstacle avoidance on wet roads.
Chen, Yang, Zhang, Zichen, Ahmadian, Mehdi
Low Mu/Winter Driving Skill CertificationJ3300/1_202008 (Current)8/12/2020
This SAE Recommended Practice is intended to establish a procedure to certify the low mu/winter driving skill levels of professional drivers. This certification can be used by the individual driver to qualify their skills when seeking employment or other professional activity. These certification levels may also be used by test facilities or other organizations when seeking test or professional drivers of various skills. This document provides directions for obtaining certification through Probitas Authentication®1, and the low mu/winter driving skill examination requirements. This document is a supplement to SAE J3300, providing information specific to the low mu/winter driving skill certification and clarifying the application of the rules set forth in J3300 to the low mu/winter driving certification. While the references, definitions, rules, and guidelines presented in SAE J3300 Sections 1 through 5 apply to the low mu/winter driving certification, they are not repeated in this document.
Driving Skills Standards Committee
Development of Design and Engineering Recommendations for In-Vehicle Alphanumeric MessagesJ2831_202007 (Current)7/29/2020
This Information Report provides recommendations for alphanumeric messages that are supplied to the vehicle by external (e.g., RDS, satellite radio) or internal (e.g., infotainment system) sources while the vehicle is in-motion. Information/design recommendations contained in this report apply to OEM (embedded) and aftermarket systems. Ergonomic issues with regard to display characteristics (e.g., viewing angle, brightness, contrast, font design, etc.) should review ISO 15008.
Driver Vehicle Interface (DVI) Committee
AVSC Best Practice for Passenger-Initiated Emergency Trip InterruptionAVSC000032020066/30/2020
As passengers take rides in fleet-managed automated driving system-dedicated vehicles (ADS-DVs), they may feel the need to interrupt the trip due to a perceived emergency. There is currently no industry consensus on the proper balance between ADS passenger agency and the potential for introducing unexpected outcomes in dynamic traffic environments. In order to build public trust in automated vehicles, passengers should be given an option to exercise some type of control (agency) to intervene during situations they perceive as emergencies. Passenger-initiated emergency trip interruption features — however they manifest in a given vehicle - can help establish this confidence in ADS technologies. AVSC Best Practice for Passenger-Initiated Emergency Trip Interruption recommends processes surrounding aspects of passenger-initiated features in SAE level 4 and 5 fleet-managed ADS-DVs. It recommends criteria and processes for passenger initiation of these features from inside the vehicle; communication with passengers and fleet operations; enhanced diagnoses of the situation, interaction outside the vehicle with other road users, and general post-stop actions. Also, precautions against some types of foreseeable misuse are addressed. These recommendations apply to commercially available, deployed ADS-DV’s providing trips to people. The AVSC recommends that every fleet-managed SAE level 4 and 5 ADS-DV be equipped with a (PES) or (PEC) or both.
Automated Vehicle Safety Consortium
Control Model of Automated Driving Systems Based on SOTIF Evaluation2020-01-12144/14/2020
In partially automated and conditionally automated vehicles, a part of the work of human drivers is replaced by the system, and the main source of safety risks is no longer system failures, but non-failure risks caused by insufficient system function design. The absence of unreasonable risk due to hazards resulting from functional insufficiencies of the intended functionality or by reasonably foreseeable misuse by persons, is referred to as the Safety Of The Intended Functionality. Drivers have the responsibility to supervise the automated driving system. When they don't agree with the operation behavior of the system, they will interfere with the instructions. However, this may lead to potential risks. In order to discover the causes of human misuse, this paper takes the trust feeling between the driver and the automated driving system as the starting point, and based on the collected data of track test, establishes the evaluation indicator -- degree of confidence to show the trust feeling between the driver and the automated system. Degree of confidence is a comprehensive interpretation of the driver's physical and psychological feelings. In the process of track test, we simultaneously collect the dynamics indicators of the vehicle. After the test, the drivers' driving feeling was evaluated by questionnaire. Then, the relationship between objective indicator and subjective score was established by machine learning method, and the development of evaluation indicator was completed. Finally, this paper optimizes the automatic driving motion planning algorithm based on this indicator, and verifies the effectiveness of the algorithm through simulation.
