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Towards Smart Transportation in China: The Evolution and Status quo (2/2)

Driving forces and future trends

· smart transportation

{{{Richard Huang}}}

The last section analyzed the rapid deployment of smart transportation starting in 2016. The three key catalysts for implementation success are policy guidance and implementation, technology advancement, and industry and enterprise progresses.

Strong policy guidance and implementation

Unlike most of the Western markets, where industry-led applications would push for the coordination of the municipal and central governments, the acceleration of smart transportation solutions in China is government-led instead of industry-led. The key factor that necessitates this approach is the scale of deployment. A Chinese city is typically similar in size to a whole country in other parts of the world. The city at this scale exaggerates the complexity of stakeholder relationship, requiring much more resources and coordination to mobilize different stakeholders. Therefore, it is more suitable for the government to play the role of guidance and coordination.

Digging further into the different roles of the government, we observe that the central government typically sets the tone, while the local governments are in charge of the implementation. The competition among the local governments accelerates the progress of smart transportation solutions and cultivates multiple forms of partnerships.

Technology advancement

Preceding the government guideline to promote technology, stakeholders increasingly realized that the advancement of 5G, cloud computing, big data, Internet of Things, Artificial Intelligence, and Blockchain are at the heart of smart transportation development. In fact, they are enablers. These technologies could all be classified into the broad spectrum of Chinese government's new infrastructure development initiative. They drive the practical applications of smart transportation in many industry verticals. For example, many technology giants and emerging players such as Megvii have heavily invested in image processing technologies, which is the most mature, complete and deepest application field for semantic and structured processing of images and video data. Through the enablement of Artificial Intelligence and 5G, image processing in smart transportation might not only be applied in transportation modes such as railways, highways, waterways, aviation independent passenger, and cargo transportation; but form a digitized, three-dimensional intelligent service network that could monitor, analyze, and intervene the real-time situation, advancing the customer experience.

Industry and enterprise progress

The push of private sector players fuels innovation and deployment of financial resources towards smart transportation. When deploying large capital expenditures upfront, private market actors might achieve first mover advantages in future sizable markets in the long run. As major internet and automotive companies as well as startups rushed into the field, different players tried to leverage their unique competitive advantages in winning the deals from the government.

One type of players is thereby building on their existing ecosystem to capture the needs from the customer side and use the customer adoption as the main driver for deployment from the bottom-up. For example, Tencent leverages on the high-frequency usage of WeChat and widespread adoption of WeChat Pay to promote mini-programs for organizing transportation and paying for parking lots without the need for cash. Baidu built on its Baidu Map infrastructure and increased its investment in Artificial Intelligence and open sourced its Apollo vehicle-road coordination solutions.

Baidu's Apollo vehicle leverages on the strength of Baidu Map infrastructure (Source: Internet)

Another common type of players targets primarily governments to large scale project needs, develop solutions and later deploy them at scale across the country. For example, Huawei started from hardware to build ICT product solutions along with the infrastructure development. Alibaba combined the strengths of Alibaba Cloud and Amap ("Chinese Google Maps") to create the City Brain platform which is database to seamlessly coordinate pedestrians, vehicles, roads, and public services. Many specialized providers followed the footstep of Alibaba and developed specialized solutions based on the tailoring solutions for the local governments.

The Hangzhou City Brain project piloted the development of smart transportation

Hangzhou piloted the smart transportation development through its project, Hangzhou City Brain Project, which combined the private sector involvement with the strong top-down government involvement. As a city with very rich tradition, Hangzhou has become a modern Chinese metropolis with 9+ million people. It is also home to internet giants such as Alibaba. The road system, with thousands of intersections, forms a complex transportation network, with more than 2 million trains, 9,000 buses, 300-500 bus routes, 7,000 stations, and 3-4 million daily passengers. In 2015, Hangzhou was ranked as the 5th most congested city in China and the 30th most congested city in the world by TomTom.

The planning of the Hangzohu smart transportation system started in 2016, but the structure of the City Brain project was first introduced only in June 2018 at the World Transport Conference. Amap and Alibaba Cloud, two subsidiaries of Alibaba, jointly released the concept. The concept of City Brain can be divided into left-brain and right-brain. The "left brain" is the traffic governance solution, serving the government departments, while the "right brain" is for city smart travel solutions, serving the end-users. The City Brain possess the characteristics of interconnected, real-time, intelligent, and open.

