Advanced Driver Assistance System Car Following Model Optimization Framework Using Genetic Algorithm Implemented In Sumo Traffic Simulation

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Advanced Driver Assistance System Car Following Model Optimization Framework Using Genetic Algorithm Implemented in Sumo Traffic Simulation

Author : Matt J Carroll
Publisher :
ISBN 13 :
Total Pages : 52 pages
Book Rating : 4.:/5 (133 download)

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Book Synopsis Advanced Driver Assistance System Car Following Model Optimization Framework Using Genetic Algorithm Implemented in Sumo Traffic Simulation by : Matt J Carroll

Download or read book Advanced Driver Assistance System Car Following Model Optimization Framework Using Genetic Algorithm Implemented in Sumo Traffic Simulation written by Matt J Carroll and published by . This book was released on 2022 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: As advanced driver-assistance systems (ADAS) such as smart cruise control and lane keepinghave become common technologies, self-driving above SAE level 3 are being competitivelydeveloped by major automobile manufacturers, autonomous vehicles (AVs) will prevail inthe near future traffic network. In particular, evasive action algorithms with collision detec-tion by sensors and faster braking response will enable AVs to drive with a shorter gap athigher speeds which has not been possible with human drivers. Such technologies will be ableto improve current traffic performance as long as raising concerns on safety are addressed. Therefore, there have been efforts to improve understanding between stakeholders such asregulatory authorities and developers to draw a consensus about autonomous driving stan-dard and regulations. Meanwhile, a mixed traffic network with human driving vehicles andAVs will show transient system behavior based on penetration rate of AVs thereby requiringdifferent optimal AV settings. We are interested in understanding this system behavior overtransitional period to achieve an optimal traffic performance with safety as a hard constraint. We investigate the system behavior with agent-based simulation with different penetrationrates by mixing of human-driving and AV vehicle models, identify the key parameters ofADAS algorithms for traffic flow, and find the optimal parameter set per penetration rateby using genetic algorithm (GA). Simulation results with optimal parameter values revealimprovement in average traffic performance measures such as flow (5.6% increase), speed(4.9% increase), density (15.9% decrease), and waiting time (48.2% decrease). We providesimulation examples and discuss the implication of the optimal parameter values for bothtraffic control authorities and AV developers during the transitional period.

Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions

Author : Harald Waschl
Publisher : Springer
ISBN 13 : 331991569X
Total Pages : 235 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions by : Harald Waschl

Download or read book Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions written by Harald Waschl and published by Springer. This book was released on 2018-06-28 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes different methods that are relevant to the development and testing of control algorithms for advanced driver assistance systems (ADAS) and automated driving functions (ADF). These control algorithms need to respond safely, reliably and optimally in varying operating conditions. Also, vehicles have to comply with safety and emission legislation. The text describes how such control algorithms can be developed, tested and verified for use in real-world driving situations. Owing to the complex interaction of vehicles with the environment and different traffic participants, an almost infinite number of possible scenarios and situations that need to be considered may exist. The book explains new methods to address this complexity, with reference to human interaction modelling, various theoretical approaches to the definition of real-world scenarios, and with practically-oriented examples and contributions, to ensure efficient development and testing of ADAS and ADF. Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions is a collection of articles by international experts in the field representing theoretical and application-based points of view. As such, the methods and examples demonstrated in the book will be a valuable source of information for academic and industrial researchers, as well as for automotive companies and suppliers.

Vehicle Systems and Driver Modelling

Author : Huseyin Abut
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 1501504169
Total Pages : 271 pages
Book Rating : 4.5/5 (15 download)

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Book Synopsis Vehicle Systems and Driver Modelling by : Huseyin Abut