Guo, Mengge, Shang, Shiliang, Haifeng, Cui, Zhang, Kaijiong, Deng, Weishun, Zhang, Xi, Yu, Fan
Research on AEB Collision Avoidance Strategy Based on Characteristics of Driver-Vehicle-Road2020-01-12134/14/2020
With the rise of intelligent transportation systems around the world, research on automobile active safety technology has gained widespread attention. Autonomous Emergency Braking (AEB) which can avoid or mitigate collision by active braking has become a hot research topic in the field of automobile. However, there are some limitations in the present AEB collision avoidance strategy, including lack of effective identification of road adhesion conditions, mismatch of active braking system parameters and imperfection of target vehicle motion information, which leads to poor collision avoidance performance on low adhesion coefficient road surface and intervention with the normal driving operation of the driver. A new collision avoidance strategy for AEB is proposed in this paper. Firstly, a new safe distance collision avoidance model is established based on the peak adhesion coefficient in real time, the performance parameters of the active braking system and the motion information of the target vehicle. Secondly, under the premise of not interfering with the driver's normal collision avoidance operation, an AEB collision avoidance strategy that can balance vehicle safety and intervention comfort is proposed. Finally, the C-NCAP scenario test is carried out on the hardware-in-loop test environment. The results show that the AEB collision avoidance strategy proposed in this paper can actively adjust the braking moment according to the current road surface attachment condition. The collision avoidance can be achieved in the most test scenarios, and the minimum distance between the self-vehicle and the target vehicle is less than 1.5 meter. In the few test scenarios, the collision can also occur at a relative speed lower than 4.2 km/h, which satisfies the active avoidance of the vehicle.
He, Ren, Zhang, Dong
Development of a Camera-Based Driver State Monitoring System for Cost-Effective Embedded Solution2020-01-12104/14/2020
To prevent the severe consequences of unsafe driving behaviors, it is crucial to monitor and analyze the state of the driver. Developing an effective driver state monitoring (DSM) systems is particularly challenging due to limited computation capabilities of embedded systems in automobiles and the need for finishing processing in real-time. However, most of the existing research work was conducted in a lab environment with expensive equipment while lacking in-car benchmarking and validation. In this paper, a DSM system that estimates driver's alertness and drowsiness level as well as performs emotion detection built with a cost-effective embedded system is presented. The proposed system consists of a mono camera that captures driver's facial image in real-time and a machine learning based detection algorithm that detects facial landmark points and use that information to infer driver's state. In the detection module, driver's distraction level is evaluated by estimating head-pose through solving a perspective-n-point problem, drowsiness level is estimated by processing eyelid related parameters extracted from facial keypoints data, and machine learning approach was used for emotion state monitoring. It is discovered for emotion recognition that using multilayer perceptron (MLP) network reached the accuracy of 93% on DISFA (Denver Intensity of Spontaneous Facial Action) dataset when combined with Action Units (AU) analysis. The performance of the developed DSM system has been verified in both laboratory and in-vehicle condition, and the experimental results showed its effectiveness in both normal and low lighting conditions. Moreover, the performance of the developed algorithm using commercially available low-cost cameras as well as memory and processing speed analysis considering the required embedded system design has also been examined.
Zhou, Xunfei, Wingert, Tobias, Sauer, Maximilian, Kundu, Subrata
Driver Drowsiness Behavior Detection and Analysis Using Vision-Based Multimodal Features for Driving Safety2020-01-12114/14/2020
Driving inattention caused by drowsiness has been a significant reason for vehicle crash accidents, and there is a critical need to augment driving safety by monitoring driver drowsiness behaviors. For real-time drowsy driving awareness, we propose a vision-based driver drowsiness monitoring system (DDMS) for driver drowsiness behavior recognition and analysis. First, an infrared camera is deployed in-vehicle to capture the driver’s facial and head information in naturalistic driving scenarios, in which the driver may or may not wear glasses or sunglasses. Second, we propose and design a multi-modal features representation approach based on facial landmarks, and head pose which is retrieved in a convolutional neural network (CNN) regression model. Finally, an extreme learning machine (ELM) model is proposed to fuse the facial landmark, recognition model and pose orientation for drowsiness detection. The DDMS gives promptly warning to the driver once a drowsiness event is detected. The proposed CNN and ELM models are trained in a drowsy driving dataset and are validated on public datasets and field tests. Comparing to the end-to-end CNN recognition model, the proposed multi-modal fusion with the ELM detection model allows faster and more accurate detection with minimal intervention. The experimental result demonstrates that DDMS is able to provide real-time and effective drowsy driving alerts under various light conditions to augment driving safety.
