Browse Topic: Intelligent transportation systems

Items (326)
This document describes [motor] vehicle driving automation systems that perform part or all of the dynamic driving task (DDT) on a sustained basis. It provides a taxonomy with detailed definitions for six levels of driving automation, ranging from no driving automation (Level 0) to full driving automation (Level 5), in the context of [motor] vehicles (hereafter also referred to as “vehicle” or “vehicles”) and their operation on roadways: Level 0: No Driving Automation Level 1: Driver Assistance Level 2: Partial Driving Automation Level 3: Conditional Driving Automation Level 4: High Driving Automation Level 5: Full Driving Automation These level definitions, along with additional supporting terms and definitions provided herein, can be used to describe the full range of driving automation features equipped on [motor] vehicles in a functionally consistent and coherent manner. “On-road” refers to publicly accessible roadways (including parking areas and private campuses that permit public access) that collectively serve all road users, including cyclists, pedestrians, and users of vehicles with and without driving automation features. The levels apply to the driving automation feature(s) that are engaged in any given instance of on-road operation of an equipped vehicle. As such, although a given vehicle may be equipped with a driving automation system that is capable of delivering multiple driving automation features that perform at different levels, the level of driving automation exhibited in any given instance is determined by the feature(s) that are engaged. This document also refers to three primary actors in driving: the (human) user, the driving automation system, and other vehicle systems and components. These other vehicle systems and components (or the vehicle in general terms) do not include the driving automation system in this model, even though as a practical matter a driving automation system may actually share hardware and software components with other vehicle systems, such as a processing module(s) or operating code. The levels of driving automation are defined by reference to the specific role played by each of the three primary actors in performance of the DDT and/or DDT fallback. “Role” in this context refers to the expected role of a given primary actor, based on the design of the driving automation system in question and not necessarily to the actual performance of a given primary actor. For example, a driver who fails to monitor the roadway during engagement of a Level 1 adaptive cruise control (ACC) system still has the role of driver, even while s/he is neglecting it. Active safety systems, such as electronic stability control (ESC) and automatic emergency braking (AEB), and certain types of driver assistance systems, such as lane keeping assistance (LKA), are excluded from the scope of this driving automation taxonomy because they do not perform part or all of the DDT on a sustained basis, but rather provide momentary intervention during potentially hazardous situations. Due to the momentary nature of the actions of active safety systems, their intervention does not change or eliminate the role of the driver in performing part or all of the DDT, and thus are not considered to be driving automation, even though they perform automated functions. In addition, systems that inform, alert, or warn the driver about hazards in the driving environment are also outside the scope of this driving automation taxonomy, as they neither automate part or all of the DDT, nor change the driver’s role in performance of the DDT (see 8.13). It should be noted, however, that crash avoidance features, including intervention-type active safety systems, may be included in vehicles equipped with driving automation systems at any level. For automated driving system (ADS) features (i.e., Levels 3 to 5) that perform the complete DDT, crash mitigation and avoidance capability is part of ADS functionality (see also 8.13).
On-Road Automated Driving (ORAD) committee
Adopting Aviation Safety Knowledge into the Discussions of Safe Implementation of Connected and Autonomous Road Vehicles2021-01-00744/6/2021
The development of connected and autonomous vehicles (CAVs) is progressing fast. Yet, safety and standardization-related discussions are limited due to the recent nature of the sector. Despite the effort that is initiated to kick-start the study, awareness among practitioners is still low. Hence, further effort is required to stimulate this discussion. Among the available works on CAV safety, some of them take inspiration from the aviation sector that has strict safety regulations. The underlying reason is the experience that has been gained over the decades. However, the literature still lacks a thorough association between automation in aviation and the CAV from the safety perspective. As such, this paper motivates the adoption of safe-automation knowledge from aviation to facilitate safer CAV systems. The authors briefly elaborate on the widely discussed aviation themes, including autopilot and auto-throttle malfunctions, flight management system, human factors, and suggests how this knowledge can improve the safety of road CAVs use-case. Besides, the differences between the safety consideration in the two fields are also denoted. In summary, the main aim of this paper is to highlight the potential benefits of adopting aviation automation safety knowledge into safe CAV development. With the advances in the CAV, the authors are convinced that this subject could serve software developers and engineers in developing safe and standardized CAV technology.
