scholarly journals Performance Guarantees for Hazard Based Lateral Vehicle Control

2002 ◽  
Author(s):  
Eric J. Rossetter ◽  
J. Christian Gerdes
Keyword(s):  
Control Force ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Driving Experience ◽  
The Road ◽  
Performance Guarantees ◽  
System A ◽  
Assistance Systems ◽  
On The Road ◽  
Near Future

Today’s vehicles are incorporating many advanced driver assistance systems and in the near future it will be likely to have increased capabilities such as lanekeeping assist systems. These systems will be an integral part of the driving experience, aiding the driver in avoiding hazardous obstacles. One approach for these systems is to represent the hazards as artificial potential fields that add control inputs to move the vehicle towards safe regions on the road. This paper focuses on bounding the lateral motion of a vehicle for a lanekeeping system. A Lyapunov approach is used where the bounding function consists of the artificial potential energy associated with the controller, the kinetic energy in the lateral and yaw modes, and energy terms that are dependent on vehicle heading. In order to achieve this bound, a condition has to be met for the lookahead distance and the location of the control force (which can also be interpreted as a condition on the decoupling of lateral and yaw modes). Using this bound, a potential field gain can be chosen to guarantee collision avoidance with fixed lateral obstacles.

scholarly journals Implementing a Gaze Tracking Algorithm for Improving Advanced Driver Assistance Systems

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1480
Author(s):  
Agapito Ledezma ◽  
Víctor Zamora ◽  
Óscar Sipele ◽  
M. Paz Sesmero ◽  
Araceli Sanchis
Keyword(s):  
Traffic Accidents ◽  
Tracking System ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Gaze Tracking ◽  
Advanced Driver Assistance Systems ◽  
The Road ◽  
Assistance Systems ◽  
On The Road ◽  
Driver Distractions

Car accidents are one of the top ten causes of death and are produced mainly by driver distractions. ADAS (Advanced Driver Assistance Systems) can warn the driver of dangerous scenarios, improving road safety, and reducing the number of traffic accidents. However, having a system that is continuously sounding alarms can be overwhelming or confusing or both, and can be counterproductive. Using the driver’s attention to build an efficient ADAS is the main contribution of this work. To obtain this “attention value” the use of a Gaze tracking is proposed. Driver’s gaze direction is a crucial factor in understanding fatal distractions, as well as discerning when it is necessary to warn the driver about risks on the road. In this paper, a real-time gaze tracking system is proposed as part of the development of an ADAS that obtains and communicates the driver’s gaze information. The developed ADAS uses gaze information to determine if the drivers are looking to the road with their full attention. This work gives a step ahead in the ADAS based on the driver, building an ADAS that warns the driver only in case of distraction. The gaze tracking system was implemented as a model-based system using a Kinect v2.0 sensor and was adjusted on a set-up environment and tested on a suitable-features driving simulation environment. The average obtained results are promising, having hit ratios between 96.37% and 81.84%.

Improved Vision Based Driving Space Analysis by Condensation of Image Data

2012 ◽  
Vol 605-607 ◽  
pp. 2260-2264
Author(s):  
Yan Fen Mao ◽  
Hans Wiedmann ◽  
Ming Chen
Keyword(s):  
Image Data ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
The Road ◽  
Detection And Tracking ◽  
Detection And Identification ◽  
Diversity Sampling ◽  
Assistance Systems ◽  
On The Road ◽  
Improve Reliability

Sophisticated ADAS (Advanced Driver Assistance Systems) use vision based methods for detection and keeping track of ahead driving cars. With thus acquired data it is possible to implement e.g. following up functions to automatically keep equal distance to ahead driving vehicles or avoid collisions with obstacles ahead. Known vision based methods for detection and tracking of vehicles use its underneath shadow on the road. The main drawbacks of those methods are the detection and identification of a shadow belonging to a vehicle is neither reliable nor robust, and the thereto required processing of the camera images is very expensive concerning processing time. To improve reliability and detectability we propose here to use an approach which is different from the known methods a nonparametric one; to improve processing speed we propose to apply diversity-sampling to condense the image data before processing it.

scholarly journals Advanced Driver Assistant Systems Focused on Pedestrians’ Safety: A User Experience Approach

