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Journal Article

3D Auditory Displays for Parking Assistance Systems

The objective of this study was to investigate if 3D auditory displays could be used to enhance parking assistance systems (PAS). Objective measurements and estimations of workload were used to assess the benefits of different 3D auditory displays. In today’s cars, PAS normally use a visual display together with simple sound signals to inform drivers of obstacles in close proximity. These systems rely heavily on the visual display, as the sound does not provide information about obstacles' location. This may cause the driver to lose focus on the surroundings and reduce situational awareness. Two user studies (during summer and winter) were conducted to compare three different systems. The baseline system corresponded to a system normally found in today’s cars. The other systems were designed with a 3D auditory display, conveying information of where obstacles were located through sound. A visual display was also available. Both normal parking and parallel parking was conducted.
Technical Paper

3D Automotive Millimeter-Wave Radar with Two-Dimensional Electronic Scanning

The radar-based advanced driver assistance systems (ADAS) like autonomous emergency braking (AEB) and forward collision warning (FCW) can reduce accidents, so as to make vehicles, drivers and pedestrians safer. For active safety, automotive millimeter-wave radar is an indispensable role in the automotive environmental sensing system since it can work effectively regardless of the bad weather while the camera fails. One crucial task of the automotive radar is to detect and distinguish some objects close to each other precisely with the increasingly complex of the road condition. Nowadays almost all the automotive radar products work in bidimensional area where just the range and azimuth can be measured. However, sometimes in their field of view it is not easy for them to differentiate some objects, like the car, the manhole covers and the guide board, when they align with each other in vertical direction.
Technical Paper

A Case Study in Applying a Product Line Approach for Car Periphery Supervision Systems

Car Periphery Supervision (CPS) systems comprise a family of automotive systems that are based on sensors installed around the vehicle to monitor its environment. The measurement and evaluation of sensor data enables the realization of several kinds of higher level applications such as parking assistance or blind spot detection. Although a lot of similarity can be identified among CPS applications, these systems are traditionally built separately. Usually, each single system is built with its own electronic control unit, and it is likely that the application software is bound to the controller's hardware. Current systems engineering therefore often leads to a large number of inflexible, dedicated systems in the automobile that together consume a large amount of power, weight, and installation space and produce high manufacturing and maintenance costs.
Technical Paper

A Comparative Study on Various Methodologies and Solutions for Evaluation of Short-Range Radar to Validate the Features of Autonomous Vehicle

Autonomous vehicle is a vehicle capable of sensing its environment and taking decisions automatically with no human interventions. To achieve this goal, ADAS (Advance Driving Assistance System) technologies play an important role and the technologies are improving and emerging. The sensing of environment can be achieved with the help of sensors like Radar and Camera. Radar sensors are used in detecting the range, speed and directions of multiple targets using complex signal processing algorithms. Radar with long range and short range are widely used in the autonomous vehicles. Radar sensors with long range can be used to realize features like Adaptive Cruise Control, Advance Emergency Brake Assist. The short-range radar sensors are used for Blind Spot Monitoring, Lane Change Assist, Rear/Front Cross Traffic Alert and Occupant Safe Exit. To realize the Autonomous vehicle functionalities four short range radar sensors are required, two on front and two on rear (left and right).
Technical Paper

A Context Aware Automatic Image Enhancement Method Using Color Transfer

Advanced Driver Assistance Systems (ADAS) have become an inevitable part of most of the modern cars. Their use is mandated by regulations in some cases; and in other cases where vehicle owners have become more safety conscious. Vision / camera based ADAS systems are widely in use today. However, it is to be noted that the performance of these systems is depends on the quality of the image/video captured by the camera. Low illumination is one of the most important factors which degrades image quality. In order to improve the system performance under low illumination, it is required to first enhance the input images/frames. In this paper, we propose an image enhancement algorithm that would automatically enhance images to a near ideal condition. This is accomplished by mapping features taken from images acquired under ideal illumination conditions on to the target low illumination images/frames.
Technical Paper