Abdul Hamid, Umar ZakirMehndiratta, MohitAdali, Erkan
Stability Criteria for Accurate Path Tracking in Automated Guided Vehicle Systems2021-01-00934/6/2021
Satisfactory performance of intelligent vehicles systems in tracking a predefined trajectory requires an efficient control scheme to generate steering control signals from posture errors (i.e., errors in position and orientation). For such systems, it is necessary at each instant to control steering action so that any deviation from the path is corrected in a stable manner, in a reasonable time and without any oscillation about the desired path. This paper deals with stability of motion and motion control of intelligent vehicle systems. In this regard, the general control structure and specification of an optimum range of predefined control parameters for accurate path tracking of these systems are determined. A two degree of freedom (DOF) nonlinear dynamic model is developed to represent their plane motion. Path tracking of the vehicle is attained by controlling the position and orientation errors about the trajectory, which is accomplished by modifying the steering input signal on the basis of error feedbacks to the controller. Employment of various stability criteria and other constraints such as applying the physical limits of the vehicle to the controlled system narrows down the range of control parameters, within which the controlled system would remain stable. Experimental results demonstrating the performance of the system are reported.
Mehrabi, Mostafa
Letter from the Guest Editors
Hamid, Umar Zakir AbdulSandblom, FredrikHabibovic, AzraLi, Bin
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
This document is not a standard, it is a candidate for a standard being submitted to SAE for their consideration as a comment to SAE J2735. The term SAE J2735 SE candidate is used within this document to refer to this submission. This document specifies dialogs, messages, and the data frames and data elements that make up the messages specifically for use by applications intended to utilize the 5.9 GHz Dedicated Short Range Communications for Wireless Access in Vehicular Environments (DSRC/WAVE, referenced in this document simply as “DSRC"), communications systems. Although the scope of this Standard is focused on DSRC, these dialogs, messages, data frames and data elements have been designed, to the extent possible, to be of use for applications that may be deployed in conjunction with other wireless communications technologies. This standard therefore specifies the definitive message structure and provides sufficient background information to allow readers to properly interpret the message definitions from the point of view of an application developer implementing the messages according to the DSRC Standards.
V2X Communications Steering Committee
V2X Communications Message Set Dictionary™ SetJ2735SET_202007 (Historical)7/23/2020
This Abstract Syntax Notation (ASN.1) File is the precise source code used for SAE International Standard J2735. As part of an international treaty, all US ITS standards are expressed in "ASN.1 syntax". ASN.1 Syntax is used to define the messages or "ASN specifications". Using the ASN.1 specification, a compiler tool produces the ASN library which will then be used to produce encodings (The J2735 message set uses UPER encoding). The library is a set of many separate files that collectively implement the encoding and decoding of the standard. The library is then used by any application (along with the additional logic of that application) to manage the messages. The chosen ASN tool is used to produce a new copy of the library when changes are made, and it is then linked to the final application being developed. The ASN library manages many of the details associated with ASN syntax, allowing for subtle manipulation to make the best advantage of the encoding style. The J2735 Standard specifies a message set, and its data frames and data elements, specifically for use by applications intended to utilize the 5.9 GHz Dedicated Short Range Communications for Wireless Access in Vehicular Environments (DSRC/WAVE, referenced simply as "DSRC") communications systems. The ASN.1 integrates software for validation of telecommunications and networking. Although the scope of this Standard is focused on DSRC, this message set, and its data frames and data elements, have been designed, to the extent possible, to be of potential use for applications that may be deployed in conjunction with other wireless communications technologies as well. This Standard therefore specifies the definitive message structure and encoding and provides sufficient background information to allow readers to properly interpret the message definitions from the point of view of an application developer implementing the messages according to the DSRC Standards. You may also be interested in: V2X Communications Message Set Dictionary™ the J2735 PDF V2X Communications Message Set Dictionary™ J2735 ASN file includes the ASN file (ZIP format) - download purchase only Dedicated Short Range Communications (DSRC) Performance Requirements for V2V Safety Awareness™ the J2945/2 PDF Dedicated Short Range Communications (DSRC) Performance Requirements for V2V Safety Awareness™ J2945/2 ASN file that includes the ASN file (ZIP format) - download purchase only. Dedicated Short Range Communications (DSRC) Performance Requirements for V2V Safety Awareness™ Set includes the J2945/2 ASN file and the J2945/2 PDF (ZIP format) - download purchase only. Requirements for Road Weather Applications™ the J2945/3 PDF Requirements for Road Weather Applications™ J2945/3 ASN file that includes the ASN file (ZIP format) - download purchase only. Requirements for Road Weather Applications™ Set includes the J2945/3 ASN file and the J2945/3 PDF (ZIP format) - download purchase only.
