Found a total of 5226 related content
Let's talk about low-speed autonomous driving and high-speed autonomous driving in one article
Article Introduction:In a previously shared article: How to Make Self-Driving Cars "Recognize the Road", I mainly talked about the importance of high-precision maps in self-driving cars. A friend left a message, "If the author knew about the automatic mobile cars sorted by STO Express In a work scenario, I’m afraid you won’t have the views and opinions of this article?” In this dialogue, the related concepts of low-speed autonomous driving and high-speed autonomous driving were involved. Autonomous vehicles, also known as driverless vehicles, are an automated vehicle and a vehicle that requires driver assistance or does not require control at all. As an automated vehicle, a self-driving vehicle does not require human operation. Perceive the surrounding environment and complete navigation and travel tasks. The ultimate goal of autonomous driving development is that it can be accomplished by autonomous vehicles
2023-04-08
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A grand view of autonomous driving simulation! Let's talk about the industry of autonomous driving simulation!
Article Introduction:Hello, fellow listeners! It’s time for the Simulation Grand View Garden program again! Today I will give you a brief introduction to the autonomous driving simulation industry. First, let’s talk about why autonomous driving requires simulation. A few years ago, when watching If You Are the One, guest Huang Lan said that she would only accept autonomous driving if 2/3 of the people accepted it, which reflected the general public's concern for the safety of autonomous driving. In order to ensure safety, autonomous driving algorithms need to undergo a large number of road tests before they can be truly applied on a large scale. However, the testing of autonomous driving systems is very "expensive": the time and capital costs are huge, so people hope to move as many tests as possible to computer systems, use simulation to expose most of the problems in the autonomous driving system, and reduce on-site road testing needs and therefore our jobs
2023-10-17
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How to do self-driving and full automation in PHP?
Article Introduction:With the rapid development of machine learning and artificial intelligence, autonomous driving and complete automation have become a trend. Today, PHP is a very popular server scripting language that can also be used to develop self-driving and fully automated applications. This article will introduce how to achieve self-driving and complete automation in PHP, including the following aspects: Understand the concepts of self-driving and complete automation How PHP supports self-driving and complete automation How to use PHP to achieve self-driving and complete automation Some practical application cases 1 , Understand autonomous driving
2023-05-25
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How to make self-driving cars 'know the road'
Article Introduction:Just like human walking, self-driving cars also need to have the ability to think independently and make judgments and decisions about the traffic environment in order to complete the travel process. With the improvement of advanced assisted driving system technology, the safety of drivers driving cars continues to improve, and the degree of driver participation in driving decision-making is gradually reduced. Autonomous driving is getting closer and closer to us. Self-driving cars, also known as driverless cars, are essentially highly intelligent robots that can complete travel behaviors with only driver assistance or without driver operation at all. Autonomous driving is mainly realized through the perception layer, decision-making layer and execution layer. As an automated vehicle, autonomous vehicles can use additional radar (millimetre-wave radar, lidar), vehicle cameras, and global navigation satellite systems (G
2023-04-09
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Self-driving company Cruise: Self-driving taxis require human assistance every 4 to 5 miles traveled
Article Introduction:According to news on November 7, Cruise, a self-driving company owned by General Motors, recently confirmed that self-driving taxis require manual assistance every 4 to 5 miles. On Sunday, Cruise CEO and founder Kyle Vogt responded to claims that the company's self-driving taxis are not fully autonomous and require frequent assistance from staff at remote operations centers. There are reports that General Motors' Cruise relies on humans to achieve "autonomous" driving, and Vogt admitted that Cruise does have a remote assistance team. He said, "In complex urban environments, Cruise autonomous vehicles receive remote assistance (RA) an average of 2% to 4% of the time. This is low enough, and further optimization will not bring huge benefits.