A Data-Driven Radar Object Detection and Clustering Method Aided by Camera

The majority of road accidents are caused by human oversight. Advanced Driving Assistance System (ADAS) has the potential to reduce human error and improve road safety. With the rising demand for safety and comfortable driving experience, ADAS functions have become an important feature when car manufacturers developing new models. ADAS requires high accuracy and robustness in the perception system. Camera and radar are often combined to create a fusion result because the sensors have their own advantages and drawbacks. Cameras are susceptible to bad weather and poor lighting condition and radar has low resolution and can be affected by metal debris on the road. Clustering radar targets into objects and determine whether radar targets are valid objects are challenging tasks. In the literature, rule-based and thresholding methods have been proposed to filter out stationary objects and objects with low reflection power.
Technical Paper

A Digital Forensic Method to Detect Object based Video Forgery Security Attacks on Surround View ADAS Camera System

The present and futuristic surround view camera systems provide the bird-eye’s view of the driving environment to the driver through a real-time video feed in the digital cockpit infotainment display, which assists the driver in maneuvering, parking, lane changing by performing object detection, object tracking, maneuver estimation, blind spot detection, lane detection, etc., The functional safety of this surround view camera system is gets compromised, if it fails to alert the driver, when truly obstacles are present in the nearby driving environment of the vehicle, or if it alerts the driver when no obstacles are present in the nearby driving environment. This malfunctioning of surround view driver assistance system is due to integrity compromisation through cyberattacks, where attackers forge the displayed video data on the infotainment system, which has external world connectivity.
Technical Paper

A Driver Assistance System for Improving Commercial Vehicle Fuel Economy

Commercial vehicle operators and governments around the world are looking for ways to cut down on fuel consumption for economic and environmental reasons. Two main factors affecting the fuel consumption of a vehicle are the drive route and the driver behavior. The drive route can be specified by information such as speed limit, road grade, road curvature, traffic etc. The driver behavior, on the other hand, is difficult to classify and can be responsible for as much as 35% variation in fuel consumption. In this work, nearly 600,000 miles of drive data is utilized to identify driving behaviors that significantly affect fuel consumption. Based on this analysis, driving scenarios and related driver behaviors are identified that result in the most efficient vehicle operation. A driver assistance system is presented in this paper that assists the driver in driving more efficiently by issuing scenario specific advice.
Technical Paper

A Driving Simulator HMI Study Comparing a Steering Wheel Mounted Display to HUD, Instrument Panel and Center Stack Displays for Advanced Driver Assistance Systems and Warnings

Simple, effective, and appropriately placed visual information must be available to the driver as part of a well designed Human Machine Interface (HMI). Visual interfaces for Advanced Driver Assistance Systems (ADAS), secondary task control, and safety warnings should attempt to minimize both driver reaction time to warnings and the workload on the driver to comprehend a warning or respond to driving advice or information. A driving simulator study was designed and executed to assess the appropriateness and effectiveness of three display concepts. The study directly compared the driver warning reaction and overall workload for three visual HMIs: the conventional instrument panel and center-stack displays (IP/CS), an idealized heads up display (HUD), and the Communication Steering Wheel (CSW) display. Study participants were required to respond to secondary convenience control tasks (4 tasks); safety warnings (3 scenarios); and also a peripheral detection task (PDT).
Journal Article

A Flexible High-Performance Accelerator Platform for Automotive Sensor Applications

High-performance computer architectures for advanced driver assistance systems have become increasingly important in automotive research in the last several years. In order to achieve an optimal and robust perception of the vehicle's surroundings, current driver assistance applications typically rely on multiple sensor systems that deliver large amounts of incoming data from different sensor types. Such sensors include optical systems, which consist of a multi-camera setup combined with complex preprocessing algorithms. These algorithms exhibit high computation and data transport demands, as real-time image processing of multiple input streams is a mandatory requirement for these systems. At the same time, however, future driver assistance systems must adhere to strict power consumption requirements and automotive cost constraints in order to be considered for integration in series vehicles.
Journal Article