V2X Core Technical Committee
V2X Communications Message Set Dictionary™ ASN fileJ2735ASN_202007 (Historical)7/23/2020
This Abstract Syntax Notation (ASN.1) File is the precise source code used for SAE International Standard J2735. As part of an international treaty, all US ITS standards are expressed in "ASN.1 syntax". ASN.1 Syntax is used to define the messages or "ASN specifications". Using the ASN.1 specification, a compiler tool produces the ASN library which will then be used to produce encodings (The J2735 message set uses UPER encoding). The library is a set of many separate files that collectively implement the encoding and decoding of the standard. The library is then used by any application (along with the additional logic of that application) to manage the messages. The chosen ASN tool is used to produce a new copy of the library when changes are made, and it is then linked to the final application being developed. The ASN library manages many of the details associated with ASN syntax, allowing for subtle manipulation to make the best advantage of the encoding style. The J2735 Standard specifies a message set, and its data frames and data elements, specifically for use by applications intended to utilize the 5.9 GHz Dedicated Short Range Communications for Wireless Access in Vehicular Environments (DSRC/WAVE, referenced simply as "DSRC") communications systems. The ASN.1 integrates software for validation of telecommunications and networking. Although the scope of this Standard is focused on DSRC, this message set, and its data frames and data elements, have been designed, to the extent possible, to be of potential use for applications that may be deployed in conjunction with other wireless communications technologies as well. This Standard therefore specifies the definitive message structure and encoding and provides sufficient background information to allow readers to properly interpret the message definitions from the point of view of an application developer implementing the messages according to the DSRC Standards. You may also be interested in: V2X Communications Message Set Dictionary™ the J2735 PDF V2X Communications Message Set Dictionary™ Set includes the J2735 ASN file and the J2735 PDF (ZIP format) - download purchase only. Dedicated Short Range Communications (DSRC) Performance Requirements for V2V Safety Awareness™ the J2945/2 PDF Dedicated Short Range Communications (DSRC) Performance Requirements for V2V Safety Awareness™ J2945/2 ASN file that includes the ASN file (ZIP format) - download purchase only. Dedicated Short Range Communications (DSRC) Performance Requirements for V2V Safety Awareness™ Set includes the J2945/2 ASN file and the J2945/2 PDF (ZIP format) - download purchase only. Requirements for Road Weather Applications™ the J2945/3 PDF Requirements for Road Weather Applications™ J2945/3 ASN file that includes the ASN file (ZIP format) - download purchase only. Requirements for Road Weather Applications™ Set includes the J2945/3 ASN file and the J2945/3 PDF (ZIP format) - download purchase only.
V2X Core Technical Committee
This document describes machine-to-machine (M2M) communication to enable cooperation between two or more participating entities or communication devices possessed or controlled by those entities. The cooperation supports or enables performance of the dynamic driving task (DDT) for a subject vehicle with driving automation feature(s) engaged. Other participants may include other vehicles with driving automation feature(s) engaged, shared road users (e.g., drivers of manually operated vehicles or pedestrians or cyclists carrying personal devices), or road operators (e.g., those who maintain or operate traffic signals or workzones). Cooperative driving automation (CDA) aims to improve the safety and flow of traffic and/or facilitate road operations by supporting the movement of multiple vehicles in proximity to one another. This is accomplished, for example, by sharing information that can be used to influence (directly or indirectly) DDT performance by one or more nearby road users. Vehicles and infrastructure elements engaged in cooperative automation may share information, such as state (e.g., vehicle position, signal phase), intent (e.g., planned vehicle trajectory, signal timing), or seek agreement on a plan (e.g., coordinated merge). Cooperation among multiple participants and perspectives in traffic can improve safety, mobility, situational awareness, and operations. However, nothing in this document is intended to suggest that driving automation requires such cooperation in order to be performed safely. Cooperative strategies may be enabled by the sharing of information in a way that meets the needs of a given application. The needs may be expressed in terms of performance characteristics, such as latency, transmission mode (e.g., one-way, two-way), range, privacy and security, and information content and quality. There are several potential technologies for communicating information between the subject vehicle and other participants. This document focuses on application-oriented functionality and does not imply the need for or require any specific functionality associated with communications protocols or the open systems interconnection model layers in a protocol stack. This document addresses the operational and tactical timescales of dynamic driving on ADS-operated vehicles, and excludes strategic functions such as trip scheduling and selection of destinations and waypoints. This information report is intended to facilitate communication and awareness for the design and anticipated development and validation of cooperative driving automation.