2023-11-07
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Research on key technical difficulties of autonomous driving
Article Introduction:The Society of Automotive Engineers divides autonomous driving into six levels, L0-L5, based on the degree of vehicle intelligence: L0 is No Automation (NA), which is a traditional car where the driver performs all operating tasks, such as steering and braking. , acceleration, deceleration or parking, etc.; L1 is Driving Assistant (DA), which can provide the driver with driving warning or assistance, such as providing support for one operation of the steering wheel or acceleration and deceleration, and the rest is left to the driver. Operation; L2 is Partial Automation (PA), the vehicle provides driving for multiple operations in steering wheel and acceleration and deceleration, and the driver is responsible for other driving operations; L3 is conditional automation
2023-04-08
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Giving up autonomous driving is also a kind of reconciliation
Article Introduction:1 From glory to bottom, where will autonomous driving go? The autonomous driving industry has entered a stage of rapid development since 2013. In 2016, the autonomous driving industry ushered in a stage of rapid development. Investment and financing events from related companies have gradually increased, and autonomous driving companies have begun to bloom everywhere. Reaching its peak in 2018, there were as many as 472 newly registered companies, 78 comprehensive investment and financing incidents, and a disclosed investment and financing amount of up to 81.1 billion yuan. Beginning in 2019, the autonomous driving industry began to enter a stage of steady development. In 2020, due to uncontrollable factors, the pace of development of the autonomous driving industry began to slow down. However, the amount of investment and financing in the autonomous driving industry is still as high as 43.63 billion yuan, a year-on-year increase of 136.9%. The autonomous driving track is still hot in 2021, only the first 3 seasons
2023-06-15
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Autonomous driving is difficult to attack by dimensionality reduction
Article Introduction:Since 2021, some L4 autonomous driving companies targeting Robotaxi have begun to differentiate into new businesses, trying to make breakthroughs in commercial revenue through technology. The phenomenon of autonomous driving companies developing L2-level assisted driving functions is called a "dimensionality reduction attack" by some people. In their view, L4 autonomous driving companies can rely on the advantages of software algorithms to provide smart cars with richer functions and driving experiences, just as high-dimensional creatures in "The Three-Body Problem" can easily wipe out low-dimensional creatures and civilizations. However, some people are dismissive of this. They believe that it may not be a smooth process for autonomous driving companies that are good at software algorithms to enter the research and development field of automotive functions that emphasize the combination of software and hardware. Both sides hold different opinions and it is difficult to distinguish. But what is certain is that since
2023-04-12
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An article explaining the key technical difficulties of autonomous driving
Article Introduction:The Society of Automotive Engineers divides autonomous driving into six levels, L0-L5, based on the degree of vehicle intelligence: L0 is NoAutomation (NA), which is a traditional car where the driver performs all operating tasks, such as steering, braking, Acceleration, deceleration or parking, etc.; L1 is Driving Assistance (DA), which can provide the driver with driving warning or assistance, such as providing support for one operation of the steering wheel or acceleration and deceleration, and the rest is operated by the driver; L2 is Partial Automation (PA). The vehicle provides driving for multiple operations in steering wheel and acceleration and deceleration, and the driver is responsible for other driving operations; L3 is Conditional Automation (Co
2023-05-15
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Comprehensive analysis of four major autonomous driving strategies
Article Introduction:Introduction Current autonomous driving strategy research still focuses on implementing specific strategies in specific scenarios. Researchers from Tsinghua University published a comprehensive review at a top conference in the transportation field, analyzing autonomous driving strategies from a more advanced perspective. When an autonomous driving encounters an oncoming vehicle, should it pass first or wait to give way? The strategy of autonomous driving has always been a core issue in this field, that is, how autonomous vehicles should interact reasonably and efficiently with other traffic participants in traffic conflict areas. Strategies that are too radical or too conservative will have an impact on traffic efficiency and even threaten the lives of passengers. Previous research on autonomous driving strategies mainly focused on low-level detailed driving behaviors or specific traffic situations, that is, "concrete analysis of specific problems", resulting in engineering generation.
2023-04-16
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萝卜打车自动驾驶
Article Introduction:萝卜打车自动驾驶领跑行业,其优势和特色包括:技术优势:依靠百度强大AI能力和算法,实现360度无死角感知。安全保障:多重冗余系统、安全监视员监控、远程接管机制,确保车辆安全运行。便捷出行:一键呼叫即可体验自动驾驶,免除手动驾驶负担。智能化体验:车载娱乐系统、语音交互等功能,提供丰富娱乐和便利体验。展望未来:推动行业变革,提供经济、环保、便捷的出行选择,并探索物流、公共交通等领域的应用。
2024-07-13
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HaoMo Zhixing & Tsinghua AIR self-driving open class Dr. Pan Xing revealed HaoMo's self-driving AI practice on the spot
Article Introduction:As AI large models emerge from deep learning algorithms, they are becoming the hottest new technology paradigm in the current AI field. Autonomous driving technology also has the possibility to evolve from the modular stage to end-to-end autonomous driving due to the introduction of large model technology. AI large models are reshaping the technical route of autonomous driving. On September 27, the high-quality public course on autonomous driving jointly organized by HaoMo Zhixing and Tsinghua University Intelligent Industry Research Institute (AIR) concluded successfully. This open class focuses on the current leading AI algorithms for autonomous driving, combined with Haomo’s specific practices, bringing an end-to-end autonomous driving technology feast to autonomous driving practitioners, industry partners and media friends. This course is the third in a series of public courses on autonomous driving, following the first and second courses.
2023-10-20
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How to develop autonomous driving and Internet of Vehicles in PHP?
