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--- en:av:autonomy_and_autonomous_systems:overview:autonomous_cars [2021/06/11 09:56] – agrisnik
+++ en:av:autonomy_and_autonomous_systems:overview:autonomous_cars [Unknown date] (current) – external edit (Unknown date) 127.0.0.1
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 Summarizing most of the available definition we will use the following (provided by SDC_Explained_2017)((https://www.ucsusa.org/resources/self-driving-cars-101)):
-//Self-driving cars are cars or trucks in which human drivers are never required to take control to safely operate the vehicle. They combine sensors and software to control, navigate and drive vehicles//
+//Self-driving cars are cars or trucks in which human drivers are never required to take control to safely operate the vehicle. They combine sensors and software to control, navigate and drive vehicles.//
 Unfortunately, currently, there are no legally operating, fully autonomous vehicles in the United States or other parts of the world. There are, however, partially autonomous vehicles—cars and trucks with varying amounts of self-automation, from conventional cars with brake and lane assistance to highly-independent, self-driving prototypes((https://www.ucsusa.org/resources/self-driving-cars-101)).
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 The technology behind includes the following main data processing steps:
-  * Mapping – the preprocessed map is required to build internal data structures and representation of the road infrastructure including traffic lights, sideroads and other important objects. The map is built by the company staff in 3D
+  * Mapping – the preprocessed map is required to build internal data structures and representation of the road infrastructure including traffic lights, sideroads, and other important objects. The map is built by the company staff in 3D;
-  * Real-time sensor data processing, which enables to recognize and map surrounding objects like pedestrians, other vehicles, traffic light status, and others
+  * Real-time sensor data processing, which enables to recognize and map surrounding objects like pedestrians, other vehicles, traffic light status, and others;
-  * Modelling – this step enables to forecast object motion patterns, which is of very high importance for safe driving
+  * Modelling – this step enables to forecast object motion patterns, which is of very high importance for safe driving;
-  * Decision making – taking into consideration of the mentioned aspects the control software determines the exact way of actions
+  * Decision making – taking into consideration of the mentioned aspects the control software determines the exact way of actions;
-  * Execution – the made decision is being executed on the road
+  * Execution – the made decision is being executed on the road.
 The second-largest autonomous vehicles fleet consisting of more than 180 vehicles is deployed by General Motors’ Cruise division (https://www.getcruise.com/). The developing team puts a great emphasis on achievements in AI and robotics. However, a major part of the onboard hardware is made by the Cruise team as well.
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 <figure>
 {{ :en:av:autonomy_and_autonomous_systems:overview:getcruise.png?400 |}}
 <caption>Cruise system</caption>
 </figure>
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 <figure>
 {{ :en:av:autonomy_and_autonomous_systems:overview:waymo_minivan_1.jpg?400 |}}
 <caption>Waymo system</caption>
 </figure>
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 Besides the mentioned companies there are many more at different stages of development. However, the fundamental building blocks are the same:
-  * Self-awareness sensor systems like Lidars, cameras, and others, which provide data for decision-making in real-time under highly changing environmental conditions.
+  * Self-awareness sensor systems like Lidars, cameras, and others, which provide data for decision-making in real-time under highly changing environmental conditions;
   * High performance computing unit with redundancy and cross-check capabilities (not all of the developer ensures these capabilities yet);
   * Simulation-based training before field tests, which reduces development time and increases safety;
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 The main potential impacts of technology in the future is anticipated through the following main benefits ((https://www.ucsusa.org/resources/self-driving-cars-101)):
-  * Safety is the most anticipated with the potential to reduce the huge number of car crashes on a global scale. However, the main concerns are related to software security issues
+  * Safety is the most anticipated with the potential to reduce the huge number of car crashes on a global scale. However, the main concerns are related to software security issues;
-  * Equity through enabling to mobilize people who currently because of different reasons cannot participate in mobile adventures. For instance, elderly people. However, this might have some negative aspects as well for instance, significantly increased traffic intensity, displaced employment structure and others.
+  * Equity through enabling to mobilize people who currently because of different reasons cannot participate in mobile adventures. For instance, elderly people. However, this might have some negative aspects as well for instance, significantly increased traffic intensity, displaced employment structure and others;
   * Environmental footprint which might shift to both – increased or decreased because of significant growth of total miles driven. On one case due to emissions, in the other due to the use of clean energy grids (for powering electric vehicles).

en/av/autonomy_and_autonomous_systems/overview/autonomous_cars.1623405391.txt.gz · Last modified: 2021/06/11 09:00 (external edit)