Cooperative Driving Automation(CDA) Committee
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
Analysis of LiDAR and Camera Data in Real-World Weather Conditions for Autonomous Vehicle Operations2020-01-00934/14/2020
Autonomous vehicle technology has the potential to improve the safety, efficiency, and cost of our current transportation system by removing human error. With sensors available today, it is possible for the development of these vehicles, however, there are still issues with autonomous vehicle operations in adverse weather conditions (e.g. snow-covered roads, heavy rain, fog, etc.) due to the degradation of sensor data quality and insufficiently robust software algorithms. Since autonomous vehicles rely entirely on sensor data to perceive their surrounding environment, this becomes a significant issue in the performance of the autonomous system. The purpose of this study is to collect sensor data under various weather conditions to understand the effects of weather on sensor data. The sensors used in this study were one camera and one LiDAR. These sensors were connected to an NVIDIA Drive Px2 which operated in a 2019 Kia Niro. Two custom scenarios (static and dynamic objects) were chosen to collect sensor data operating in four real-world weather conditions: fair, cloudy, rainy, and light snow. An algorithm developed herein was used to provide a method of quantifying the data for comparison against the other weather conditions. The results from these performance algorithms show that sensor data quality degrades by an average of 13.88% for static objects and 16.16% for dynamic objects while operating in these conditions, with operations in rain proving to have the most significant effect on sensor data degradation. From this study, it is hypothesized that advancements in data processing algorithms can improve the usability of this degraded data. In future work, we seek to explore fault-tolerant sensor fusion algorithms that can overcome the effects of adverse weather.
Goberville, NickEl-Yabroudi, MohammadOmwanas, MarkRojas, JohanMeyer, RickAsher, ZacharyAbdel-Qader, Ikhlas
A Visible and Infrared Fusion Based Visual Odometry for Autonomous Vehicles2020-01-00994/14/2020
An accurate and timely positioning of the vehicle is required at all times for autonomous driving. The global navigation satellite system (GNSS), even when integrated with costly inertial measurement units (IMUs), would often fail to provide high-accuracy positioning due to GNSS-challenged environments such as urban canyons. As a result, visual odometry is proposed as an effective complimentary approach. Although it’s widely recognized that visual odometry should be developed based on both visible and infrared images to address issues such as frequent changes in ambient lightening conditions, the mechanism of visible-infrared fusion is often poorly designed. This study proposes a Generative Adversarial Network (GAN) based model comprises a generator, which aims to produce a fused image combining infrared intensities and visible gradients, and a discriminator whose target is to force the fused image to retain as many details that exist mostly in visible images as possible. Based on the fused image, the Features from Accelerated Segment Test (FAST) algorithm is adopted to extract feature points which are then traced with the Lucas-Kanade (LK) algorithm in subsequent images. Furthermore, to remove mismatched feature points, the Random Sample Consensus (RANSAC) method is employed to detect the outliers iteratively and to compute the essential matrix. Experiments are conducted utilizing the KAIST benchmark dataset. A significant improve in positioning accuracy is observed from experimental results, as compared to visual odometry built upon visible and infrared images only. The proposed visual odometry can provide high-accuracy positioning when the GNSS is challenged.
Zhou, YunfeiYin, Zhishuai
Autonomous Vehicles Camera Blinding Attack Detection Using Sequence Modelling and Predictive Analytics2020-01-07194/14/2020
Autonomous vehicles are waiting to address the global automotive mobility challenges through an intelligent smart transportation system, which includes advanced sensor-actuator configurations to control, navigate, and drive the vehicles. Multi-sensor data fusion from the key sensors such as camera, radar, and lidar is used to achieve the environmental perception for autonomous vehicles by capturing the various attributes of the environment. Cameras are the dominant sensors to achieve the perception by providing vision capability to vehicles. The direct interface of the cameras with the dynamic driving environment carries numerous attack surfaces on the camera. Blinding attacks on the cameras are one of the critical attacks with an intention to blind the cameras either fully or partially by projecting light into the cameras to hide the objects which results in failure in object detection. Here, the blinding attack detection approach is proposed which detects the blinding attacks on the camera in a dynamic driving environment by camera data predictive analytics. The proposed system predicts the future next frame of the video at each time instance and compares the received frame from the camera with the predicted frame at that instance to detect the blinding attacks. The incoming frames from the camera are sequentially modeled using a convolutional encoder-decoder neural network to predict the consecutive future frames, and the predicted frames are compared with the received camera frames to identify the similarity measure between the predicted and incoming camera frames of the same instance. Further, the approach detects the blinding on the camera, if the similarity measure calculated falls below a fixed threshold. The similarity measure which is inversely proportional to the amount of blinding is used to identify the blinding attacks. The predictive analytics of the sequentially modeled video frames with similarity measurement is used for the successful detection of blinding attacks.
