A high-definition map (HD map) is a highly accurate map used primarily in the field of autonomous driving, [1] [2] containing details not normally present on traditional maps. [3] [4] HD maps are often captured using an array of sensors, such as LiDARs, radars, digital cameras, and GPS, [3] [5] [6] and they can also be constructed using aerial imagery. [7] [8] Such maps can be precise at a centimetre level. [3] [9]
High-definition maps for self-driving cars usually include map elements such as road shape, road marking, traffic signs, and barriers. [4] [10] Maintaining high accuracy is one of the biggest challenges in building HD maps of real-world roads. With regard to accuracy, there are two main focus points that determine the quality of an HD map:
In areas with good GPS reception it is possible to achieve a global accuracy of less than 3 cm (1.2 in) deviation using satellite signals and correction data from base stations.
In GPS-denied areas, however, inaccuracy rises with distance traveled through the area, being largest in its middle. This means that the maximum GPS error can be expressed as a percentage of the distance traveled through a GPS-denied area: this value is less than 0.5%. [11]
A self-driving car, also known as a autonomous car (AC), driverless car, robotaxi, robotic car or robo-car, is a car that is capable of operating with reduced or no human input. Self-driving cars are responsible for all driving activities, such as perceiving the environment, monitoring important systems, and controlling the vehicle, which includes navigating from origin to destination.
An autonomous agent is an artificial intelligence (AI) system that can perform complex tasks independently.
Edge computing is a distributed computing model that brings computation and data storage closer to the sources of data. More broadly, it refers to any design that pushes computation physically closer to a user, so as to reduce the latency compared to when an application runs on a centralized data centre.
Patrick M. Hanrahan is an American computer graphics researcher, the Canon USA Professor of Computer Science and Electrical Engineering in the Computer Graphics Laboratory at Stanford University. His research focuses on rendering algorithms, graphics processing units, as well as scientific illustration and visualization. He has received numerous awards, including the 2019 Turing Award.
Özalp Babaoğlu, is a Turkish computer scientist. He is currently professor of computer science at the University of Bologna, Italy. He received a Ph.D. in 1981 from the University of California at Berkeley. He is the recipient of 1982 Sakrison Memorial Award, 1989 UNIX InternationalRecognition Award and 1993 USENIX AssociationLifetime Achievement Award for his contributions to the UNIX system community and to Open Industry Standards. Before moving to Bologna in 1988, Babaoğlu was an associate professor in the Department of Computer Science at Cornell University. He has participated in several European research projects in distributed computing and complex systems. Babaoğlu is an ACM Fellow and has served as a resident fellow of the Institute of Advanced Studies at the University of Bologna and on the editorial boards for ACM Transactions on Computer Systems, ACM Transactions on Autonomous and Adaptive Systems and Springer-Verlag Distributed Computing.
Global Navigation Satellite System (GNSS) receivers, using the GPS, GLONASS, Galileo or BeiDou system, are used in many applications. The first systems were developed in the 20th century, mainly to help military personnel find their way, but location awareness soon found many civilian applications.
Urban computing is an interdisciplinary field which pertains to the study and application of computing technology in urban areas. This involves the application of wireless networks, sensors, computational power, and data to improve the quality of densely populated areas. Urban computing is the technological framework for smart cities.
Margaret Martonosi is an American computer scientist who is currently the Hugh Trumbull Adams '35 Professor of Computer Science at Princeton University. Martonosi is noted for her research in computer architecture and mobile computing with a particular focus on power-efficiency.
Map matching is the problem of how to match recorded geographic coordinates to a logical model of the real world, typically using some form of Geographic Information System. The most common approach is to take recorded, serial location points and relate them to edges in an existing street graph (network), usually in a sorted list representing the travel of a user or vehicle. Matching observations to a logical model in this way has applications in satellites navigation, GPS tracking of freight, and transportation engineering.
Fog computing or fog networking, also known as fogging, is an architecture that uses edge devices to carry out a substantial amount of computation, storage, and communication locally and routed over the Internet backbone.
Holly Rushmeier is an American computer scientist and is the John C. Malone Professor of Computer Science at Yale University. She is known for her contributions to the field of computer graphics.
RIPE Atlas is a global, open, distributed Internet measurement platform, consisting of thousands of measurement devices that measure Internet connectivity in real time.
Implicit authentication (IA) is a technique that allows the smart device to recognize its owner by being acquainted with his/her behaviors. It is a technique that uses machine learning algorithms to learn user behavior through various sensors on the smart devices and achieve user identification. Most of the current authentication techniques, e.g., password, pattern lock, finger print and iris recognition, are explicit authentication which require user input. Comparing with explicit authentication, IA is transparent to users during the usage, and it significantly increases the usability by reducing time users spending on login, in which users find it more annoying than lack of cellular coverage.
An AI accelerator, deep learning processor or neural processing unit (NPU) is a class of specialized hardware accelerator or computer system designed to accelerate artificial intelligence and machine learning applications, including artificial neural networks and computer vision. Typical applications include algorithms for robotics, Internet of Things, and other data-intensive or sensor-driven tasks. They are often manycore designs and generally focus on low-precision arithmetic, novel dataflow architectures or in-memory computing capability. As of 2024, a typical AI integrated circuit chip contains tens of billions of MOSFETs.
Cache prefetching is a technique used by computer processors to boost execution performance by fetching instructions or data from their original storage in slower memory to a faster local memory before it is actually needed. Most modern computer processors have fast and local cache memory in which prefetched data is held until it is required. The source for the prefetch operation is usually main memory. Because of their design, accessing cache memories is typically much faster than accessing main memory, so prefetching data and then accessing it from caches is usually many orders of magnitude faster than accessing it directly from main memory. Prefetching can be done with non-blocking cache control instructions.
Transition refers to a computer science paradigm in the context of communication systems which describes the change of communication mechanisms, i.e., functions of a communication system, in particular, service and protocol components. In a transition, communication mechanisms within a system are replaced by functionally comparable mechanisms with the aim to ensure the highest possible quality, e.g., as captured by the quality of service.
Moustafa Youssef is an Egyptian computer scientist who was named Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2019 for contributions to wireless location tracking technologies and a Fellow of the Association for Computing Machinery (ACM) in 2019 for contributions to location tracking algorithms. He is the first and only ACM Fellow in the Middle East and Africa.
Static application security testing (SAST) is used to secure software by reviewing the source code of the software to identify sources of vulnerabilities. Although the process of statically analyzing the source code has existed as long as computers have existed, the technique spread to security in the late 90s and the first public discussion of SQL injection in 1998 when Web applications integrated new technologies like JavaScript and Flash.
Spatial embedding is one of feature learning techniques used in spatial analysis where points, lines, polygons or other spatial data types. representing geographic locations are mapped to vectors of real numbers. Conceptually it involves a mathematical embedding from a space with many dimensions per geographic object to a continuous vector space with a much lower dimension.
Xing Xie is a partner research manager at Microsoft Research Asia. As a computer scientist, his research has focused on data mining, social computing, and responsible AI. He has published more than 400 papers which have been cited more than 60,000 times. He has been on organizing committees or helped with the programs of over 70 conferences and workshops.