Download or read book Vehicle Systems and Driver Modelling written by Huseyin Abut and published by Walter de Gruyter GmbH & Co KG. This book was released on 2017-09-11 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: World-class experts from academia and industry assembled at the sixth Biennial Workshop on Digital Signal Processing (DSP) for In-Vehicle Systems at Korea University, Seoul, Korea in 2013. The Workshop covered a wide spectrum of automotive fields, including in-vehicle signal processing and cutting-edge studies on safety, driver behavior, infrastructure, in-vehicle technologies. Contributors to this volume have expanded their contributions to the Workshop into full chapters with related works, methodology, experiments, and the analysis of the findings. Topics in this volume include: DSP technologies for in-vehicle systems Driver status and behavior monitoring In-Vehicle dialogue systems and human machine interfaces In-vehicle video and applications for safety Passive and active driver assistance technologies Ideas and systems for autonomous driving Transportation infrastructure

Advances in Intelligent Vehicles

Author : Yaobin Chen
Publisher : Academic Press
ISBN 13 : 0123973279
Total Pages : 333 pages
Book Rating : 4.1/5 (239 download)

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Book Synopsis Advances in Intelligent Vehicles by : Yaobin Chen

Download or read book Advances in Intelligent Vehicles written by Yaobin Chen and published by Academic Press. This book was released on 2014-03-20 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Intelligent Vehicles presents recent advances in intelligent vehicle technologies that enhance the safety, reliability, and performance of vehicles and vehicular networks and systems. This book provides readers with up-to-date research results and cutting-edge technologies in the area of intelligent vehicles and transportation systems. Topics covered include virtual and staged testing scenarios, collision avoidance, human factors, and modeling techniques. The Series in Intelligent Systems publishes titles that cover state-of-the-art knowledge and the latest advances in research and development in intelligent systems. Its scope includes theoretical studies, design methods, and real-world implementations and applications. - Provides researchers and engineers with up-to-date research results and state-of-the art technologies in the area of intelligent vehicles and transportation systems - Covers hot topics, including driver assistance systems; cooperative vehicle-highway systems; collision avoidance; pedestrian protection; image, radar and lidar signal processing; and V2V and V2I communications

Machine Learning in Advanced Driver-assistance Systems

Author : Farzin Ghorban
Publisher :
ISBN 13 : 9783832548742
Total Pages : 0 pages
Book Rating : 4.5/5 (487 download)

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Book Synopsis Machine Learning in Advanced Driver-assistance Systems by : Farzin Ghorban

Download or read book Machine Learning in Advanced Driver-assistance Systems written by Farzin Ghorban and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the context of advanced driver-assistance systems (ADAS), vehicles are equipped with multiple sensors to record the vehicle's environment and use intelligent algorithms to understand the data. This study contributes to the research in modern ADAS on different aspects. Methods deployed in ADAS must be accurate and computationally efficient in order to run fast on embedded platforms. We introduce a novel approach for pedestrian detection that economizes on the computational cost of cascades. We demonstrate that (a) our two-stage cascade achieves a high accuracy while running in real time, and (b) our three-stage cascade ranks as the fourth best-performing method on one of the most challenging pedestrian datasets. The other challenge faced with ADAS is the scarcity of positive training data. We introduce a novel approach that enables AdaBoost detectors to benefit from a high number of negative samples. We demonstrate that our approach ranks as the second-best among its competitors on two challenging pedestrian datasets while being multiple times faster. Acquiring labeled training data is costly and time-consuming, particularly for traffic sign recognition. We investigate the use of synthetic data with the aspiration to reduce the human efforts behind the data preparation. We (a) algorithmically and architecturally adapt the adversarial modeling framework to the image data provided in ADAS, and (b) conduct various evaluations and discuss promising future research directions.

Deep Long Short-term Memory Network Embedded Connected Automated Car-following Model Predictive Control Strategy

Author : Zhen Zhang
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis Deep Long Short-term Memory Network Embedded Connected Automated Car-following Model Predictive Control Strategy by : Zhen Zhang

