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Languages : en
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Abstract : This dissertation proposes a data-driven optimization-based framework to model traffic dynamics under uncertainty including travel demand, transportation network (i.e. route choice), and connected and automated driving dynamics (on freeways and arterials) using connected vehicle data though Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehicle-to-Network (V2N) communications. To model travel demand dynamics, this dissertation proposes Distributionally Robust Stochastic Optimization (DRSO) using V2N data. A challenge of modeling travel demand dynamics directly using the real-world V2N data is the incomplete and inaccurate trajectory records from the raw data due to technical and privacy issues. Through the proposed DRSO models, this dissertation offline reconstructs the missing choices of activity locations, durations, and paths using the partially observed trajectories from a real-world connected vehicle dataset. This dataset contains around 2,800 connected vehicles over two separate months in Southeast Michigan from the Safety Pilot Model Deployment (SPMD) project. For modeling route choice dynamics, this dissertation develops a Conditional Value-at-Risk (CVaR) based DRSO model for the route choice problem under the impacts of travel time uncertainties and travelers' risk attitudes using vehicle trajectory data from the SPMD dataset. The proposed CVaR-DRSO model offline estimates route choices under uncertainties by using a data-driven uncertainty set. For modeling connected and automated driving, this dissertation develops DRSO-based Model Predictive Control (MPC) models with Distributionally Robust Chance Constraints (DRCC). For the connected and automated driving on freeways (i.e. uninterrupted flow facilities), a DRSO-DRCC based MPC model is proposed to improve the stability, robustness, and safety for the online longitudinal cooperative automated driving of a platoon of Connected and Automated Vehicles (CAVs) under uncertain traffic conditions by using real-time V2V data. For the energy efficient connected and automated driving on arterials (i.e. interrupted flow facilities), a DRSO-DRCC based MPC model is developed to improve the safety, energy, efficiency, driving comfort, and robustness of the automated driving on signalized arterials under traffic uncertainties by using real-time V2I and V2V data. This dissertation provides a comprehensive data-driven optimization-based framework to model the traffic dynamics using the connected vehicle data and improve the connected and automated driving control under uncertainty based on CAV technologies.
Author: Erik Jakobsson
Publisher: Linköping University Electronic Press
ISBN: 9179299725
Category :
Languages : en
Pages : 22
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Book Description
Situation awareness is a crucial capability of any autonomous system, including mining vehicles such as drill rigs and mine trucks. Typically situation awareness is interpreted as the capability of an autonomous system to interpret its surroundings and the intentions of other agents. The internal system awareness however, is often not receiving the same focus, even though the success of any given mission is completely dependent of the condition of the agents themselves. The internal system awareness in the form of vehicle health is the focus of this thesis. As the mining industry becomes increasingly automated, and vehicles become increasingly advanced, the need for condition monitoring and prognostics will continue to rise. This thesis explores data-driven methods that estimate the health of mining vehicles to accommodate those needs. We do so by utilizing available sensor signals, common on a large amount of mining vehicles, to make assessments of the current vehicle condition and tasks. The mining industry is characterized by small series of highly specialized vehicles, which affects the possibility to use more traditional prognostic solutions. The resulting health information can be used both to aid in tasks such as maintenance planning, but also as an important input to decision making for the planning system, i.e. how to run the vehicle for minimum wear and damage, while maintaining other mission objectives. The contributions include: a) A method to use operational data to estimate damage on the frame of a mine truck. This is done using system identification to find a model describing stresses in the structure with input from other sensors such as accelerometers, load sensors and pressure sensors. The estimated stress time signal is in turn used to calculate accumulated damage, and is shown to reveal interesting conclusions on driver behavior. b) A method to characterize the different driving tasks by using an accelerometer and a convolutional neural network. We show that the model is capable of classifying the vehicle task correctly in 96 % of the cases. And finally c), a system for underground road monitoring, where a quarter car model and a Kalman filter are used to generate an estimate of the road profile, while positioning the vehicle using inertial measurements and access point signal strength.