Li, Rui, Brand, Howard, Gopinath, Aditya, Kamarajugadda, Srivatsav, Yang, Liang, Wang, Weitian, Li, Bing
A Study of Driver's Driving Concentration Based on Computer Vision Technology2020-01-05724/14/2020
Driving safety is an eternal theme of the transportation industry. In recent years, with the rapid growth of car ownership, traffic accidents have become more frequent, and the harm it brings to human society has become increasingly serious. In this context, car safety assisted driving technology has received widespread attention. As an effective means to reduce traffic accidents and reduce accident losses, it has become the research frontier in the field of traffic engineering and represents the trend of future vehicle development. However, there are still many technical problems that need to be solved. With the continuous development of computer vision technology, face detection technology has become more and more mature, and applications have become more and more extensive. This article will use the face detection technology to detect the driver's face, and then analyze the changes in driver's driving focus. Firstly, the problem of detecting the eyes and mouth status of the driver is discussed. The purpose is to capture the driver's long-term closed eyes and yawning and other actions closely related to the dozing behavior. Secondly, the problem of estimating the driver's head posture is studied. The purpose is to capture the abnormal movements of the driver's long bow, head up or frequent nodding. The study consists of three parts: detection of facial feature points, estimation of the head posture based on the feature points, and definition of fatigue characteristics. The experimental results show that the method in this paper is not only easy to operate but also has a high accuracy rate for the detection of driver concentration.
Lin, Guan, Zhan, Zhenfei, Peng, Xiangjun, Xu, Huijie, Fu, Yue, Jiang, Ling
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, Steven, Seppelt, Bobbie, Russo, Luca, Mehler, Bruce, Angell, Linda, Gershon, Pnina, Reimer, Bryan
A Novel Velocity Planner for Autonomous Vehicle Considering Human Driver’s Habits2020-01-01334/14/2020
In automatic driving application, the velocity planner can be considered as a key factor to ensure the safety and comfort. One of the most important tasks of the velocity planner is to simulate the velocity characteristics of human drivers. In this paper, two Driver In-the-Loop (DIL) experiments are designed to explain velocity characteristics of human drivers. In the first experiment, static obstacles are placed on both sides of the straight road to shorten the cross range that vehicles can driver across. Moreover, different cross ranges are set to study the influence of the steering wheel error. In the second experiment, velocity characteristics are investigated under the condition of different road widths and curvatures in a U-turn road contour. In both tests, different drivers’ preview behavior is analyzed through the operation of throttle, braking, and steering. From the results we could see the change of vehicle speed depends largely on the traffic environment at the driver’s preview point. On this basis, a novel velocity planner is proposed. Firstly, a target velocity in preview terminal point is calculated. The calculation of the velocity is based on two indicators-the driver’s driving & operating ability, and the degree of visual restriction. The former refers to the ability of the driver to maintain the driveway as well as the control ability of the vehicle stability, and the latter is related to the uncertainty of the environment. Subsequently, the smooth velocity profiles that connect the initial point and the preview terminal point are generated based on the convex optimization. Finally, the simulation results show that this velocity planner possesses good human-like performance, considering the human-vehicle-road coordination. This study is useful to customize velocity planning for autonomous vehicle so as to improve the acceptability of the specific human driver.