Download or read book Deep Long Short-term Memory Network Embedded Connected Automated Car-following Model Predictive Control Strategy written by Zhen Zhang and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent years, autonomous vehicle (AV) technology, which is expected to solve critical issues, such as traffic efficiency, capacity, and safety, has been put a lot of efforts and making considerable progress. It utilizes data from various sensors for sensing, prediction, and control tasks. Another related technology that also has significant impacts on transportation is connected vehicle (CV). With the assistance of dedicated short-range communication devices, CV communicates with other vehicles in the system or roadside infrastructure to get valuable information about surroundings. Combining these technologies together, connected and automated vehicle (CAV) can further enhance the AV benefits in various ways, such as safety and efficiency. Towards to fully automation, one of most important areas is the advanced driver-assistance systems, especially the longitudinal control. Since the manual vehicles will still dominate the road for a long time, how to perform the longitudinal control for a CAV is a critical problem to be solved for mixed traffic consisting of CAVs and manual vehicles. Model Predictive Control (MPC) is a modern control framework that has been extensively studied across various fields. There is also plenty of research applying MPC to control the vehicle in full CAV environments. However, due to the lack of communication with the preceding manual vehicle, CAV is not able to attain the planning of the leading vehicle's control actions, which is critically needed by MPC controller. The emerging deep learning techniques have demonstrated promising capability in various domains, including traffic prediction. This research focuses on developing a novel car-following control strategy for a platoon of CAVs and manual vehicles. Specifically, it controls those CAVs following another manual vehicle in this platoon and enhance the stability. The proposed longitudinal control strategy is designed in MPC manner, embedded with deep-learning enhanced prediction. This dissertation first conducts a comprehensive review on car-following models and MPC theories and applications on vehicle control. Then a novel control strategy is developed to enhance the efficiency and stability of controlling CAVs in mixed traffic. There are two major parts in this strategy. One is trajectory prediction model, and the other is MPC controller. Two different deep long-short-term-memory (LSTM) based models are designed and evaluated for two potential control scenarios, taking advantages of new deep learning technology. Embedded with deep learning models, MPC controller is formulated with consideration of safety, efficiency, and driving comfort. Several experiments are carried out to analyze the performance of trajectory prediction models and proposed control strategy and results show promising potential.

Advanced Driver Assistance Systems and Autonomous Vehicles

Author : Yan Li
Publisher : Springer Nature
ISBN 13 : 9811950539
Total Pages : 628 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Advanced Driver Assistance Systems and Autonomous Vehicles by : Yan Li

Download or read book Advanced Driver Assistance Systems and Autonomous Vehicles written by Yan Li and published by Springer Nature. This book was released on 2022-10-28 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive reference for both academia and industry on the fundamentals, technology details, and applications of Advanced Driver-Assistance Systems (ADAS) and autonomous driving, an emerging and rapidly growing area. The book written by experts covers the most recent research results and industry progress in the following areas: ADAS system design and test methodologies, advanced materials, modern automotive technologies, artificial intelligence, reliability concerns, and failure analysis in ADAS. Numerous images, tables, and didactic schematics are included throughout. This essential book equips readers with an in-depth understanding of all aspects of ADAS, providing insights into key areas for future research and development. • Provides comprehensive coverage of the state-of-the-art in ADAS • Covers advanced materials, deep learning, quality and reliability concerns, and fault isolation and failure analysis • Discusses ADAS system design and test methodologies, novel automotive technologies • Features contributions from both academic and industry authors, for a complete view of this important technology

Algorithm & SoC Design for Automotive Vision Systems

Author : Jaeseok Kim
Publisher : Springer
ISBN 13 : 9401790752
Total Pages : 296 pages
Book Rating : 4.4/5 (17 download)

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Book Synopsis Algorithm & SoC Design for Automotive Vision Systems by : Jaeseok Kim

Download or read book Algorithm & SoC Design for Automotive Vision Systems written by Jaeseok Kim and published by Springer. This book was released on 2014-06-29 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: An emerging trend in the automobile industry is its convergence with information technology (IT). Indeed, it has been estimated that almost 90% of new automobile technologies involve IT in some form. Smart driving technologies that improve safety as well as green fuel technologies are quite representative of the convergence between IT and automobiles. The smart driving technologies include three key elements: sensing of driving environments, detection of objects and potential hazards and the generation of driving control signals including warning signals. Although radar-based systems are primarily used for sensing the driving environments, the camera has gained importance in advanced driver assistance systems (ADAS). This book covers system-on-a-chip (SoC) designs—including both algorithms and hardware—related with image sensing and object detection by using the camera for smart driving systems. It introduces a variety of algorithms such as lens correction, super resolution, image enhancement and object detections from the images captured by low-cost vehicle camera. This is followed by implementation issues such as SoC architecture, hardware accelerator, software development environment and reliability techniques for automobile vision systems. This book is aimed for the new and practicing engineers in automotive and chip-design industries to provide some overall guidelines for the development of automotive vision systems. It will also help graduate students understand and get started for the research work in this field.