D H, Sharath YadavAnsari, Asadullah
Selftrust - A Practical Approach for Trust Establishment2020-01-07204/14/2020
In recent years, with increase in external connectivity (V2X, telematics, mobile projection, BYOD) the automobile is becoming a target of cyberattacks and intrusions. Any such intrusion reduces customer trust in connected cars and negatively impacts brand image (like the recent Jeep Cherokee hack). To protect against intrusion, several mechanisms are available. These range from a simple secure CAN to a specialized symbiote defense software. A few systems (e.g. V2X) implement detection of an intrusion (defined as a misbehaving entity). However, most of the mechanisms require a system-wide change which adds to the cost and negatively impacts the performance. In this paper, we are proposing a practical and scalable approach to intrusion detection. Some benefits of our approach include use of existing security mechanisms such as TrustZone® and watermarking with little or no impact on cost and performance. In addition, our approach is scalable and does not require any system-wide changes. To detect intrusions, we propose a combination of TrustZone® secure space approach along with a mechanism of static and dynamic watermarks. The current scope of research is restricted to architectures which provide a secure space to execute software. The research is an enhancement over the current TrustZone® implementation for device control post intrusion. In conclusion, the proposed approach is a simple and scalable mechanism for detection and control of intrusion.
Abhyankar, Ranjit VinayakA, Sreenath
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, GuanZhan, ZhenfeiPeng, XiangjunXu, HuijieFu, YueJiang, Ling
Data-Driven Framework for Fuel Efficiency Improvement in Extended Range Electric Vehicle Used in Package Delivery Applications2020-01-05894/14/2020
Extended range electric vehicles (EREVs) are a potential solution for fossil fuel usage mitigation and on-road emissions reduction. The use of EREVs can be shown to yield significant fuel economy improvements when proper energy management strategies (EMSs) are employed. However, many in-use EREVs achieve only moderate fuel reduction compared to conventional vehicles due to the fact that their EMS is far from optimal. This paper focuses on in-use rule-based EMSs to improve the fuel efficiency of EREV last-mile delivery vehicles equipped with two-way Vehicle-to-Could (V2C) connectivity. The method uses previous vehicle data collected on actual delivery routes and machine learning methods to improve the fuel economy of future routes. The paper first introduces the main challenges of the project, such as inherent uncertainty in human driver behavior and in the roadway environment. Then, the framework of our practical physics-model guided data-driven approach is introduced. For vehicles with small amounts of prior data, a Bayesian method is used to adjust a control parameter in the EMS offline for each vehicle with introduced prior information derived from large numbers of trips from other vehicles in the fleet. For vehicles with many delivery trips, a reinforcement learning algorithm is used to optimize the parameter in real-time without requiring future information of the trip. Although our data-driven framework cannot achieve a globally optimal solution with respect to the fuel efficiency, it provides a systematic and immediate solution for in-use EREVs used for package delivery with a very low computation cost and no change of vehicle hardware. Also, this framework is ready to be extended for further fuel economy improvements if more information is available from advanced transportation infrastructures like Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) connectivity.
Wang, PengyueNorthrop, William
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
A Stability-Guaranteed Time-Delay Range for Feedback Control of Autonomous Vehicles2020-01-00904/14/2020
The vehicles with level-5 autonomy (L5AVs) that have no human driver in the loop are also known as self-driving cars. L5AVs are assumed the next generation of ground transportation, which have growing attention from both industry and academia in most recent years. Most of the work related to feedback strategies of L5AVs are on developing mapping systems through a variety of sensors. These systems can be considered as an analogue to the perception and central nervous system of human drivers. For instance, innovative visualization systems are more powerful when compared to the visual perception system of a person, yet, mapping demands high computation loads. This burden causes delay in the feedback loop and thus, it might have an unfavorable influence on proper and safe control action. This study investigates the effect of time delay occurring in mapping systems on the stability of the controlled vehicle. An algorithm entitled as “Cluster Treatment of Characteristic Roots - CTCR” is used to calculate a safe delay range as a remedy for the time delay caused by mapping systems. The CTCR analysis is applied to a linearized two degree-of-freedom bicycle model for different velocities. The critical time delay values, which determines the boundary between the stability and instability of the controlled vehicle, are calculated based on the vehicle dynamics. Finally, results are drawn for a regular weave test by computer simulations, in which a non-linear vehicle model is used. The proposed approach is validated by exhibiting that a delay value outside the safe range leads the vehicle instability.