Cui, Zongwei, Guo, Xuexun, Pei, Xiaofei
Decision Making and Trajectory Planning of Intelligent Vehicle’ s Lane-Changing Behavior on Highways under Multi-Objective Constrains2020-01-01244/14/2020
Discretionary lane changing is commonly seen in highway driving. Intelligent vehicles are expected to change lanes discretionarily for better driving experience and higher traffic efficiency. This study proposed to optimize the decision-making and trajectory-planning process so that intelligent vehicles made lane changes not only with driving safety taken into account, but also with the goal to improve driving comfort as well as to meet the driver’ s expectation. The mechanism of how various factors contribute to the driver’s intention to change lanes was studied by carrying out a series of driving simulation experiments, and a Lane-Changing Intention Generation (LCIG) model based on Bi-directional Long Short-Term Memory (Bi-LSTM) was proposed. The inputs of the Bi-LSTM were data fragments of several influencing factors including the relative velocity and the distance between the relative vehicles, the type of the preceding vehicles, and the average velocity of the adjacent traffic flows, that over a certain period of time, which was determined via examining subjects’ visual behaviors of the left view mirror or the right view mirror. By combining the LCIG model with a feasibility judgement model which was based on minimum safety spacing (MSS), a lane-changing decision-making model satisfying driving safety and drivers’ expectation was proposed. The model was trained with a part of trajectory dataset obtained from the simulation driving experiments. The jerk was taken into full consideration as boundary condition on the basis of seventh-degree polynomial trajectory planning. The proposed decision-making model were verified against a test dataset from the other parts of experimental data and the results show that the model resembles the lane-changing decision-making process of human drivers in real-world.
Nie, Linzhen, Yin, Zhishuai, Huang, Haoran
Simulation of Curved Road Collision Prevention Warning System of Automobile Based on V2X2020-01-07074/14/2020
The high popularity of automobiles has led to frequent collisions. According to the latest statistics of the United Nations, about 1.25 million people worldwide die from road traffic accidents each year. In order to improve the safety of vehicles in driving, the active safety system has become a research hotspot of various car companies and research institutions around the world. Among them, the more mature and popular active security system are Forward Collision Warning(FCW) and Autonomous Emergency Braking(AEB). However, the current active safety system is based on traditional sensors such as radar and camera. Therefore, the system itself has many limitations due to the shortage of traditional sensors. Compared to traditional sensors, Vehicle to Everything (V2X) technology has the advantages of richer vehicle parameter information, no perceived blind spots, dynamic prediction of dangerous vehicle status, and no occlusion restriction. In order to overcome the many shortcomings of the existing anti-collision warning system and strategy, this paper proposes a curved road collision prevention warning strategy based on V2X technology. Through V2X technology, the state information released by the neighboring car and the road environment information issued by the roadside unit are obtained. Using the above information and the state information of the vehicle, the relative positional relationship between the car and the neighboring car is dynamically predicted in real time, and then a two-degree-of-freedom dynamic collision time model and a two-degree-of-freedom collision time threshold model are proposed and designed. Finally, based on the output parameters of the above model, a two-degree-of-freedom curved road collision prevention warning system of automobile based on V2X technology is proposed, and a layered early warning mechanism is established. Through the PreScan environment, the typical working conditions and early warning strategy models are built by Matlab & Simulink, and the simulation of the early warning strategy is completed.
Li, Xuanhe, Wu, Jian, He, Rui, Zhu, Bing, Zhao, Jian, Zhou, Hang
Evaluation of Methods for Identification of Driving Styles and Simulation-Based Analysis of their Influence on Energy Consumption on the Example of a Hybrid Drive Train2020-01-04434/14/2020
Due to current progresses in the field of driver assistance systems and the continuously growing electrification of vehicle drive trains, the evaluation of driver behavior has become an important part in the development process of modern cars. Findings from driver analyses are used for the creation of individual profiles, which can be permanently adapted due to ongoing data processing. A benefit of data-based dynamic control systems lies in the possibility to individually configure the vehicle behavior for a specific driver, which can contribute to increasing customer acceptance and satisfaction. In this way, an optimization of the control behavior between driver and vehicle and the resulting mutual system learning and -adjustment hold great potential for improvements in driving behavior, safety and energy consumption. The submitted paper deals with the analysis of different methods and measurement systems for the identification and classification of driver profiles as well as with their potential to optimize both vehicle driving behavior and energy consumption on the example of a hybrid drive train. A literature research results in a number of different approaches of evaluation, which are analyzed, linked and adapted in the publication. As a result, an evaluation of the connection between different methods of driver profile determination is given. Data collection and interviews have been performed during twenty test drives on a defined route profile with different measurement systems and methods. The acquired data form the basis for a comparison and an analysis of a comprehensive driving style classification. Subsequently, a framework for computer-aided investigations of the influences of driver behavior on the control of drive trains is established by use of an existed simulation model of a hybrid drive train. Finally, a driver model is implemented based on the learnings out of analyzing the measurements and surveys. The evaluation of the measurement campaigns delivers detailed information about vehicle longitudinal acceleration behavior in different driving scenarios. This information is used to classify the individual driving styles into the types calm, normal and aggressive. This driving style-related information can be integrated into the control strategy of a hybrid power train to support operation strategy optimization regarding both driver satisfaction and reduction of energy-, respectively fuel consumption.