2021 ◽  
Vol 13 (8) ◽  
pp. 4264
Author(s):  
Matúš Šucha ◽  
Ralf Risser ◽  
Kristýna Honzíčková
Keyword(s):  
Autonomous Vehicles ◽  
Qualitative Data ◽  
Expert Interviews ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Assistant Systems ◽  
Vehicle Technology ◽  
Assistance Systems ◽  
Technical Solutions ◽  
Near Future

Globally, pedestrians represent 23% of all road deaths. Many solutions to protect pedestrians are proposed; in this paper, we focus on technical solutions of the ADAS–Advanced Driver Assistance Systems–type. Concerning the interaction between drivers and pedestrians, we want to have a closer look at two aspects: how to protect pedestrians with the help of vehicle technology, and how pedestrians–but also car drivers–perceive and accept such technology. The aim of the present study was to analyze and describe the experiences, needs, and preferences of pedestrians–and drivers–in connection with ADAS, or in other words, how ADAS should work in such a way that it would protect pedestrians and make walking more relaxed. Moreover, we interviewed experts in the field in order to check if, in the near future, the needs and preferences of pedestrians and drivers can be met by new generations of ADAS. A combination of different methods, specifically, an original questionnaire, on-the-spot interviewing, and expert interviews, was used to collect data. The qualitative data was analyzed using qualitative text analysis (clustering and categorization). The questionnaire for drivers was answered by a total of 70 respondents, while a total of 60 pedestrians agreed to complete questionnaires concerning pedestrian safety. Expert interviews (five interviews) were conducted by means of personal interviews, approximately one hour in duration. We conclude that systems to protect pedestrians–to avoid collisions of cars with pedestrians–are considered useful by all groups, though with somewhat different implications. With respect to the features of such systems, the considerations are very heterogeneous, and experimentation is needed in order to develop optimal systems, but a decisive argument put forward by some of the experts is that autonomous vehicles will have to be programmed extremely defensively. Given this argument, we conclude that we will need more discussion concerning typical interaction situations in order to find solutions that allow traffic to work both smoothly and safely.

Analysis of Preference for Autonomous Driving Under Different Traffic Conditions Using a Driving Simulator

2015 ◽  
Vol 27 (6) ◽  
pp. 660-670 ◽  
Author(s):  
Udara Eshan Manawadu ◽  
◽  
Masaaki Ishikawa ◽  
Mitsuhiro Kamezaki ◽  
Shigeki Sugano ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Driving Simulator ◽  
Autonomous Driving ◽  
Driving Experience ◽  
The Road ◽  
Traffic Conditions ◽  
Passenger Vehicles ◽  
New Type ◽  
On The Road ◽  
Near Future

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00270006/08.jpg"" width=""300"" /> Driving simulator</div>Intelligent passenger vehicles with autonomous capabilities will be commonplace on our roads in the near future. These vehicles will reshape the existing relationship between the driver and vehicle. Therefore, to create a new type of rewarding relationship, it is important to analyze when drivers prefer autonomous vehicles to manually-driven (conventional) vehicles. This paper documents a driving simulator-based study conducted to identify the preferences and individual driving experiences of novice and experienced drivers of autonomous and conventional vehicles under different traffic and road conditions. We first developed a simplified driving simulator that could connect to different driver-vehicle interfaces (DVI). We then created virtual environments consisting of scenarios and events that drivers encounter in real-world driving, and we implemented fully autonomous driving. We then conducted experiments to clarify how the autonomous driving experience differed for the two groups. The results showed that experienced drivers opt for conventional driving overall, mainly due to the flexibility and driving pleasure it offers, while novices tend to prefer autonomous driving due to its inherent ease and safety. A further analysis indicated that drivers preferred to use both autonomous and conventional driving methods interchangeably, depending on the road and traffic conditions.

scholarly journals Design Method of ADAS for Urban Electric Vehicle Based on Virtual Prototyping

2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Katarzyna Jezierska-Krupa ◽  
Wojciech Skarka
Keyword(s):  
Design Method ◽  
Virtual Prototyping ◽  
Real Life ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Smart Power ◽  
The Road ◽  
Unique Method ◽  
On The Road ◽  
Positive Effect

