Core Insights - 2025 is identified as a pivotal year for automotive intelligence, initiating a three-year cycle that will elevate domestic electrification penetration rates to 50%-80%+, leading to a restructuring of the automotive landscape [4][10] - Leading intelligent driving manufacturers have successfully implemented complex urban scenarios such as roundabouts and U-turns, enhancing high-level functionalities like parking and scene understanding, thereby improving the driving experience for passengers and safety personnel [4][10] Investment Highlights - A comprehensive evaluation of six intelligent driving manufacturers, including ZunJie, Xiaopeng, Zhiji, Ideal, Xiaomi, and NIO, was conducted through large sample concentrated road tests and small sample in-depth road tests, focusing on scene implementation, takeover frequency, and comfort [5][10] - The keyword for the Beijing intelligent driving assessment is "stronger gets stronger," with Huawei and Xiaopeng leading in overall takeover counts and performance across various scenarios, particularly excelling in challenging situations [5][10] - Compared to Q1, the gap in intelligent driving capabilities among manufacturers has been narrowing by Q3, with second-tier manufacturers improving their performance in complex urban scenarios and reducing takeover frequencies [6][10] Road Test Overview - The large sample concentrated road test involved a standardized route in Beijing, assessing various performance metrics such as overall evaluation, takeover counts, stability, and efficiency [41][40] - The small sample in-depth road tests were conducted under varying traffic conditions, focusing on specific scenarios like roundabouts and complex intersections to evaluate the vehicles' decision-making and interaction capabilities [61][72] Manufacturer Performance - ZunJie achieved the highest overall evaluation score with an average takeover count of 1.16, demonstrating strong performance in challenging scenarios [44] - Xiaopeng's XOS model exhibited the lowest average takeover count at 0.94, showcasing balanced performance across various scenarios [48] - Zhiji's IM AD 3.0 received a score of 3.55 with an average takeover count of 1.44, indicating good handling of complex situations [49] - Ideal's OTA 8.0 scored 3.20 with a lower average takeover count of 1.06, reflecting a conservative driving style [52] - Xiaomi's V1.9.7 had an average takeover count of 3.86, indicating variability in performance across different scenarios [55] - NIO's cedar model recorded an average takeover count of 4.14, effectively covering most urban intelligent driving scenarios [58]

一位对理想很有感情人士向TOP2表示，他认为理想很多人挺傲的，对友商的进步优秀之处认识不充 分。给李想本人反馈XX需求时，李想喜欢用用户不需要来回应。这位对理想很有感情人士内心想法 是，根据其接触到的大量用户反馈，其实很多用户是需要的。 本文将分享一个李想认为用户不需要，但后面真改正了的成功实践。 A是L系列车主兼员工，其在高速行驶时，即使和家人同行，也有很强的希望尽量多用电需求，需求 底层源自两点，1.省钱快感。2.纯电更平顺，NVH更好。 故其在家人同行高速场景下，也会脑中计算，采用什么模式，可以尽可能高速多用电。 再加上也有其他人反馈类似需求，A希望理想OTA可以升级功能，实现更加自动化的，面向L系列车 主的高速充电规划，且理念是尽可能多用电，更方便充电，并且根据实际里程，给予新的增程器工作 算法，在尽可能多用电前提下，还尽可能少用油（理想原先的模式里，高速油电混合与纯油模式耗油 量几乎没区别）。 这个思路上报上去时，李想认为这是一个伪需求，他认为大多数理想用户高速就是多用油的，故评审 不通过。 A后面想办法，调后台数据（这个过程并不算很容易，不是直接一导就实现的，还需要挺多步骤与协 调的），发现理想实 ...