autonomous navigation where a vehicle builds a global map of current environment and uses this map to navigate or know its location at any point of time. Next the decision on reaction is conveyed to vehicle motion control modules that drive the necessary actuators to realize required maneuvers like lane change or acceleration or braking.
Challenges and Conclusion Nevertheless autonomous vehicles encounter several challenges. If autonomous driving is intended to improve road safety by the widespread use of vehicles with such capabilities, the safety objective must be measured against the status quo of road safety. The available testing methods needs to be improved to validate such complex systems. Concepts for the assessment of human and machine driving performance are required. Hence newer metrics may have to be defined to assess the performance. This could be a greater challenge than the development of artificial intelligence for autonomous driving itself. Secondly, technological development requires large investments that can only be redeemed by an appropriate market demand. If the market does not accept the developed product, financing further developmental steps may prove difficult. Next the autonomous vehicles would need a strong infrastructural support. For example in terms of road topology or lane markings. Collective traffic control is dependent on technologies like V2X which needs further development towards a level of maturity that allows usage in on road vehicles. Finally introduction of such cars in the market needs to satisfy legislation requirements of various markets as well as legal requirements (Who’s liable in the case of an accident?). Though it is clear that the automated systems on one hand can increase convenience and road safety it is likely to bring in some automation related risks to road traffic that is not fully known. The question of acceptance in future therefore remains significant.
Disclaimer The views expressed in this article are my own and do not necessarily represent the views of the organization I work with. o Author Akarsh K A Technical Architect Robert Bosch Engineering and Business Solutions Enthusiast for Autonomous Driving technologies working as a Technical Architect at Robert Bosch Engineering and Business Solutions with over 11 years of Industry Experience. My primary focus is on Perception related topics involving Driver Assistance and Autonomous Driving Systems with expertise in Software Engineering.
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Prospects of Autonomous Driving with Enhanced Driver Monitoring System to perform Breathe Alcohol Content Test – To ensure safeness of everyone Sam Richardson Amalraj Renault Nissan
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t gives me great excitement to watch the revolution that autonomous driving is going to create in people’s lives, not just within the automotive industry but also in multiple fields of engineering, ranging from the healthcare industry and eBooks to the entertainment industry, and that is just the cherry on top. The ocean of opportunities goes deeper on the hunt to mine down the various business possibilities in the field autonomous drive. It seems that the race to build the first fully-autonomous vehicle has only just begun. However, with the theme “The World of Tomorrow,” GM presented an audacious vision of America two decades early. Futurama, revealing an automated highway system complete with self-driving cars. The success of autonomous driving purely depends on bridging the existing driving challenges within the vehicle components, its robust behaviour in the environment and the homologation that varies from country to country, in order to provide a safer and more comfortable driving experience to the driver. In present-day high-end cars, the number of electronic component units (ECU) that are embedded into cars varies between 80 to 120 nos. In the days to come, this number will go higher. Keeping this in mind, some of the leading chip processor manufacturers like Qualcomm and Intel already have research in place to develop the advanced processing units required for autonomous driving. With growing volume of big data around us and increased IoT infrastructure scaling, analysis of any kind descriptive, diagnostic, prescriptive and predictive levels have been made highly viable. In recent years, investors in Silicon Valley and across the globe have been pumping in more revenue into research for self-driving cars. The autonomous vehicle manufacturing vertical raked in $10.3 billion worldwide in Venture Capital financing across 146 deals in 2018 according to PitchBook
The Futuristic Medical Benefits off SelfDriving Cars: In 2015, more than 38,000 people died in motor vehicle accidents as per the National Safety Council. 26 percent of