Vehicles, Drivers, and Safety

Author : John Hansen
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 311066657X
Total Pages : 274 pages
Book Rating : 4.1/5 (16 download)

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Book Synopsis Vehicles, Drivers, and Safety by : John Hansen

Download or read book Vehicles, Drivers, and Safety written by John Hansen and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-05-05 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents works from world-class experts from academia, industry, and national agencies representing countries from across the world focused on automotive fields for in-vehicle signal processing and safety. These include cutting-edge studies on safety, driver behavior, infrastructure, and human-to-vehicle interfaces. Vehicle Systems, Driver Modeling and Safety is appropriate for researchers, engineers, and professionals working in signal processing for vehicle systems, next generation system design from driver-assisted through fully autonomous vehicles.

Behavior Analysis and Modeling of Traffic Participants

Author : Xiaolin Song
Publisher : Springer Nature
ISBN 13 : 3031015096
Total Pages : 160 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Behavior Analysis and Modeling of Traffic Participants by : Xiaolin Song

Download or read book Behavior Analysis and Modeling of Traffic Participants written by Xiaolin Song and published by Springer Nature. This book was released on 2022-06-01 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: A road traffic participant is a person who directly participates in road traffic, such as vehicle drivers, passengers, pedestrians, or cyclists, however, traffic accidents cause numerous property losses, bodily injuries, and even deaths to them. To bring down the rate of traffic fatalities, the development of the intelligent vehicle is a much-valued technology nowadays. It is of great significance to the decision making and planning of a vehicle if the pedestrians' intentions and future trajectories, as well as those of surrounding vehicles, could be predicted, all in an effort to increase driving safety. Based on the image sequence collected by onboard monocular cameras, we use the Long Short-Term Memory (LSTM) based network with an enhanced attention mechanism to realize the intention and trajectory prediction of pedestrians and surrounding vehicles. However, although the fully automatic driving era still seems far away, human drivers are still a crucial part of the road‒driver‒vehicle system under current circumstances, even dealing with low levels of automatic driving vehicles. Considering that more than 90 percent of fatal traffic accidents were caused by human errors, thus it is meaningful to recognize the secondary task while driving, as well as the driving style recognition, to develop a more personalized advanced driver assistance system (ADAS) or intelligent vehicle. We use the graph convolutional networks for spatial feature reasoning and the LSTM networks with the attention mechanism for temporal motion feature learning within the image sequence to realize the driving secondary-task recognition. Moreover, aggressive drivers are more likely to be involved in traffic accidents, and the driving risk level of drivers could be affected by many potential factors, such as demographics and personality traits. Thus, we will focus on the driving style classification for the longitudinal car-following scenario. Also, based on the Structural Equation Model (SEM) and Strategic Highway Research Program 2 (SHRP 2) naturalistic driving database, the relationships among drivers' demographic characteristics, sensation seeking, risk perception, and risky driving behaviors are fully discussed. Results and conclusions from this short book are expected to offer potential guidance and benefits for promoting the development of intelligent vehicle technology and driving safety.

Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS)

Author : John Ball
Publisher : MDPI
ISBN 13 : 303921375X
Total Pages : 342 pages
Book Rating : 4.0/5 (392 download)

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Book Synopsis Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS) by : John Ball

Download or read book Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS) written by John Ball and published by MDPI. This book was released on 2019-10-01 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the latest research on machine learning and embedded computing in advanced driver assistance systems (ADAS). It encompasses research in detection, tracking, LiDAR and camera processing, ethics, and communications. Several new datasets are also provided for future research work. Researchers and others interested in these topics will find important advances contained in this book.