Domijanic, Marko, Hirz, Mario, Pucher, Gregor
What If the Speed Had Been Less? Causation in Time Limited and Distance Limited Hazards2020-01-08814/14/2020
With a path intrusion incident, it is almost always the case that the collision would have been avoided if the pedestrian had not run out, or if the vehicle on the minor road had stopped, or so on. However should the other party be thought to have been travelling at an excessive speed, often the reconstructionist is asked to make a calculation of what whether the collision would, at some alternative speed say equal to the speed limit, still have occurred. In that way causation is addressed. The paper distinguishes between those hazards which are distance limited and those which are time limited, giving definitions of the two types. Distance limited hazards are deterministic, but time limited hazards have a probabilistic basis. This difference has important implications for causation. For a hazard at a fixed distance, there is a well known formula for calculating whether the collision would have been avoided at a slower alternative speed. However a time limited hazard often has no clear cut boundary between avoided/not avoided. According to the warning time during which the hazard develops, the alternative speed of the vehicle may mean that a collision would certainly be avoided, the alternative speed may have no effect, or the effect of the alternative speed may be in between. A method is given for estimating the effect of a slower speed. A further type of path intrusion is where the pedestrian, or driver on a minor road, has seen the oncoming vehicle but gauged that there was time to cross in front of it. This also is considered, with its implications for causation. Traffic lights, where one must not go over on red, have similarities and differences with path intrusion incidents. The paper gives a formula for the maximum speed at which a traffic light might be approached if drivers made the best choices, with a discussion of the difference between the unrealistic result of this calculation and a realistic maximum.
Searle, John
An Improved Probabilistic Threat Assessment Method for Intelligent Vehicles in Critical Rear-End Situations2020-01-06984/14/2020
Threat assessment (TA) method is vital in the decision-making process of intelligent vehicles (IVs), especially for ADAS systems. In the research of TA, the probabilistic threat assessment (PTA) method is acting an increasing role, which can reduce the uncertainties of driver’s maneuvers. However, the driver behavior model (DBM) used in present PTA methods was mainly constructed by limited data or simple functions, which is not entirely reasonable and may affect the performance of the TA process. This work aims to utilize crash data extracted from Event Data Recorder (EDR) to establish more accurate DBM and improve the current PTA method in rear-end situations. EDR data with responsive maneuvers were firstly collected, which were then employed to construct the initial DBM (I-DBM) model by using the multivariate Gaussian distribution (MGD) framework. Besides, the model was further subdivided into six parts by two important risk indicators, Time-to-collision (TTC) and velocity. To accurately represent the driver’s maneuvers in critical situations, unresponsive samples were introduced and the I-DBMs were upgraded by the Gaussian mixture model (GMM). The obtained DBMs were employed to sample driver’s evasive behaviors by Monte Carlo Markov Chain (MCMC) method, which generated multiple collision-avoidance trajectories. Finally, we chose the real-world crash case in the SHRP2 dataset to verify the proposed method. Results show that the upgraded DBMs reasonably represented the driver’s evasive maneuvers, and the MCMC method could capture the main features of given GMM distributions. The proposed PTA method can accurately depict the changing trend of dangerous degree and derive the crash probability (CP) at critical point of time. Its effectiveness and real-time performance were verified in the chosen rear-end case. The improved PTA method can be used for real-time TA application and contribute to the development of the decision-making process for ADAS and IVs.