Kirli, AhmetArslan, Mehmet Selçuk
Platooning Vehicles Control for Balancing Coupling Maintenance and Trajectory Tracking - Feasibility Study Using Scale-Model Vehicles2020-01-01284/14/2020
Recently, car-sharing services using ultra-compact mobilities have been attracting attention as a means of transportation for one or two passengers in urban areas. A platooning system consisting of a manned leader vehicle and unmanned follower vehicles can reduce vehicle distributors. We have proposed a platooning system which controls vehicle motion based on the relative position and posture measured by non-contact coupling devices installed between vehicles. The feasibility of the coupling devices was validated through a HILS experiment. There are two basic requirements for realizing our platooning system; (1) all devices must remain coupled and (2) follower vehicles must be able to track the leader vehicle trajectory. Thus, this paper proposes two vehicle control method for satisfying those requirements. They are the “device coupling and trajectory tracking merging method” and the “trajectory shifting method”. The device coupling and trajectory tracking merging method consisting of a coupling keeping controller and a trajectory tracking controller. The predominant controller is chosen according to the amount of the coupling device error and the trajectory tracking error. The trajectory shifting method shifts the tracking target trajectory to keep the device coupled. The shifting amount is decided by the estimated turning radius of the leader vehicle. Platooning experiments using two 1:16 scale-model vehicles has been performed on the experiment course containing a straight section and a circular section. Experiment results revealed that the device coupling and trajectory tracking merging method can maintain the coupling of the device while limiting the trajectory tracking error to a certain range. Though the trajectory shifting method can reduce the coupling device error, it fails on both device coupling keeping and trajectory error limiting, owing to the inadequacy in estimating the turning radius of the leader.
Fukui, RuiYe, QiweiSuzuki, AyumiWarisawa, Shin’ichi
Effects of a Probability-Based Green Light Optimized Speed Advisory on Dilemma Zone Exposure2020-01-01164/14/2020
Green Light Optimized Speed Advisory (GLOSA) systems have the objective of providing a recommended speed to arrive at a traffic signal during the green phase of the cycle. GLOSA has been shown to decrease travel time, fuel consumption, and carbon emissions; simultaneously, it has been demonstrated to increase driver and passenger comfort. Few studies have been conducted using historical cycle-by-cycle phase probabilities to assess the performance of a speed advisory capable of recommending a speed for various traffic signal operating modes (fixed-time, semi-actuated, and fully-actuated). In this study, a GLOSA system based on phase probability is proposed. The probability is calculated prior to each trip from a previous week’s, same time-of-day (TOD) and day-of-week (DOW) period, traffic signal controller high-resolution event data. By utilizing this advisory method, real-time communications from the vehicle to infrastructure (V2I) become unnecessary, eliminating data-loss related issues. The effects of three different advice approaches (conservative, balanced, and aggressive) on dilemma zone exposure are analyzed. Proof of concept is carried out by simulating drives through a test-route composed of an arterial that had historical high-resolution traffic signal event logs for a series of actuated-coordinated traffic signals during different TOD and DOW. A comparison was performed between unadvised and GLOSA advised trips obtained from approximately 486,000 simulated trajectories. Results were obtained by analyzing the vehicle’s probability of stopping from utilizing Traffic Engineering dilemma zone theory. Reductions of 93% in the amount of hard brakings and 96% in the number of crossings through red light were observed with the proposed system. This data suggests the feasibility of a probability-based advisory, as well as the viability of utilizing the proposed GLOSA system to minimize dilemma zone exposure.