Towards Human-Vehicle Harmonization

Author : Huseyin Abut
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110981319
Total Pages : 490 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Towards Human-Vehicle Harmonization by : Huseyin Abut

Download or read book Towards Human-Vehicle Harmonization written by Huseyin Abut and published by Walter de Gruyter GmbH & Co KG. This book was released on 2023-03-20 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features works from world-class experts from academia, industry, and national agencies focusing on a wide spectrum of automotive fields towards humanvehicle harmonization covering in-vehicle signal processing, driver modeling, systems and safety. The essays collected in this volume present cutting-edge studies on safety, driver behavior, infrastructure, and human-to-vehicle interfaces.

Development of a Car-following Model to Simulate Driver and Autonomous Intelligent Cruise Controlled Vehicular Traffic Flow

Author : Murat Fahrettin Aycin
Publisher :
ISBN 13 :
Total Pages : 520 pages
Book Rating : 4.:/5 (486 download)

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Book Synopsis Development of a Car-following Model to Simulate Driver and Autonomous Intelligent Cruise Controlled Vehicular Traffic Flow by : Murat Fahrettin Aycin

Download or read book Development of a Car-following Model to Simulate Driver and Autonomous Intelligent Cruise Controlled Vehicular Traffic Flow written by Murat Fahrettin Aycin and published by . This book was released on 2001 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Fundamentals of Traffic Simulation

Author : Jaume Barceló
Publisher : Springer Science & Business Media
ISBN 13 : 1441961429
Total Pages : 450 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Fundamentals of Traffic Simulation by : Jaume Barceló

Download or read book Fundamentals of Traffic Simulation written by Jaume Barceló and published by Springer Science & Business Media. This book was released on 2011-01-06 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increasing power of computer technologies, the evolution of software en- neering and the advent of the intelligent transport systems has prompted traf c simulation to become one of the most used approaches for traf c analysis in s- port of the design and evaluation of traf c systems. The ability of traf c simulation to emulate the time variability of traf c phenomena makes it a unique tool for capturing the complexity of traf c systems. In recent years, traf c simulation – and namely microscopic traf c simulation – has moved from the academic to the professional world. A wide variety of traf- c simulation software is currently available on the market and it is utilized by thousands of users, consultants, researchers and public agencies. Microscopic traf c simulation based on the emulation of traf c ows from the dynamics of individual vehicles is becoming one the most attractive approaches. However, traf c simulation still lacks a uni ed treatment. Dozens of papers on theory and applications are published in scienti c journals every year. A search of simulation-related papers and workshops through the proceedings of the last annual TRB meetings would support this assertion, as would a review of the minutes from speci cally dedicated meetings such as the International Symposiums on Traf c Simulation (Yokohama, 2002; Lausanne, 2006; Brisbane, 2008) or the International Workshops on Traf c Modeling and Simulation (Tucson, 2001; Barcelona, 2003; Sedona, 2005; Graz 2008). Yet, the only comprehensive treatment of the subject to be found so far is in the user’s manuals of various software products.

Traffic Flow Dynamics

Author : Martin Treiber
Publisher : Springer Science & Business Media
ISBN 13 : 3642324592
Total Pages : 505 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Traffic Flow Dynamics by : Martin Treiber

Download or read book Traffic Flow Dynamics written by Martin Treiber and published by Springer Science & Business Media. This book was released on 2012-10-11 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive and instructive coverage of vehicular traffic flow dynamics and modeling. It makes this fascinating interdisciplinary topic, which to date was only documented in parts by specialized monographs, accessible to a broad readership. Numerous figures and problems with solutions help the reader to quickly understand and practice the presented concepts. This book is targeted at students of physics and traffic engineering and, more generally, also at students and professionals in computer science, mathematics, and interdisciplinary topics. It also offers material for project work in programming and simulation at college and university level. The main part, after presenting different categories of traffic data, is devoted to a mathematical description of the dynamics of traffic flow, covering macroscopic models which describe traffic in terms of density, as well as microscopic many-particle models in which each particle corresponds to a vehicle and its driver. Focus chapters on traffic instabilities and model calibration/validation present these topics in a novel and systematic way. Finally, the theoretical framework is shown at work in selected applications such as traffic-state and travel-time estimation, intelligent transportation systems, traffic operations management, and a detailed physics-based model for fuel consumption and emissions.