Zhou, Huajian, Zhong, Zhihua, Wang, Xiaowei, Huang, Jin
Vehicle Safe-Mode, Concept to Practice Limp-Mode in the Service of Cybersecurity11-02-02-00062/27/2020
This article describes both a concept and an implementation of vehicle safe-mode (VSM) - a mechanism that may help reduce the damage of an identified cyberattack to the vehicle, its driver, the passengers, and its surroundings. Unlike other defense mechanisms that try to block the attack or simply notify of its existence, the VSM mechanism responds to a detected intrusion by limiting the vehicle’s functionality to safe operations and optionally activating additional security countermeasures. This is done by adopting ideas from the existing mechanism of Limp-mode that was originally designed to limit the damage of a mechanical, or an electrical, malfunction and let the vehicle “limp back home” in safety. Like Limp-mode, the purpose of safe-mode is to limit the vehicle from performing certain functions when conditions arise that could render full operation dangerous: Detecting a malfunction in the Limp-mode case is analogous to detecting an active cybersecurity breach in the safe-mode case, and the reactions should be analogous as well. We demonstrate that the VSM can be implemented, possibly even as an aftermarket add-on: to do so we developed a proof-of-concept (PoC) system and actively tested it in real time on an operating vehicle. Once activated, our VSM system restricts the vehicle to Limp-mode behavior by guiding it to remain in low gear, taking into account the vehicle’s speed and the driver’s actions. Our system does not require any changes to the electronic control units (ECUs), or to any other part of the vehicle, beyond connecting the safe-mode manager (SMManager) to the correct bus. We note that our system can rely upon any deployed anomaly-detection system to identify the potential attack. We point out that restricting the vehicle to Limp-mode-like behavior by an aftermarket system is just an example. If a car manufacturer would integrate such a system into a vehicle, they would have many more options, and the resulting system would probably be safer and with a better human-machine interface.
Dagan, Tsvika, Montvelisky, Yuval, Marchetti, Mirco, Stabili, Dario, Colajanni, Michele, Wool, Avishai
Influence Analysis of AEB Two-Wheeler on Passenger Car Impact Two-Wheeler Traffic Accidents in China2020-01-50232/24/2020
AEB two-wheeler system is an active safety technology which developed for avoiding two-wheeler accidents. With a large number of two wheelers, China needs to conduct research and analysis of this system. In this paper, real traffic accident data in China are used to analyze the possible influence of AEB two-wheeler system on traffic accidents. The paper chooses real passenger car impact two wheeler accidents happen in China, and gets the characteristics of data analysis. Then the paper analysis the influence of AEB system using position data when TTC=3s. According to the analysis, the detection range of 90 meters and the detection angle of 45 degrees can improve the recognition rate of day crossing accident by 17.7%, night crossing accident by 21.5% and longitudinal accident by 38.8%. The paper provides effective support for the development and test of AEB two-wheeler system in China. Car-to-two-wheeler accident AEB two-wheeler system Influence of the accident
Xudong, Li, Xiaowei, Lian, Xingchang, Wang
Takeover Level of Autonomous Vehicle Based on Driver’s Neuromuscular Characteristic2020-01-50172/24/2020
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, Wei, Yanhong, Wu, Yuxuan, Zhang, Rui, Xu
Breathalyzer Detects MarijuanaTBMG-359712/1/2020
As recreational marijuana legalization becomes more widespread in the U.S., so has concern about what that means for enforcing driving-under-the-influence (DUI) laws. Unlike a breathalyzer used to detect alcohol, police do not have a device that can be used in the field to determine if a driver is under the influence of marijuana.
Tier 1s tout newest mobility tech at CES 202020AUTP02_091/1/2020
The mammoth annual techfest formerly known as the Consumer Electronics Show has become a must-attend for the mobility industry, with dozens of displays by OEMs and suppliers of all dimensions. At this year's CES, Automotive Engineering was impressed by new developments in ADAS and AV sensing and processing, V2X connectivity, vehicle cabin sensing and related technologies, electrification advances and a number of vehicle introductions. Highlights of our reporting include:
Brooke, Lindsay
A Personalized Lane-Changing Model for Advanced Driver Assistance System Based on Deep Learning and Spatial-Temporal Modeling09-07-02-000911/14/2019
Lane changes are stressful maneuvers for drivers, particularly during high-speed traffic flows. However, modeling driver’s lane-changing decision and implementation process is challenging due to the complexity and uncertainty of driving behaviors. To address this issue, this article presents a personalized Lane-Changing Model (LCM) for Advanced Driver Assistance System (ADAS) based on deep learning method. The LCM contains three major computational components. Firstly, with abundant inputs of Root Residual Network (Root-ResNet), LCM is able to exploit more local information from the front view video data. Secondly, the LCM has an ability of learning the global spatial-temporal information via Temporal Modeling Blocks (TMBs). Finally, a two-layer Long Short-Term Memory (LSTM) network is used to learn video contextual features combined with lane boundary based distance features in lane change events. The experimental results on a -world driving dataset show that the LCM is capable of learning the latent features of lane-changing behaviors and achieving significantly better performance than other prevalent models.
