Jiushi Intelligence obtains a patent for intersection algorithms, using three-level stopping points to crack complex intersection negotiations for autonomous vehicles, moving beyond endurance and load competition to win the second half.
The competition among terminal logistics unmanned vehicles is being forced to shift from a pure arms race in battery life and payload capacity to a brutal algorithmic showdown over survival at complex urban intersections. Recently, the China National Intellectual Property Administration announced that a patent application filed by Ninebot (Suzhou) Intelligent Technology Co., Ltd. titled "Control Method, Control System, and Unmanned Vehicle for Low-Speed Complex Intersections" has been officially granted.
The approval of this new technology directly targets the systemic anxiety that most troubles R&D teams in fully driverless low-speed autonomous driving during urban capillary delivery—namely, how to navigate complex intersections where traffic lights change abruptly and unexpected road conditions interweave, without either violating traffic rules and causing rear-end collisions, or resorting to a blanket "hard-braking that disrupts traffic."
A large number of onlookers, accustomed to judging autonomous driving capabilities by flashy LiDAR hardware and autonomous driving speeds of a hundred kilometers per hour or more, tend to dismiss intersection control technology for such low-speed unmanned vehicles as a trivial long-tail optimization. This simplistic logic clearly underestimates the trust and legal costs that urban last-mile delivery faces on real public roads. In actual urban traffic, if a fully loaded autonomous delivery vehicle frequently performs "suicide hard braking" in front of crosswalks because the yellow light suddenly turns on, it not only poses a serious rear-end collision risk to human-driven vehicles behind it, but also risks compliance crackdowns by local traffic management authorities due to frequently getting stuck in the middle of intersections.
To fully understand the deeper causality behind Ninebot Intelligence's latest technological move, one must deconstruct the system's underlying actuarial logic through the intellectual property landscape on Tianyancha.
The core algorithm introduced by this emerging Suzhou-based intelligent technology company essentially uses a set of cold physical formulas to forcibly take over the unmanned vehicle's braking behavior. In actual low-speed complex intersection flow, the system does not simply determine whether to "go" or "stop." Instead, based on the navigation path, it pre-calculates and generates three progressive "stop points" with precision inside the algorithm.
The core game-theoretic causality lies in the fact that when the vehicle captures abrupt changes in the upcoming traffic light status via V2X or onboard perception, the speed management module immediately uses a specific formula to calculate the absolute stopping distance to the first stop point. If the vehicle cannot brake firmly before the first point due to excessive inertia, the algorithm does not choose a violent wheel lock. Instead, it decelerates at maximum deceleration while instantly generating a second stop point. If the system dynamically assesses that it still cannot safely stop before the second point after passing the first, the algorithm decisively "ignores" the second point and accelerates through the intersection at normal speed. Only when the vehicle has passed the second point and it is determined that it can safely brake before the third stop point does the third point take effect.
This causal driver that breaks down intersection decision-making into "three-stage verification with fault-tolerant passage" is essentially Ninebot Intelligence using more rigid physical rules to reshape the commercial value chain of terminal logistics unmanned vehicles.
For a long time, the deep-seated obstacle preventing low-speed unmanned delivery vehicles from being legally licensed for large-scale operation in all cities has been their "idiot-style avoidance" behavior at intersections, which unnecessarily consumes public transportation efficiency. With the authorization of this patent, Ninebot Intelligence has, by interlocking the maximum deceleration formula with the three-level progressive stop points at the underlying algorithmic level, essentially used pure mathematics to strike a dynamic balance between "absolute compliance" and "absolute smoothness." This not only significantly reduces hardware wear and energy consumption caused by indecisive behavior at intersections, but also provides an immutable, no-fault technical self-certification for future local compliance approvals and insurer damage assessments.
As the capital bubble in autonomous driving deflates, what tests the survival quality of an unmanned vehicle company is no longer the illusory operational mileage touted at press conferences, but its control precision at the granular level of every traffic light and every crosswalk. Ninebot Intelligence's granting of this invention for "complex intersection control" into its core asset library is a clear industry gear-shift warning: the arms race in terminal unmanned delivery has moved beyond reckless volume scaling. Whoever can first establish a perfect engineering deconstruction of high-risk, high-friction intersection scenarios deep within the chassis algorithm will be the one who truly holds the long-term bargaining power in the upcoming logistics scenario harvest.