A Framework for Virtual Testing of ADAS

Virtual testing of advanced driver assistance systems (ADAS) using a simulation environment provides great potential in reducing real world testing and therefore currently much effort is spent on the development of such tools. This work proposes a simulation and hardware-in-the-loop (HIL) framework, which helps to create a virtual test environment for ADAS based on real world test drive. The idea is to reproduce environmental conditions obtained on a test drive within a simulation environment. For this purpose, a production standard BMW 320d is equipped with a radar sensor to capture surrounding traffic objects and used as vehicle for test drives. Post processing of recorded GPS raw data from the navigation system using an open source map service and the radar data allows an exact reproduction of the driven road including other traffic participants.
Technical Paper

A Framework for Vision-Based Lane Line Detection in Adverse Weather Conditions Using Vehicle-to-Infrastructure (V2I) Communication

Lane line detection is a very critical element for Advanced Driver Assistance Systems (ADAS). Although, there has been significant amount of research dedicated to the detection and localization of lane lines in the past decade, there is still a gap in the robustness of the implemented systems. A major challenge to the existing lane line detection algorithms stems from coping with bad weather conditions (e.g. rain, snow, fog, haze, etc.). Snow offers an especially challenging environment, where lane marks and road boundaries are completely covered by snow. In these scenarios, on-board sensors such as cameras, LiDAR, and radars are of very limited benefit. In this research, the focus is on solving the problem of improving robustness of lane line detection in adverse weather conditions, especially snow. A framework is proposed that relies on using Vehicle-to-Infrastructure (V2I) communication to access reference images stored in the cloud.
Technical Paper

A HiL Test Bench for Monocular Vision Sensors and Its Applications in Camera-Only AEBs

This paper presents a HiL test bench specifically designed for closed-loop testing of the monocular-vision based ADAS sensors, whereby the animated pictures of the virtual scene is calibrated and projected onto a 120-degree circular screen, such that the camera sensor installed has the same vision as the observation of the real-world scene. A high-fidelity AEBs model is established and deployed in the real-time target of the HiL system, making intervention decisions based on the instance-level detection information transmitted from the physical sensor. By referring to the 2018 edition of the C-NCAP testing protocol, the HiL tests of the rear-end collision scenarios is performed to investigate the performance and characteristics of the longitudinal-motion sensing of the sensor sample under test.
Technical Paper

A Hybrid Classification of Driver’s Style and Skill Using Fully-Connected Deep Neural Networks

Driving style and skill classification are of great significance in human-oriented advanced driver-assistance system (ADAS) development. In this paper, we propose Fully-Connected Deep Neural Networks (FC-DNN) to classify drivers’ styles and skills with naturalistic driving data. Followed by the data collection and pre-processing, FC-DNN with a series of deep learning optimization algorithms are applied. In the experimental part, the proposed model is validated and compared with other commonly used supervised learning methods including the k-nearest neighbors (KNN), support vector machine (SVM), decision tree (DT), random forest (RF), and multilayer perceptron (MLP). The results show that the proposed model has a higher Macro F1 score than other methods. In addition, we discussed the effect of different time window sizes on experimental results. The results show that the driving information of 1s can improve the final evaluation score of the model.
Technical Paper

A Lane Departure Estimating Algorithm Based on Camera Vision, Inertial Navigation Sensor and GPS Data

In this paper, a sensor fusion approach is introduced to estimate lane departure. The proposed algorithm combines the camera, inertial navigation sensor, and GPS data with the vehicle dynamics to estimate the vehicle path and the lane departure time. The lane path and vehicle path are estimated by using Kalman filters. This algorithm can be used to provide early warning for lane departure in order to increase driving safety. By integrating inertial navigation sensor and GPS data, the inertial sensor biases can be estimated and the vehicle path can be estimated where the GPS data is not available or is poor. Additionally, the algorithm can be used to reduce the latency of information embedded in the controls, so that the vehicle lateral control performance can be significantly improved during lane keeping in Advanced Driver Assistance Systems (ADAS) or autonomous vehicles. Furthermore, it improves lane detection reliability in situations when camera fails to detect lanes.
Technical Paper