Author: Yinhai Wang
Publisher: Elsevier
ISBN: 0128170271
Category : Transportation
Languages : en
Pages : 302
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Book Description
Data-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data analysis, and machine learning. The book examines the state-of-the-art in data-enabled methodologies, technologies and applications in transportation. Readers will learn how to solve problems relating to energy efficiency under connected vehicle environments, urban travel behavior, trajectory data-based travel pattern identification, public transportation analysis, traffic signal control efficiency, optimizing traffic networks network, and much more. - Synthesizes the newest developments in data-driven transportation science - Includes case studies and examples in each chapter that illustrate the application of methodologies and technologies employed - Useful for both theoretical and technically-oriented researchers
Author: Tech Whiz
Publisher: Independently Published
ISBN:
Category : Law
Languages : en
Pages : 0
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Book Description
In the age of digital revolution, navigating the vast expanse of the internet can feel like embarking on an epic journey without a map. But fear not, for within the pages of "Data-Driven Vehicles," readers will discover the keys to mastering the art of digital navigation with confidence and competence. At the core of this enlightening guide lies a simple yet profound analogy: gadgets are the vehicles that propel us forward, and the internet serves as the expansive highway of our digital landscape. With this analogy as our compass, we embark on a transformative journey through the intricacies of online exploration. From understanding the fundamental role of data as the fuel that powers our digital vehicles to unraveling the complexities of online platforms as meeting points, marketplaces, and destinations, "Data-Driven Vehicles" equips readers with the essential tools and insights needed to navigate the digital realm with ease. Throughout the book, readers will delve into the nuances of digital navigation, exploring key concepts such as the multifaceted nature of online platforms, the importance of digital literacy and safety, and the evolving trends shaping the future of data-driven exploration and engagement. With clarity and precision, the author elucidates the intricacies of our digital landscape, offering practical tips, strategies, and real-world examples to empower readers in their online endeavors. Whether browsing social media, conducting research, or shopping online, readers will learn how to optimize their digital experiences for maximum efficiency and productivity. Moreover, "Data-Driven Vehicles" goes beyond mere instruction, delving into the deeper implications of our digital interactions. From the ethical considerations of data usage to the impact of emerging technologies on our online experiences, readers are encouraged to engage critically with the digital world and make informed decisions that align with their values and priorities. But perhaps the most compelling aspect of "Data-Driven Vehicles" lies in its unwavering commitment to empowerment. By demystifying the complexities of digital navigation and providing readers with the knowledge and tools they need to navigate the digital landscape with confidence, this book serves as a beacon of guidance in an increasingly interconnected world. In essence, "Data-Driven Vehicles" is more than just a book -- it is a roadmap to success in the digital age. Whether you're a seasoned navigator or a novice explorer, this indispensable guide will empower you to chart your course with purpose and clarity, ensuring that every journey through the digital landscape is a fulfilling and enriching experience.
Author: James Wen
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Every computing system has two, and only two attributes: Data Value and Data timing, which represent fully the system functionalities from the system external behavior point of view.The data driven system engineering is the approach to develop the system by focusing on the two attributes mentioned above, in which, the data values are derived by the system operation concept design, and the data timing is derived by the system latency design. Based on which, this book provides a full range of system and software engineering development activities: Requirement Elicitation Requirement Engineering System and Software Architecture Design System Operation Concept Design System and Software Structure Design Electronic Architect Design Functionality Allocation Failure Mode and Effect Analysis (FMEA) Safety Cybersecurity System and software Verification System and Software Integration and Verification System and Software Black Box VerificationEach of which has its own clearly defined scope and approach, which is different from the conventional development, in some cases even different from some ISO standards, for example: about the safety development in this book, the safety requirements for every part in a vehicle are cascaded from the vehicle safety requirements, which is different from the Concept Phase in the Part 3 of ISO 26262; about the error prevention in this book, there are only two types of errors to be detected in a computing system: Data Value error and Data Timing error.