Since 2012, the Smart Power Team has been actively participating in the Shell Eco-marathon, which is a worldwide competition. From the very beginning, the team has been working to increase driver’s safety on the road by developing Advanced Driver Assistance Systems. This paper presents unique method for designing ADAS systems in order to minimize the costs of the design phase and system implementation and, at the same time, to maximize the positive effect the system has on driver and vehicle safety. The described method is based on using virtual prototyping tool to simulate the system performance in real-life situations. This approach enabled an iterative design process, which resulted in reduction of errors with almost no prototyping and testing costs.

scholarly journals Can ADAS Distract Driver’s Attention? An RGB-D Camera and Deep Learning-Based Analysis

2021 ◽  
Vol 11 (24) ◽  
pp. 11587
Author(s):  
Luca Ulrich ◽  
Francesca Nonis ◽  
Enrico Vezzetti ◽  
Sandro Moos ◽  
Giandomenico Caruso ◽  
...  
Keyword(s):  
Deep Learning ◽  
Expression Recognition ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Driving Experience ◽  
Vehicle Accidents ◽  
Non Invasive ◽  
Driver Inattention ◽  
Assistance Systems ◽  
Invasive Techniques

Driver inattention is the primary cause of vehicle accidents; hence, manufacturers have introduced systems to support the driver and improve safety; nonetheless, advanced driver assistance systems (ADAS) must be properly designed not to become a potential source of distraction for the driver due to the provided feedback. In the present study, an experiment involving auditory and haptic ADAS has been conducted involving 11 participants, whose attention has been monitored during their driving experience. An RGB-D camera has been used to acquire the drivers’ face data. Subsequently, these images have been analyzed using a deep learning-based approach, i.e., a convolutional neural network (CNN) specifically trained to perform facial expression recognition (FER). Analyses to assess possible relationships between these results and both ADAS activations and event occurrences, i.e., accidents, have been carried out. A correlation between attention and accidents emerged, whilst facial expressions and ADAS activations resulted to be not correlated, thus no evidence that the designed ADAS are a possible source of distraction has been found. In addition to the experimental results, the proposed approach has proved to be an effective tool to monitor the driver through the usage of non-invasive techniques.

scholarly journals Detection and Tracking of Road Barrier Based on Radar and Vision Sensor Fusion

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Taeryun Kim ◽  
Bongsob Song
Keyword(s):  
Lateral Position ◽  
Vision Sensor ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
The Road ◽  
Estimation Algorithms ◽  
Detection And Tracking ◽  
First Case ◽  
Lateral Distance ◽  
Assistance Systems

The detection and tracking algorithms of road barrier including tunnel and guardrail are proposed to enhance performance and reliability for driver assistance systems. Although the road barrier is one of the key features to determine a safe drivable area, it may be recognized incorrectly due to performance degradation of commercial sensors such as radar and monocular camera. Two frequent cases among many challenging problems are considered with the commercial sensors. The first case is that few tracks of radar to road barrier are detected due to material type of road barrier. The second one is inaccuracy of relative lateral position by radar, thus resulting in large variance of distance between a vehicle and road barrier. To overcome the problems, the detection and estimation algorithms of tracks corresponding to road barrier are proposed. Then, the tracking algorithm based on a probabilistic data association filter (PDAF) is used to reduce variation of lateral distance between vehicle and road barrier. Finally, the proposed algorithms are validated via field test data and their performance is compared with that of road barrier measured by lidar.

scholarly journals The choice of rational complex of active safety systems for smart cars

2021 ◽  
Vol 2061 (1) ◽  
pp. 012128
Author(s):  
A I Markovnina ◽  
N D Tsyganov ◽  
A V Papunin ◽  
V S Makarov ◽  
V V Belyakov
Keyword(s):  
Road Safety ◽  
Vehicle Safety ◽  
Active Safety ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
The Road ◽  
Active Safety Systems ◽  
Assistance Systems ◽  
Smart Cars ◽  
Safety Systems

Abstract The problem of ensuring road safety affects all elements of the Driver-Car-Road-Environment system. Smart cars equipped with enough traffic assistants can significantly improve road safety. Active vehicle safety systems, including intelligent driver assistance systems and assistants, perform similar road safety functions. With all the variety of possibilities for equipping cars with systems complexes, the need arises to assess the feasibility and profitability of installing a particular complex of systems. For this, it is proposed to apply the methods of multi-criteria assessment. As a result of calculations, the best options for the sets of systems that most widely cover the road situation have been identified.

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