Gao, Jun, Yi, Jiangang, Zhu, Honghui, Murphey, Yi Lu
Unsettled Topics Concerning Automated Driving Systems and the Transportation EcosystemEPR201900511/5/2019
Over the last 100 years, the automobile has become integrated in a fundamental way into the broader economy. A broad and deep ecosystem has emerged, and critical components of this ecosystem include insurance, after-market services, automobile retail sales, automobile lending, energy suppliers (e.g., gas stations), medical services, advertising, lawyers, banking, public planners, and law enforcement. These components - which together represent almost $2 trillion of the U.S. economy - are in equilibrium based on the current capabilities of automotive technology. However, the advent of autonomous vehicles (AVs) and technologies like electrification have the potential to significantly disrupt the automotive ecosystem. The critical cog governing the rate and pace of this shift is the management of the test and verification of AVs. In this SAE EDGE™ report, six senior industry leaders in the impacted ecosystems essay articles which describe sectors of the current automotive ecosystem and the manner in which AV technology can potentially reshape them - providing a mosaic of the massive infrastructure shifts which will be required to absorb AV technologies. 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.
Razdan, Rahul
Research on Control Algorithm of Active Steering Control Based on the Driver Intention2019-01-506411/4/2019
Active steering technology can improve the operability of the driver by the involvement to the steering system. Driver is the major controller of the vehicle Therefore, the involvement of advanced technologies including the active steering technology shouldn’t interfere with the intention of the driver, and the driver should still have great control of the vehicle. The aim of this paper is to solve the problem of the driver’s control when the active steering system works to improve the flexibility of the low speed and the stability of the high speed, and the active steering model based on the driver’s steering intention is established. Through the CarSim simulation software, this paper adopts 9 parameters related to the vehicle steering of the DLC (Double Line Change). And PCA (Principal Component Analysis) algorithm, a tool of statistical analysis, is applied to select 4 parameters which can stand for the DLC from the 9 parameters, which makes the data processing easier. Through the 4 parameters, this model divide the driver’s steering intention into four categories (emergency steering, normal steering, turn left and turn right) having different weights of active steering angle by clustering analysis, which ensures the driver get better control to the vehicle than traditional active steering system at different steering conditions. Finally, the feasibility of this model is verified by the simulation results through the comparison with the curve of the ideal steering at DLC steering condition.
Zhang, Pengcheng, Zheng, Hongyu
Analysis of the Driver’s Breaking Response in the Safety Cut-in Scenario Based on Naturalistic Driving2019-01-505311/4/2019
For the personification of automotive vehicle function performance under common traffic scenarios, analysis of human driver behavior is necessary. Based on China Field Operational Test (China-FOT) database of China Natural Driving Study project, this paper studies the driver's response in the common cut-in scenario. A total of 266 cut-in cases are selected by manual interception of driving recorder video. The relevant traffic environment characteristics are also extracted from video, including light conditions, road conditions, scale and lateral position of cut-in vehicle, etc. Dynamic information is decoded form CAN, such as speed, acceleration and so on. Then image processing results, such as relative speed and distance of cut-in and subject vehicles, are calculated. Statistical results based on above information show the response type and distribution of human driver: the behavior of keeping lane is 96.24%, in which the ratio of braking response is 51.13%. According to this, we choose to further research the behavior of keeping lane, and analyze the influencing factors of braking response. Statistical methods, such as Chi-square test, Spearman correlation test, are used to verify the relativity between the factor introduced above and braking. And test results indicated traffic flow, cut-in vehicle type, relative speed and distance of two vehicles are significantly correlated with the driver's braking response. Finally, a logistic regression model of the braking response probability is established with the relevant parameter. The model shows the braking probability of human drivers, when faced with cut-in vehicle.
