… An autonomous car is a driverless vehicle for the purpose of navigating autonomously and
… the technological limitations and impacts of using autonomous cars, observing the feasibility, …

… mapping studies due to their simple structures and straightforward implementation. Vehicle
kinematics models that take into account steering and speed control inputs to predict vehicle …

… evaluate a GraphSLAM-based algorithm for mapping in the following complex field scenarios:
… , using an autonomous car. The map built by the system is used for localization and for …

… maps and rich maps data are so prized by autonomous vehicle developers, we concentrate
on one firm—Uber. Uber provides a good example here because its struggles over mapping …

… The aim of this study is to map out the research on AV for a better understanding of the trends,
patterns, and interconnections in studies along with identifying future research directions. …

… autonomous cars’ development and deployment on a large scale. We also highlight autonomous
car appli… and motion control in autonomous cars [26], long-term maps’ constructions for …

… map-based local route in urban areas, respectively. Since an autonomous car does not require
precise maps … the cost of creating and managing the precise map in that region. Since an …

… This study shows that SNA in a complex network setting will provide the … study examines
the SWOT analysis for self-driving technology and the factors that influence autonomous …

… viable for autonomous driving. Section IV will concern the techniques that tackle some of
the challenges of SLAM for autonomous cars, namely building and exploiting long-term maps. …

… In this paper, we present the results of a systematic mapping study in the context of autonomous
driving. The main contributions are: (i) introducing a comprehensive taxonomy for critical …