When it comes to visions for future road transportation systems, what can you imagine? I think most people’s first reaction is autonomous driving. Yes, many new energy and new power car companies, represented by Tesla, are investing heavily in research on intelligent driving, hoping to achieve an early breakthrough in autonomous vehicle driving and completely liberate human hands and feet.
But Ford, a long-established American car company, has a different plan. In the 2023 Mondeo we tested today ( parameters | inquiry ), we experienced the prototype of Ford's vision for future transportation: the V2I vehicle-road collaboration system. Its basic concept is based on mobile cellular networks to realize network interconnection of all traffic participants such as vehicles, road facilities, and pedestrians, share traffic dynamics and intentions, and form a complete set of smart transportation IoT systems to improve traffic efficiency and traffic Safety.
Of course, this is a relatively ideal goal. For now, Ford has developed six major vehicle-road collaboration functions for China's traffic conditions, namely traffic light signal push, green wave speed, green light start reminder, red light warning, road Information broadcasting and electronic road signs are used to improve intersection efficiency and reduce urban congestion. Therefore, in this test drive event, we focused on experiencing this vehicle-road collaboration system to see to what extent it can help drivers.
This system is currently in a "666" status. This does not mean how complete it is, but it means that it is currently configured on 6 Ford models, has the above 6 major functions, and will be implemented in 6 major cities. Be the first to pilot. To put it simply, these 6 functions are able to process some relevant information based on the traffic conditions of some intersections under the navigation route.
For example, it can remotely push traffic light information at the intersection ahead, including light control status and countdown; for example, it can monitor driving status and promptly warn the driver when there is a red light ahead; for example, its "green wave speed" function can be combined with the current The driving status and the countdown of the green light ahead use color changes to predict the probability of smooth passage.
After actual experience, this system does realize the above functions and can help the driver to a certain extent, but this system also shows great limitations. Although the Ford manufacturer claims that this system has been put into mass production, the real difficulty with this system similar to the Internet of Things is not the cars, but the transportation facilities and other traffic participants.
In the Guangzhou area, this vehicle-road coordination system is currently only open at 102 intersections in Huangpu District, and its scope of application will be wider in the future. Since its function is based on the in-car navigation system, it will only be activated when navigation is turned on and passes through its relevant intersection. If navigation is not turned on, or there is no corresponding intersection, then this system cannot provide services.
The second is the handling of some details. If the straight ahead route has a red light and the driver temporarily decides to enter the right turn lane with a green light, its route update speed is lagging behind and the driver will still be warned loudly to be careful about running the red light. In addition, even at intersections where the function has been activated, its activation probability is not 100%, and there is a phenomenon of sometimes working and sometimes not working.
I admire Ford's ambition and layout, but how do you evaluate this vehicle-road collaboration system that is still in its infancy? To me, it looks like a few-month-old baby with endless potential for future development, but right now it's still in a state of needing more help than providing value. Ambitious goals are important, but it is also crucial to take every step in front of you in a down-to-earth manner.
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