The assisted driving system is still in its infancy in the market, and even 100,000 models are claimed to have L2 intelligent driving, so the huge and mixed market lacks a professional evaluation standard, for this reason, Cheyun Research created the "CC-400A Intelligent Driving Evaluation System" (hereinafter referred to as the "system") in early 2021.
The system is divided into four test modules for vehicle auxiliary driving ability: intelligent driving, automatic parking, navigation assistance, and innovation items, from the four modules can map out 10+ driving scenarios, 49 core capabilities and 31 basic capabilities, each with a full score of 5 points, and the total score of the system is 400 points (excluding innovation items), so as to objectively and fairly evaluate the vehicle auxiliary driving ability.
The system integrates the multi-dimensional evaluation of the auxiliary driving scenario and the car journey, and excavates the user's feelings and exposed problems at each critical moment in the auxiliary driving by building the minimum value unit of the user experience, aiming to study the development process of the auxiliary driving system of each car company, as well as building a bridge based on the experience of the auxiliary driving product between consumers and car companies, supplemented by more professional car purchase guidance suggestions.
The system is constructed on the basis of the two-state model, which can well show the user experience of a complex system, and can involve multi-dimensional analysis and evaluation of multi-user, multi-scene, multi-function, multi-interaction, and cross-time. The punctuation of the black line tends to be stable, which covers the core scene of assisted driving and its core capabilities, such as vehicle recognition ability, car stability, curvature curve efficiency, etc. These high-frequency and high-value core capabilities are the focus of our evaluation, and the punctuation away from the black line part is free, we evaluate through innovative projects, such as remote parking and other functions, to achieve quantifiable justice and fairness.
An evaluation system is not the more test items the better, we aim to restore the scenes and functions that can represent the consumer experience for testing, and "very few people use", "special time will be used", "very rare travel purposes" and "low-frequency operation" This Kinder Case is not easy to see the core experience brought to users. Therefore, the system only focuses on the core scenario and core capabilities to click through, and excavates the user's feelings at each critical moment and the exposed problems.
On the basis of the core capabilities in the core scenario, we will also pay more attention to the experience of interaction and monitoring, the basic consensus of the entire industry on the auxiliary driving experience is safety, for the driver, safety is reflected in the driver's subjective belief that the vehicle capability and the actual ability of the vehicle boundary consistency, the greater the cognitive gap, the more unsafe, and the key to solving the cognitive gap lies in the vehicle and human interaction and monitoring capabilities. Therefore, the system's evaluation of interaction and monitoring accounts for 20%, which can better explore the performance of vehicles at this level.
The current driver assistance function is still "human-led", and both humans and machines will inevitably have defects, and these defects can only be remedied when human-machine co-driving is fully considered. How to let the driver get the best interaction perception in different scenarios is also the direction of the efforts of the car companies, so on the basis of the cognitive gap model, we will also have a human-machine co-driving analysis model, even if the same ability of the auxiliary driving model, interaction will have many differences, which reflects the different emphases of car companies in assisted driving, these differences lead to a completely different driving experience, which is also a crucial point to measure the auxiliary driving function.