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Transportation Industry Future Development

Johnny C.H. Lok

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⦁Non-manual driving transportation tool market developmentIf Non-manual driving vehicle manufacturers expect their (AI) automatic vehicles can attract drivers to buy. I feel them to need to consider how (AI) driving machine learning system can achieve these requirements in order to satisfy manual driving vehicle drivers' requirement to change their traditional driving habit to choose non-manual driving needs. It means (AI) driving machine learning systems can help them to drive vehicles to replace manual driving vehicles on the road. This is the main factor to influence car buyers choose to buy intelligence driving vehicles replace to manual driving vehicles. I believe (AI) non-manual driving vehicle machine learning systems, need to be designed as driving safety by preventing accidents from happening. Every year, drivers are facing a large number of casualties, due to traffic accidents. The amount of killed and injured road traffic related accidents is increasing every year. The real cost of an accident can go well beyond the limits of immediate material destruction, and is impossible to evaluate.Hence, researchers and car manufacturers are looking for solutions in order to reduce the amount of accidents. They already developed a considerable set of technologies in order to decrease the amount of casualties. Most of them ( like airbags, seat-belts, anti-lock systems, shock absorbing car bodies) are efficient in decreasing the impact of an accident, and in protecting the passengers of the cars. The technologies already saved a lot of lives, but they are rarely able to avoid accidents because they do not anticipate them. Moreover, if they are protecting in many cases, the passengers of the car, they do not prevent most traffic participants, like pedestrians on bicyclists from getting injured. it causes (AI) non-manual automatic car manufacturers need to consider how to design machine learning safety system is to prevent accident from happening instead of just reducing their impact.This can only be possible using intelligent systems that can observe the driving environment, reason and decide if there is a danger, determine how to avoid it and act if necessary (2)Reducing energy consumption by optimizing the driving.Nowadays, global air pollution is serious. (AI) non-manual driving car manufacturers need to concern how to design (AI) machine learning system can reduce degree of air pollution to be the most minimum level to compare to traditional manual driving vehicles.The reduction of energy consumption if certainly one of the main challenges. Transportation is one of the major factors in fossil energy consumption, and it is also responsible for a large amount of CO2 pollution. It is difficult to ask individuals to voluntarily limit the use of their vehicle of they do not have a strong incentive to do so. Specially in regions where vehicles are needed to drive to go to work every day. It stands to reason that if it is difficult to decrease the amount of vehicles, part of the solution is to make them more energy efficient.Hence, non-manual driving car manufacturers need to design how to improve engines, which are more optimized and need less fuel to operate, and hybrid and electric cars have been developed and are continuously being improved. But we can go beyond these solutions that do not take into account the environment in which a vehicle is driving. A growing number of scientific contributions presented intelligent systems used in order to improve energy efficiency and reduce fuel consumption, based on the optimization of the way (AI) non-manual driving (AI) vehicles are performing. Such as recharge batteries and electric engine will be predicted the popular fuel in order to limit fuel consumption to future (AI) non-manual driving vehicles. They can reduce air pollution, consume less fuel for (AI) non-manual driving vehicles.

194 pages, Kindle Edition

Published January 16, 2021