As per data from the Us Department of Transportation’s National Highway Traffic Safety Administration (NHTSA), 94% of car accidents occur due to human miscalculation. Road safety and transport agencies emphasize on self-driving cars that reduce fatal road accidents to reduce human error. Autonomous trucks are commercial vehicles that implement AI to streamline the operation from shipping yard operation to long-distance delivery. AI in transportation uses long-range, high-resolution sensors, the extensive neural network that identifies patterns based on previous data for automation in vehicles. With the proliferation of e-commerce and next-day delivery, trucks play a pivotal role in the operation.

Game-changer in shipping and logistic

Autonomous vehicles can be a game-changer in shipping and logistics due to low freight and logistics cost, increased fuel efficiency, and reduced delivery time. These vehicles can be a boon for industries that struggle with expanding labor shortages and optimum delivery time. According to the American Trucking Association, there would be a shortage of 174,500 drivers by 2024, mainly for aging personnel and the absence of young drivers. On the other hand, unrestricted driving hours, capital utilization is core to a shorter delivery period in the domain of e-commerce.

65% of consumer goods in the US are transported by road. With full automation, the overhead cost will reduce by 45%, and will save between $85 to $125 in the transport industry. With better operational efficiency, autonomous trucks can lower logistic costs, improve truck utilization, fuel efficiency, and reduce delivery time. AI in transportation can streamline operations, address many issues, and can become a vital tool to avoid human error and traffic.

(ADAS) and high-performance computers are required

AI has a profound impact on the transportation industry. AI implies an intricate system of sensors, radars and cameras to pave a way through the traffic without human assistance. Premier automobile manufacturers like Tesla, BMW and Audi are doing extensive research work on automotive vehicles. Manufacturing automotive vehicles is an intricate and challenging task. V2X (vehicle –to- everything) is the first step for a fully autonomous driving system. More reliable, redundant, and real-time network-based structures are needed for autonomous driving.

Advanced driver assistance systems (ADAS) and high-performance computers are required to integrate a driverless system. An intricate system using human-machine interfaces (HMIs), high-resolution mono or stereo cameras (RADAR and LIDAR), a large 4K/8K screen display is required for autonomous vehicles. A state-of-the-art electronic system will process these vast data generated by this equipment, comprising of high-speed data nodes, cables, links and assemblies. The incorporated system within the autonomous vehicle processes the information precisely to ensure safe operation and progression of the car.

Autonomous vehicles can improve the public transportation

Traffic is snarling in big cities; autonomous vehicles can improve the public transportation system, lower car ownership by facilitating efficient, user-friendly, economical on-demand transportation systems even in remote areas. On the other hand, traffic congestion can increase if passengers find autonomous cars more appealing than riding public transport. Autonomous vehicles would be more economical, as one need not pay the fee of the driver. Using these cars would be more cost-effective than owning a car. Major blockage to make the autonomous vehicle more mainstream is to segregate it from regular driven cars. These cars need dedicated lanes, with fewer intersections and traffic lights and signs transmitting interactive signals to these vehicles.