A multifaceted change that encompasses technology, regulatory and societal impacts is impacting the automotive and transportation industries. The safety, sustainability and orderliness of people's mobility are the ultimate goals of this transformation. As far as automakers are concerned, the specific manifestation of this transformation lies in the active promotion of vehicle electrification and the development and application of autonomous vehicle technology.
It is clear that fully autonomous vehicles without human intervention are extremely attractive. As automotive technology and the digitalization of development processes continue to evolve, revolutionizing the way we interact with cars and the way we get around is a timely trend. From a business transformation perspective, autonomous driving technology will fundamentally disrupt the automotive and transportation industries. First, autonomous vehicles will change the nature of automotive products, transforming from mechanical products to multi-domain integrated technology products (Figure 1), and it can be said that autonomous vehicles are the combined effect of traditional mechanical systems (such as braking and steering) and advanced software and electronic devices required to achieve the "sense-think-act" function. For manufacturers of autonomous vehicles, this means a shift in their values and their development priorities.
Autonomous vehicles will become high-tech products that combine complex and advanced hardware, software and mechanical systems
As the driving automation class approaches SAE 5, this disruptive change is bound to be unstoppable. Some experts predict that connected autonomous vehicle technology will drive changes in the way consumers use or access private means of travel, and the transportation-as-a-service (TaaS) model will follow the trend. The basic idea behind transportation-as-a-service is that most consumers will no longer own a private car. Instead, customers can use ride-hailing services as needed to choose their desired transportation from a fleet owned and operated by a transportation company. In this way, consumers can not only get rid of the high costs associated with vehicle maintenance, insurance and fuel, but also improve the utilization rate of each vehicle.
Such a system would bring about dramatic social change and be very different from traditional automotive business models, with benefits such as improved road safety, reduced traffic congestion, lower vehicle ownership costs, and a significant increase in the probability of high-quality travel, bringing personal freedom to more people.
Based on the above, the immediate problem we need to solve becomes how to continue to promote the technology of autonomous vehicles. In this process, the biggest challenge is to train autonomous driving algorithms so that they can perceive and understand the driving environment, paying particular attention to so-called "edge situations". In addition, the need for a robust system of sensors, actuators, and computing devices to ensure that it can respond to perceptual stimuli in a fraction of a second will remain a challenge that autonomous vehicle system engineers must overcome.
There is no easy way to solve this problem. However, we estimate that the development of fully autonomous vehicles depends on the ability to integrate advanced simulation solutions to build an integrated closed-loop process around a complete digital twin. Such digital twins will serve as the foundation for a connected, cross-domain product development process, helping engineers develop and integrate multiple complex systems to build autonomous vehicles faster while reducing error rates. This process may include sensor placement and integration around the vehicle, counting the number and layout of devices, and encapsulating individual systems into the bodywork. As vehicles become more complex and advanced, simulation will become an integral part of assisting real-world testing. Simulation helps train the decision-making algorithms responsible for guiding autonomous vehicles and enables testing of a wide variety of motors or machine electronic systems at a faster and more efficient pace than real-world environmental testing. It is true that certain real-world environmental tests are inevitable in any case, especially to meet certification requirements, but adopting an integrated approach will allow autonomous vehicle engineering teams to more effectively investigate and account for abnormal road scenarios, thereby improving the safety of their autonomous vehicle systems.
There is no doubt that new approaches to vehicle development are urgently needed. Manufacturers of autonomous vehicles must embrace digitalization, breaking down the boundaries that often exist between different engineering fields and different stages of product development and manufacturing. The key to this approach is a complete digital twin that captures all aspects of vehicle design and production. With the help of digital twin technology, manufacturers of autonomous vehicles are able to connect engineering teams in the electrical, electronic, software and mechanical fields to improve the ability to design, validate and validate entire autonomous vehicle platforms, ensuring the highest standards of safety, reliability and passenger comfort.
—Nand Kochhar, Vice President, Automotive and Transportation, Digital Industrial Software, Siemens