Zhang, Jiarui, Ma, Zhixiong, Zhu, Xichan
Data Privacy in the Emerging Connected Mobility Services: Architecture, Use Cases, Privacy Risks, and Countermeasures11-02-01-000410/14/2019
The rapid development of connected and automated vehicle technologies together with cloud-based mobility services is transforming the transportation industry. As a result, huge amounts of consumer data are being collected and utilized to provide personalized mobility services. Using big data poses serious challenges to data privacy. To that end, the risks of privacy leakage are amplified by data aggregations from multiple sources and exchanging data with third-party service providers, in face of the recent advances in data analytics. This article provides a review of the connected vehicle landscape from case studies, system characteristics, and dataflows. It also identifies potential challenges and countermeasures.
Li, Huaxin, Ma, Di, Medjahed, Brahim, Kim, Yu Seung, Mitra, Pramita
Empathy to Elevate the User Experience19AVEP09_109/1/2019
Harman developers are striving to create human-machine interfaces oriented more towards user needs. In-car connectivity for today's cars and tomorrow's autonomous vehicles is moving product development norms beyond the traditional engineering approach. “Most products are designed from a straightforward engineering focus: It works like this. But with a user experience approach, it's about designing with empathy,” said Jason Johnson, director of user experience (UX) design at Harman. Designing with empathy essentially means that product developers strive to make decisions that align with user needs and wants. “What matters are the answers to these questions: Are users accomplishing their tasks and goals? What are they going to tell their friends about the experience? And will that feedback be positive or negative?” Johnson said.
Buchholz, Kami
Motion Cueing Algorithm for a 9-DoF Driving Simulator: MPC with Linearized Actuator Constraints12-02-03-00107/9/2019
In times when automated driving is becoming increasingly relevant, dynamic simulators present an appropriate simulation environment to faithfully reproduce driving scenarios. A realistic replication of driving dynamics is an important criterion to immerse persons in the virtual environments provided by the simulator. Motion Cueing Algorithms (MCAs) compute the simulator’s control input, based on the motions of the simulated vehicle. The technical restrictions of the simulator’s actuators form the main limitation in the execution of these input commands. Typical dynamic simulators consist of a hexapod with six degrees of freedom (DoF) to reproduce the vehicle motion in all dimensions. Since its workspace dimensions are limited, significant improvements in motion capabilities can be achieved by expanding the simulator with redundant DoF by means of additional actuators. This article introduces a global optimization scheme that is able to find an optimal motion for a 9-DoF driving simulator with three redundant DoF. The simulator consists of a tripod with three DoF in longitudinal, lateral and yaw direction as well as a hexapod, which is mounted on top of the tripod’s motion platform. The MCA is based on a model predictive control algorithm that solves a global optimization problem at each sampled time instance. The discrepancies between the desired and provided motion percepts are included in a cost function to be minimized by the optimization procedure. The optimization is constrained by the actuator limitations. Due to the nonlinear kinematic relations between the workspace and actuator space of both motion systems, a linearization approach is shown to adequately limit the actuator restrictions on position, velocity and acceleration level over a finite time horizon. We applied the proposed scheme to the real simulator and evaluated the method for various driving scenarios.
Ellensohn, Felix, Schwienbacher, Markus, Venrooij, Joost, Rixen, Daniel
ZF's Current Work Builds for the EV, AV Future19AVEP07_097/1/2019
The Tier-1 giant's “vision” for improving future mobility leverages its latest safety and chassis-development innovations. As the product-development landscape for light-vehicle electrification and automated-driving technologies becomes less cluttered, it's apparent that established automotive Tier 1 mega-suppliers are intent on merging their established competencies with whatever new product lines are required in the electrified, automated future…whenever it comes. This strategy was recently on display at a technology background event conducted in the U.S. by ZF. Long regarded for its transmission, driveline and chassis expertise, ZF showed customers and journalists various prototype systems intended to merge current-generation components to create higher-level functionality-and value.
Visnic, Bill
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