Saldivar-Carranza, EnriqueLi, HowellKim, WoosungMathew, JijoBullock, DarcySturdevant, James
Trajectory Planning and Tracking for Four-Wheel-Steering Autonomous Vehicle with V2V Communication2020-01-01144/14/2020
Lane-changing is a typical traffic scene effecting on road traffic with high request for reliability, robustness and driving comfort to improve the road safety and transportation efficiency. The development of connected autonomous vehicles with V2V communication provide more advanced control strategies to research of lane-changing. Meanwhile, four-wheel steering is an effective way to improve flexibility of vehicle. The front and rear wheels rotate in opposite direction to reduce the turning radius to improve the servo agility operation at the low speed while those rotate in same direction to reduce the probability of the slip accident to improve the stability at the high speed. Hence, this paper established Four-Wheel-Steering(4WS) vehicle dynamic model and quasi real lane-changing scenes to analyze the motion constraints of the vehicles. Then, the polynomial function was used for the lane-changing trajectory planning and the extended rectangular vehicle model was established to get vehicle collision avoidance condition. Vehicle comfort requirements and lane-changing efficiency were used as the optimization variables of optimization function and the control of trajectory tracking can be obtained by using model predictive control (MPC) method. A lane-changing model based on steering characteristics and safety distance with the system of V2V communication and collaboration strategy was established. The lane-changing trajectory was simulated by MATLAB and the results showed that the lane-changing trajectory can safely realize the lane-changing behavior of 4WS autonomous vehicles.
Ma, FangwuShen, YuchengNie, JiahongLi, XiyuYang, YuWang, JiaweiWu, Guanpu
Hardware-in-the-Loop and Road Testing of RLVW and GLOSA Connected Vehicle Applications2020-01-13794/14/2020
This paper presents an evaluation of two different Vehicle to Infrastructure (V2I) applications, namely Red Light Violation Warning (RLVW) and Green Light Optimized Speed Advisory (GLOSA). The evaluation method is to first develop and use Hardware-in-the-Loop (HIL) simulator testing, followed by extension of the HIL testing to road testing using an experimental connected vehicle. The HIL simulator used in the testing is a state-of-the-art simulator that consists of the same hardware like the road side unit and traffic cabinet as is used in real intersections and allows testing of numerous different traffic and intersection geometry and timing scenarios realistically. First, the RLVW V2I algorithm is tested in the HIL simulator and then implemented in an On-Board-Unit (OBU) in our experimental vehicle and tested at real world intersections. This same approach of HIL testing followed by testing in real intersections using our experimental vehicle is later extended to the GLOSA application. The GLOSA application that is tested in this paper has both an optimal speed advisory for passing at the green light and also includes a red light violation warning system. The paper presents the HIL and experimental vehicle evaluation systems, information about RLVW and GLOSA and HIL simulation and road testing results and their interpretations.
Gelbal, Sukru YarenCantas, Mustafa RidvanAksun Guvenc, BilinGuvenc, LeventSurnilla, GopichandraZhang, HaoShulman, MichaelKatriniok, AlexanderParikh, Jayendra
Secure Vehicular Communication Using Blockchain Technology2020-01-07224/14/2020
The cars we drive are rapidly transforming. Connected vehicles in the context of the Advanced Driver Assistance System or Autonomous Vehicles are about to change the way we drive cars. Connected Vehicles are futuristic vehicles that can interact with other vehicles for passing on information such as, mapping and localization, information about road traffic and driving behaviour. However, such vehicles, particularly the autonomous ones, are prone to a variety of attacks including cyber-attacks. These malicious attacks can intrude a vehicle that not only endangers the vehicles safety, but also the life of passengers and the nearby environment. Thus, identifying and eliminating these attacks for providing a secure communication environment is of great need. Also, all the existing methods for vehicular communication rely on a centralized server which itself invite massive cyber-security threats. These threats and challenges can be addressed by using the Blockchain (BC) technology, where each transaction is logged in a decentralized immutable BC ledger. In this work, we show how BC can facilitate communication between connected vehicles to send and receive information while assuring the security of all the vehicles participating in the BC network. First, we developed an application for the blockchain based less-complex Proof-of-Work consensus method that allows the vehicles to transfer information in a secured manner. Second, we demonstrate the working of the application using raspberry pi board that act as vehicles mounted with sensors and two computers that act as blockchain network. Finally, we discuss the advantages and disadvantages of blockchain based vehicular communication and the integration of the blockchain with VANET as well.
