Intelligent Transportation by Robin Li: V2X Is a Key Accelerator for Application of Autonomous Driving

robin li
(Source: Baidu)

On Thursday, Robin Li, Cofounder and CEO of Baidu, launched his new book entitled “Intelligent Transportation: Significant Transformation Over 10-40 Years Influencing the Future of Humanity.”

The new book discusses a wide range of key aspects of intelligent transportation, including intelligent transportation operators, intelligent signal control, intelligent parking, vehicle-to-everything (V2X), intelligent highway, intelligent cars and autonomous driving, maps, Mobility-as-a-Service (MaaS), carbon neutrality, and the era of human-machine integration. The discussion is illustrated by numerous real-world case studies from across 30 cities, providing practical reference for future applications.

(Source: Baidu)

Among the insights from the book, Robin points out that the technology of V2X is key to truly realizing fully autonomous driving, as complete autonomous driving cannot only rely on a single-vehicle’s intelligence, but also a fully intelligent system of cars and roads all connected together.

Baidu’s V2X is the technology that conducts real-time communications between a vehicle and any entity that may affect, or may be affected by, the vehicle on the road. With the collection, integration and processing of real-time data and transportation information, V2X will enable automatic safety functions in vehicles and the collaborative management of roads. It is a necessary path to the widespread application of autonomous driving based on the development of single-vehicle intelligence.

Baidu’s V2X technology is powered by Baidu AI Cloud, an engine driving strong growth for the firm and its autonomous driving business. According to Baidu’s 2021 Q3 financial results, Baidu AI Cloud achieved 73% growth year-on-year.

With Baidu’s V2X technology, the cost of hardware for an autonomous driving vehicle, which is currently around 1 million yuan ($156, 907), can be lowered. It is estimated that, if taken to its fullest extent, cost reduction for smart car manufacturing could reach 90%–95%. With interconnected sensors on vehicle and roads, V2X can also achieve sensing beyond the visual range, which brings higher safety. Besides, V2X can be applied to optimize for all scenarios with an efficiency that is much higher than that of single-vehicle intelligence. According to calculations, an intelligent transportation system based on V2X will increase traffic efficiency by 15%–30%.

In terms of application, Beijing Apollo Park was inaugurated in Yizhuang, Beijing in May 2020. It is the world’s largest test site for autonomous driving and V2X applications. Baidu deployed the ACE smart intersection solution at this site. It has been deployed at 28 intersections. Baidu’s innovative and leading ACE smart intersection solution has set the standards for new infrastructure traffic intersections in China.

SEE ALSO: Baidu CEO Robin Li Said Both Baidu and Tesla Are Adopting A Step-By-Step Engineering Approach to Autonomous Driving

Baidu has cooperated with local governments to promote its intelligent technologies. In August 2020, Guangzhou’s Huangpu District, Guangzhou Economic and Technological Development Zone, and Baidu Apollo launched the Autonomous Driving and V2X Intelligent Transportation New Infrastructure Project for Huangpu District and Guangzhou Economic and Technological Development Zone. They deployed urban Cellular-V2X standard digital foundations, intelligent traffic AI engines, and six city-level intelligent traffic ecological application platforms on 133km of open urban roads and at 102 intersections in Huangpu District in this large-scale project. They were connected for use with the existing traffic information system, achieving significant results.

In the project area of smart signal control in Guangzhou Huangpu Science City and Knowledge City, 57% of intersections were self-adaptive and more than 3,600 daily optimizations were performed. The average delay of vehicles at intersections fell by approximately 20% and the wastage of unused green light periods was decreased by around 21%. The average travel time on each road decreased 25% and the number of red lights at which vehicles must stop was reduced from 3-4 to 0-1.