A Systematic Literature Review about the impact of Artificial Intelligence on Autonomous Vehicle Safety <s> C. Techniques used (RQ.3) and problems they seek to address (RQ.4) <s> The overall objective of the Strategic Computing (SC) Program of the Defense Advanced Research Projects Agency (DARPA) is to develop and demonstrate a new generation of machine intelligence technology which can form the basis for more capable military systems in the future and also maintain a position of world leadership for the US in computer technology. Begun in 1983, SC represents a focused research strategy for accelerating the evolution of new technology and its rapid prototyping in realistic military contexts. Among the very ambitious demonstration prototypes being developed within the SC Program are: 1) the Pilot's Associate which will aid the pilot in route planning, aerial target prioritization, evasion of missile threats, and aircraft emergency safety procedures during flight; 2) two battle management projects one for the for the Army, which is just getting started, called the AirLand Battle Management program (ALBM) which will use knowledge-based systems technology to assist in the generation and evaluation of tactical options and plans at the Corps level; 3) the other more established program for the Navy is the Fleet Command Center Battle Management Program (FCCBIVIP) at Pearl Harbor. The FCCBMP is employing knowledge-based systems and natural language technology in a evolutionary testbed situated in an operational command center to demonstrate and evaluate intelligent decision-aids which can assist in the evaluation of fleet readiness and explore alternatives during contingencies; and 4) the Autonomous Land Vehicle (ALV) which integrates in a major robotic testbed the technologies for dynamic image understanding, knowledge-based route planning with replanning during execution, hosted on new advanced parallel architectures. The goal of the Strategic Computing computer vision technology base (SCVision) is to develop generic technology that will enable the construction of complete, robust, high performance image understanding systems to support a wide range of DoD applications. Possible applications include autonomous vehicle navigation, photointerpretation, smart weapons, and robotic manipulation. This paper provides an overview of the technical and program management plans being used in evolving this critical national technology. <s> BIB001 </s> A Systematic Literature Review about the impact of Artificial Intelligence on Autonomous Vehicle Safety <s> C. Techniques used (RQ.3) and problems they seek to address (RQ.4) <s> A review of prior, relevant literature is an essential feature of any academic project. An effective review creates a firm foundation for advancing knowledge. It facilitates theory development, closes areas where a plethora of research exists, and uncovers areas where research is needed. <s> BIB002
Aiming to answer RQ.3 and RQ.4, the sample papers were classified into categories CT.3 (techniques) and CT.4 (problems) based on how their authors described the AI technique used in the study. Then, some terminologies used to define the codification for the categories CT.3 and CT. BIB002 BIB001 . All the techniques found in the reviewed papers were mapped considering the problem (CT.4) that they were solving. As a result, Table VIII -placed in the Appendix -lists the techniques found, the number of papers in which they were used, the main problems they were seeking to address, and the references. As can be seen, there is a considerable number of studies (22%,13) that used techniques related to artificial neural networks. Also, there is a reasonable number of studies reporting the use of SVM (17%, 10 Analyzing Table VIII Solver, and Viterbi Algorithm. Thus, there is room for new studies using techniques not yet used or under-represented by the set of papers considered.