M, Vidya KrishnanKoduri, RajeshNandyala, SivaprasadManalikandy, Mithun
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
Real-time and Accurate Estimation of Road Slope for Intelligent Speed Planning System of Commercial Vehicle2020-01-01154/14/2020
In the intelligent speed planning system, real-time estimation of road slope is the key to calculate slope resistance and realize the vehicles’ active safety control. However, if the road slope is measured by the sensor while the commercial vehicle is driving, the vibration of the vehicle body will affect its measurement accuracy. Therefore, the relevant algorithm is used to estimate the real-time slope of the road when the commercial vehicle is driving. At present, many domestic and foreign scholars have analyzed and tested the estimation of road slope by the least square method or Kalman filter algorithm. Although the two methods both can achieve the estimation, the real-time performance and accuracy still need to be improved. In this paper, for traditional fuel commercial vehicle, the Kalman filter algorithm based on the kinematics and the extended Kalman filter algorithm based on the longitudinal dynamics are respectively used to estimate the road slope. In the process of estimation based on kinematics, considering the influence of road slope rate to estimate, the recursive least squares method with forgetting factor is used to estimate the road slope rate.Finally, the estimation results obtained by kinematics and dynamics are combined. It is expected that the error based on the algorithm-estimated slope value and the true slope value will be within 6% after the commercial vehicle is driving. The proposed algorithm has high accuracy, good real-time performance and strong stability. Using the commercial vehicle as a motion node and estimating the slope of a certain road, the intelligent planning of other vehicles’ speed in that region can be realized through the cloud platform. Then the fuel economy of the commercial vehicle can be improved.
Zhou, MiTan, GangfengSun, MengTian, ZhongpengZhou, FangyuLiu, ZhiQiang
Cooperative Mandatory Lane Change for Connected Vehicles on Signalized Intersection Roads2020-01-08894/14/2020
This paper presents a hierarchical control architecture to coordinate a group of connected vehicles on signalized intersection roads, where vehicles are allowed to change lane to follow a prescribed path. The proposed hierarchical control strategy consists of two control levels: a high level controller at the intersection and a decentralized low level controller in each car. In the hierarchical control architecture, the centralized intersection controller estimates the target velocity for each approaching connected vehicle to avoid red light stop based on the signal phase and timing (SPAT) information. Each connected vehicle as a decentralized controller utilizes model predictive control (MPC) to track the target velocity in a fuel efficient manner. The main objective in this paper is to consider mandatory lane changes. As in the realistic scenarios, vehicles are not required to drive in single lane. More specifically, they more likely change their lanes prior to signals. Hence, the vehicle decentralized controllers must prepare to cooperate with the vehicle that has a mandatory lane change request (host vehicle). The cooperative mandatory lane change is accomplished by inserting a virtual vehicle on the host vehicle’s target lane. The simulation results show the advantage of our proposed approach on both the lane change duration and vehicle fuel economy.
Du, ZhiyuanXu, BinPisu, Pierluigi
Engine-in-the-Loop Study of a Hierarchical Predictive Online Controller for Connected and Automated Heavy-Duty Vehicles2020-01-05924/14/2020
This paper presents a cohesive set of engine-in-the-loop (EIL) studies examining the use of hierarchical model-predictive control for fuel consumption minimization in a class-8 heavy-duty truck intended to be equipped with Level-1 connectivity/automation. This work is motivated by the potential of connected/automated vehicle technologies to reduce fuel consumption in both urban/suburban and highway scenarios. The authors begin by presenting a hierarchical model-predictive control scheme that optimizes multiple chassis and powertrain functionalities for fuel consumption. These functionalities include: vehicle routing, arrival/departure at signalized intersections, speed trajectory optimization, platooning, predictive optimal gear shifting, and engine demand torque shaping. The primary optimization goal is to minimize fuel consumption, but the hierarchical controller explicitly accounts for other key objectives/constraints, including operator comfort and safe inter-vehicle spacing. This work is experimentally experimentally validated via a sequence of EIL studies intended for evaluating the computational costs and fuel savings associated with these algorithms. These EIL studies involve the closed-loop validation of the proposed control strategies, both individually and combined. These studies show that this hierarchy of algorithms is capable of running online, with the round-trip communication delay inherent in EIL simulation being one of the key factors affecting the EIL results. Moreover, the EIL studies are encouraging, both in terms of the successful hierarchical integration of the underlying algorithms and also in the resulting fuel savings seen in the EIL tests. In particular, the EIL results suggest that an aggressive overall goal of reducing vehicle fuel consumption by 15-20% or more is potentially achievable, especially in urban/suburban scenarios.
Xu, ChuGroelke, BenAlvarez Tiburcio, MiguelEarnhardt, ChristianBorek, JohnPelletier, EvanBoyle, StephenHuynh, BrianWahba, MohamedGeyer, StephenGraham, ChristopherMagee, MarkPalmeter, KyleNaghnaeian, MohammadBrennan, SeanStockar, StephanieVermillion, ChristopherFathy, Hosam
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