A Maneuver-Based Threat Assessment Strategy for Collision Avoidance

Advanced driver assistance systems (ADAS) are being developed for more and more complicated application scenarios, which often require more predictive strategies with better understanding of driving environment. Taking traffic vehicles’ maneuvers into account can greatly expand the beforehand time span for danger awareness. This paper presents a maneuver-based strategy to vehicle collision threat assessment. First, a maneuver-based trajectory prediction model (MTPM) is built, in which near-future trajectories of ego vehicle and traffic vehicles are estimated with the combination of vehicle’s maneuvers and kinematic models that correspond to every maneuver. The most probable maneuvers of ego vehicle and each traffic vehicles are modeled and inferred via Hidden Markov Models with mixture of Gaussians outputs (GMHMM). Based on the inferred maneuvers, trajectory sets consisting of vehicles’ position and motion states are predicted by kinematic models.
Technical Paper

A Method for Camera Vision Based Parking Spot Detection

A main requirement for a driver assisting automated parking system is the identification and localisation of a free parking spot. A sensory system consisting of a reverse aid camera, a processing unit, vehicle track sensors and a link to the vehicles CAN-Bus is able to detect a parking spot, using vision processing algorithms. This report starts with a case differentiation regarding parking situations. In reality a combination between several attributes and conditions define the initial parking situation and the specific demand on the sensory system to detect the parking spot. The described method for camera vision based parking spot detection is characterised on specific situations, such as parking spots marked by painted lines and the kerbstone and well lighted rich-contrast situations. The method in general starts with the image processing on the incoming camera images.
Journal Article

A Method of Frequency Content Based Analysis of Driving Braking Behavior

Typically, when one thinks of advanced driver assistance systems (ADAS), systems such as Forward Collision Warning (FCW) and Collision Imminent Braking (CIB) come to mind. In these systems driver assistance is provided based on knowledge about the subject vehicle and surrounding objects. A new class of these systems is being implemented. These systems not only use information on the surrounding objects but also use information on the driver's response to an event, to determine if intervention is necessary. As a result of this trend, an advanced level of understanding of driver braking behavior is necessary. This paper presents an alternate method of analyzing driver braking behavior. This method uses a frequency content based approach to study driver braking and allows for the extraction of significantly more data from driver profiles than traditionally would have been done.
Technical Paper

A Methodology for Threat Assessment in Cut-in Vehicle Scenarios

Advanced Driver Assistance System (ADAS) has become a common standard feature assisting greater safety and fuel efficiency in the latest automobiles. Yet some ADAS systems fail to improve driving comfort for vehicle occupants who expect human-like driving. One of the more difficult situations in ADAS-assisted driving involves instances with cut-in vehicles. In vehicle control, determining the moment at which the system recognizes a cut-in vehicle as an active target is a challenging task. A well-designed comprehensive threat assessment developed for cut-in vehicle driving scenarios should eliminate abrupt and excessive deceleration of the vehicle and produce a smooth and safe driving experience. This paper proposes a novel methodology for threat assessment for driving instances involving a cut-in vehicle. The methodology takes into consideration kinematics, vehicle dynamics, vehicle stability, road condition, and driving comfort.
Technical Paper

A Model Based Control Strategy for an Electric Power Assisted Steering

Automotive industry is looking for new design and product development practices to become more competitive. Challenges in current global market have often included sustainable development, environmental regulation and innovative solution to reach customer needs. Today, carmakers are striving to take competitive advantages over global marketplace. Model-Based-Design (MBD) seems to be a feasible answer to improve software development practices in automotive industry. Furthermore, it has been reported as a novel development approach to develop advanced driver assistance systems (ADAS). Among ADAS technologies often required to reduce driver fatigue is Electric Power Assisted Steering (EPAS). By using an auxiliary servomotor, it can reduce significantly driver effort in parking maneuvers. In this scenario, this paper aims to describe how MBD can be used to design EPAS control system.