Author: C Mike Lewis
Publisher: Independently Published
ISBN:
Category : Computers
Languages : en
Pages : 0
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Book Description
Unlock the Future of Automotive Sales with Big Data In a rapidly evolving industry, the power of big data is transforming how car dealerships operate, compete, and thrive. "The Power of Big Data in the Automotive Industry" offers an in-depth exploration of the ways big data is revolutionizing the automotive sector, providing dealerships with the tools and insights needed to stay ahead in a competitive market. Inside This Book: Introduction to Big Data: Understand the fundamentals of big data and its unique characteristics-Volume, Velocity, And Variety-and why it matters in today's car dealership landscape. Leveraging Customer Data: Discover how to collect, organize, and analyze customer data to unveil critical insights into demographics, preferences, and buying behaviors, driving personalized marketing strategies. Optimizing Inventory Management: Learn how to use big data to forecast demand accurately, manage inventory efficiently, and streamline the procurement and distribution process to meet customer needs. Enhancing the Sales Process: Explore data-driven techniques to personalize the sales experience, optimize the sales funnel, and implement effective sales tactics using cutting-edge AI and machine learning tools. Improving Customer Retention and Loyalty: Uncover strategies to enhance customer retention through targeted efforts, customer lifetime value analysis, and exceptional post-sale experiences. Predictive Analytics for Future Sales: Apply predictive analytics to anticipate customer needs, identify emerging market trends, and prepare for the future of car sales, including the impact of autonomous vehicles. Building a Data-Driven Culture: Learn how to foster a data-centric mindset within your organization, overcome resistance to change, and develop the skills and infrastructure necessary for data-driven decision-making. IoT integration Real-World Case Studies: Gain insights from detailed case studies of dealerships that have successfully harnessed big data, showcasing best practices and lessons from industry leaders. A Vision for the Future: The transformative potential of big data and encouraging continuous learning and adaptation to stay at the forefront of the automotive industry. Whether you are a dealership owner, manager, or industry professional, this book provides a comprehensive guide to leveraging big data for strategic advantage, driving growth, and delivering exceptional customer experiences. Embrace the power of big data and unlock new opportunities in the ever-evolving automotive market.
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309392527
Category : Transportation
Languages : en
Pages : 273
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Book Description
There are approximately 4,000 fatalities in crashes involving trucks and buses in the United States each year. Though estimates are wide-ranging, possibly 10 to 20 percent of these crashes might have involved fatigued drivers. The stresses associated with their particular jobs (irregular schedules, etc.) and the lifestyle that many truck and bus drivers lead, puts them at substantial risk for insufficient sleep and for developing short- and long-term health problems. Commercial Motor Vehicle Driver Fatigue, Long-Term Health and Highway Safety assesses the state of knowledge about the relationship of such factors as hours of driving, hours on duty, and periods of rest to the fatigue experienced by truck and bus drivers while driving and the implications for the safe operation of their vehicles. This report evaluates the relationship of these factors to drivers' health over the longer term, and identifies improvements in data and research methods that can lead to better understanding in both areas.
Author: Scheubner, Stefan
Publisher: KIT Scientific Publishing
ISBN: 3731511665
Category : Technology & Engineering
Languages : en
Pages : 190
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Book Description
This work aims at improving the energy consumption forecast of electric vehicles by enhancing the prediction with a notion of uncertainty. The algorithm itself learns from driver and traffic data in a training set to generate accurate, driver-individual energy consumption forecasts.
Author: Teodora Touzharova
Publisher:
ISBN:
Category :
Languages : en
Pages : 176
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Book Description
Author: Karen Levy
Publisher: Princeton University Press
ISBN: 0691259127
Category : Business & Economics
Languages : en
Pages : 240
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Book Description
A behind-the-scenes look at how digital surveillance is affecting the trucking way of life Long-haul truckers are the backbone of the American economy, transporting goods under grueling conditions and immense economic pressure. Truckers have long valued the day-to-day independence of their work, sharing a strong occupational identity rooted in a tradition of autonomy. Yet these workers increasingly find themselves under many watchful eyes. Data Driven examines how digital surveillance is upending life and work on the open road, and raises crucial questions about the role of data collection in broader systems of social control. Karen Levy takes readers inside a world few ever see, painting a bracing portrait of one of the last great American frontiers. Federal regulations now require truckers to buy and install digital monitors that capture data about their locations and behaviors. Intended to address the pervasive problem of trucker fatigue by regulating the number of hours driven each day, these devices support additional surveillance by trucking firms and other companies. Traveling from industry trade shows to law offices and truck-stop bars, Levy reveals how these invasive technologies are reconfiguring industry relationships and providing new tools for managerial and legal control—and how truckers are challenging and resisting them. Data Driven contributes to an emerging conversation about how technology affects our work, institutions, and personal lives, and helps to guide our thinking about how to protect public interests and safeguard human dignity in the digital age.