The launch of Hangzhou City Brain project in 2017 (Source: Internet)

The service to both government and users was introduced by Amap, the location services provider under the umbrella of Alibaba. Traditionally, the typical smart transportation solution could only cover the command and control function of the traffic governance system. However, in order to allow end-users to be a part of the ecosystem, the system needs an interactive platform and real-time geospatial data to allow vehicle-road coordination. Amap, therefore, is a bridge between the traditional sensors and intelligent platforms.

The service model under Hangzhou City Brain (Source: Amap)

The system can provide industry users with four major solutions: basic warning, intelligent induction, incident management, and automatic judgment. The system also realizes three innovative functions: linking in the real-time, redistributing users through navigation, and optimizing signal timing. The main purpose is to use existing data and artificial intelligence algorithms of Amap to quickly solve traffic problems in cities.

The core technology mainly comes in two forms: on the one hand, the IoT technology solutions could upgrade the traditional sensors by adding IoT features to traditional traffic electromechanical facilities and sharing the network, control and information exchange through the governance platform. One the other hand, City Brain could also install new IoT facilities. We typically position today's infrastructure as the functional infrastructure. For instance, the cameras installed on the road today typically only have a single function: some only deal with violations of traffic laws, some only monitor traffic. To achieve different functions, many cameras are needed even on one road. The new IoT facilities may include innovations such as LIDAR, electronic license plates, vehicle-road collaboration, traffic light control devices. This could allow the system to push real-time traffic information and direction to individual drivers 2 kilometers away when emergency or redirection occurs.

An interesting use case is the automatic timing control of 104 light signals in Xiaoshan District, Hangzhou. In its first year of operation, the City Brain project was able to increase the average speed of traffic by 15% and shorten the passage time by 3 minutes. With the new IoT facilities installed, the system can detect the location of the vehicles driving to the bridge individually. If there is an emergency situation, the vehicles turning right would be redirected out of the emergency lane. The coordination of information made good use of public resources and significantly reduced the congestion.

Similar to traffic control, more extensive applications of the City Brain project were found in the fields of self-service check-in, travel assistance, and smart parking. While providing social benefits, the City Brain project has also tackled the information barriers between government departments and provided data support for improving city governance. According to Mr. Chen Weiqiang, vice mayor of Hangzhou, the City Brain platform solved the data silo challenge and integrated Hangzhou's 52 government departments and 760 information systems into a unified big data platform.

One year into the City Brain project, Hangzhou fell from 5th to 57th place in China in the traffic congestion ranking of Chinese cities by TomTom. The model has been replicated to other major and even lower-tier cities as a successful case study of smart transportation.

Future direction of development

With early success cases, the deployment of smart transportation systems has entered into the era of scaling. This follows pilot projects carried out by cities such as Hangzhou. Here are the five main industry trends that could potentially take place in the next ten years:

Transportation systems will shift from regulation-centric to user-centric. As we enter the era of the next generation of smart transportation systems, applications would quickly emerge with the guiding principles from the government. With a more competitive and mature market, providers would increasingly focus on intelligence, networks, responsiveness and on-demand features, which will create more benefits for end users (city residents).

Ecosystem players will likely consolidate the market and specialize. The large players will increasingly strengthen their relationships with cities, such as Alibaba in Hangzhou and Tencent in Shenzhen. The ecosystem of intelligent map, cloud, traffic, digital payments and other add-on services will create a more integrated user experience. Matthew effect will likely happen, as stronger players gather more data, customers, and capital to improve the customer experience. Moreover, similar to the diverging priorities of Baidu Map and Amap, the top players will start to specialize based on the functions and sectors and start to leverage more on economies of scale and experience.

More smart transportation solutions will emerge. The definition of smart transportation would continue to broaden to potentially include applications such as mobile retail and autonomous driving.

Digital legislations are on the way. Commercial applications still face laws and regulations, standards and norms, business models and other issues. In March 2020, Hangzhou legislated for urban brain. Therefore, the next step will be to explore special legislation for autonomous driving and ensures the standardization and scalability of the applications in a more universally applicable level.

All opinions expressed in this essay represent our personal views only.

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