Behavior Modeling and Motion Planning for Autonomous Driving Using Artificial Intelligence

Author : Meixin Zhu
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (14 download)

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Book Synopsis Behavior Modeling and Motion Planning for Autonomous Driving Using Artificial Intelligence by : Meixin Zhu

Download or read book Behavior Modeling and Motion Planning for Autonomous Driving Using Artificial Intelligence written by Meixin Zhu and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With an emphasis on longitudinal driving, this dissertation aims to develop data-driven models that improve existing driving behavior models and facilitate various kinds of autonomous driving planning. The first part of this work focuses on behavior modeling, which falls within the background of microscopic traffic simulation, traffic flow theory, and motion prediction. Two different driving behavior models are proposed. To model the long-term dependency of future actions on historical driving situations, a long-sequence car-following trajectory prediction model is developed using the attention-based Transformer model. The model follows a general format of encoder-decoder architecture. The encoder takes historical speed and spacing data as inputs and forms a mixed representation of historical driving context using multi-head self-attention. The decoder takes the future lead vehicle speed profile as input and outputs the predicted future following speed profile in a generative way (instead of an auto-regressive way, avoiding compounding errors). The second part of this work extends the single forward-pass of behavior prediction in the first part to the sequential motion planning of autonomous driving. Based on different demands, two motion planning algorithms are proposed for autonomous longitudinal driving. To learn a driving policy that can do closed-loop sequential planning and imitate human drivers' behavior, a framework for human-like autonomous car-following planning based on deep reinforcement learning (RL) is proposed. Car-following dynamics are encoded into a simulation environment, and a reward function that signals how much the agent deviates from the empirical data is used to encourage behavioral imitation. It was found that using RL for imitation learning purposes can well address the distribution shift issue. This is the first study that uses RL to address the distribution shift issue for imitation-orientated longitudinal motion planning. To propose a safe, efficient, and comfortable velocity planning method for autonomous driving, a multi-objective velocity planning method based on RL is proposed. To directly optimize driving performance, a reward function is developed by referencing human driving data and combining driving features related to safety, efficiency, and comfort. It was found that the proposed model demonstrates the capability of safe, efficient, and comfortable velocity control and outperforms human drivers.

Modeling of specific safety-critical driving scenarios for data synthesis in the context of autonomous driving software

Author : Nico Schick
Publisher : Cuvillier Verlag
ISBN 13 : 3736962460
Total Pages : 20 pages
Book Rating : 4.7/5 (369 download)

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Book Synopsis Modeling of specific safety-critical driving scenarios for data synthesis in the context of autonomous driving software by : Nico Schick

Download or read book Modeling of specific safety-critical driving scenarios for data synthesis in the context of autonomous driving software written by Nico Schick and published by Cuvillier Verlag. This book was released on 2020-08-06 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous driving is one of the key disciplines in the automotive field and currently under intensive development, especially with the objective of saving more people’s lives on the roads due to significant reductions in the number of traffic accidents. Therefore, the software components within autonomous cars must be tested efficient and precisely. One of the most challenging aspects of autonomous cars are the safety-critical driving scenarios. Their criticality has seldom been measured in terms of further forensic analysis or software solutions in the field of artificial intelligence. Therefore, data related to safety-critical driving scenarios must be obtained another way. In this context, kinematic models can be used to represent these scenes by describing the vehicle’s movements based on defined boundary constraints as well as providing synthesized data through the simulation of a model for the training and validation of the underlying machine learning algorithms, such as neural networks or generative algorithms. In this paper, three of the most significant safety-critical driving scenarios, namely emergency braking, turning, and overtaking, are modeled accordingly.