Article Introduction:As a popular web development language, PHP can help us build efficient and scalable autonomous driving and Internet of Vehicles applications. Autonomous driving technology is becoming more and more widely used, and the Internet of Vehicles has become a new trend in the automotive industry. Therefore, it is very important to understand how to use PHP for autonomous driving and Internet of Vehicles development. Autonomous driving technology Autonomous driving technology means that the car can drive autonomously without the driver's intervention. In autonomous driving technology, vehicles use a variety of sensors (such as radar, cameras, lidar, etc.)
2023-05-20
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How machine learning can power self-driving cars
Article Introduction:Self-driving cars equipped with machine learning algorithms can make better decisions, recognize and classify objects, and interpret situations. Humanity has come a long way in the day-to-day functioning of the world, and the integration of technology is only getting closer. Artificial intelligence and its subcategory, machine learning, have caused such huge ripples throughout this era of innovation that even self-driving cars are the future. Some multinational companies, such as Tesla and Google, have launched self-driving projects such as Waymo One to promote self-driving taxi services made possible by machine learning. Its role in this innovation is expanded below. How Machine Learning Is Changing the Game for Self-Driving Cars Self-driving cars, also known as self-driving cars or robot cars, are a
2023-04-12
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Traffic rule recognition problems in autonomous driving
Article Introduction:Traffic rule recognition problems in autonomous driving require specific code examples Abstract: Autonomous driving technology is developing rapidly and is expected to be commercialized in the future. However, at the same time, autonomous vehicles face an important challenge, namely the identification and compliance of traffic rules. This article will focus on the problem of traffic rule recognition in autonomous driving and give some specific code examples. Research Background Self-driving vehicles need to abide by traffic rules while driving to ensure traffic safety and smoothness. However, the recognition of traffic rules is difficult for computers to
2023-10-08
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萝卜快跑自动驾驶事故
Article Introduction:萝卜快跑自动驾驶事故的原因可能包括:传感器故障、软件缺陷、驾驶员干预、道路状况和天气因素。针对此类事故,应对措施包括:加强传感器可靠性、优化软件安全、规范驾驶员干预、完善道路基础设施、加强监管和认证。
2024-07-13
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Detailed explanation of autonomous driving decision planning technology
Article Introduction:With the rapid development of deep reinforcement learning technology, more and more research teams have begun to apply it to autonomous driving decision planning, integrating behavioral decision-making and motion planning modules to directly learn driving trajectories. The decision-making planning module in autonomous driving is one of the core indicators for measuring and evaluating autonomous driving capabilities. Its main task is to analyze the current environment after receiving various sensory information from sensors, and then issue instructions to the underlying control module. . A typical decision planning module can be divided into three levels: global path planning, behavioral decision-making, and motion planning. 01 Introduction In a complete autonomous driving system, if the perception module is compared to human eyes and ears, then the decision-making planning is the brain of autonomous driving. The brain receives various signals from sensors
2023-04-04
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Entering the field of self-driving trucks: Li Auto plans to be the VP or leader of intelligent driving business
Article Introduction:According to sources, Chinese electric car maker Li Auto plans to enter the field of self-driving trucks. This important move is expected to be led by Lang Xianpeng, vice president of intelligent driving business. According to people familiar with the matter, Li Auto has begun looking for self-driving trucks through multiple headhunting companies. Relevant talents, and some professionals in the autonomous driving industry have come to Li Auto for interviews. This key position is named "Truck Autonomous Driving Technical Director" and its main responsibilities include overall responsibility for the design, development, testing and experimental verification of the factory logistics truck autonomous driving system to deliver safe and efficient autonomous driving products. According to our understanding, the requirements for this position are very strict, including more than 10 years of work experience and more than 6 years of relevant R&D management and technical skills.
2023-09-08
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ChatGPT Java: How to implement autonomous driving and traffic planning
Article Introduction:ChatGPTJava: How to implement autonomous driving and traffic planning, specific code examples are needed. Autonomous driving technology is a hot topic in today's technology field. With the development of artificial intelligence and machine learning, developers can use the Java programming language to implement autonomous driving functions as well as traffic planning. This article will introduce how to use Java to implement autonomous driving and traffic planning by providing specific code examples. First, we need to understand several basic concepts and techniques. Sensor technology: Self-driving cars require a variety of sensors
2023-10-27
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How to use Go language for autonomous driving development?
Article Introduction:Autonomous driving technology is becoming one of the hottest research directions in the automotive industry. At the same time, more and more programming languages are beginning to be used in the development of autonomous driving systems. Among them, the Go language has become one of the preferred languages for autonomous driving development due to its excellent performance and ease of use. This article will introduce the basic steps and implementation methods of developing autonomous driving using Go language. 1. Choose a suitable Go editor. To start using Go language for autonomous driving development, the first step is to choose a suitable Go editor. Instead of
2023-06-11
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