**1. Introduction**

Today's world is undergoing unprecedented changes in the 21th century. A new round of technological revolution and industrial transformation is in the ascendant, and intelligent networked new energy vehicles (NEVs) have become the strategic direction of global industrial development [1]. In February 2020, China's 11 national ministries and commissions, including the National Development and Reform Commission, the Ministry of Industry and Information Technology, the Ministry of Public Security, and the Ministry of Transport, jointly issued the Smart Vehicle Innovation and Development Strategy in its "Strategic Vision", which points out that: "Looking forward from 2035 to 2050, China's standard intelligent vehicle system will be fully completed and more complete. The vision of a safe, efficient, green, and civilized intelligent vehicle system has been gradually realized, and the intelligent vehicle can fully meet the people's growing needs for a better life."

**Citation:** Li, L.; Coskun, S.; Wang, J.; Fan, Y.; Zhang, F.; Langari, R. Velocity Prediction Based on Vehicle Lateral Risk Assessment and Traffic Flow: A Brief Review and Application Examples. *Energies* **2021**, *14*, 3431. https://doi.org/10.3390/en14123431

Academic Editor: Francis F. Assadian

Received: 16 May 2021 Accepted: 7 June 2021 Published: 10 June 2021

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The application of traffic information in the design of hybrid electric vehicles (HEVs) energy management is one of the important objects, wherein the adjustment of power distribution ratio based on traffic information is achieved by predicting the change of vehicle speed [2,3]. In order to achieve the goals of "safe", "efficient", and "green" for future intelligent networked NEVs, it is of great significance to predict and plan their future speed [4,5], because the above three goals are closely related to the speed, as shown in Figure 1. "Efficient" means that the vehicles in the traffic flow move at high speeds, which makes the roads more efficient. A vehicle driving at a higher speed increases the probability of road traffic accidents, so in order to drive "safely", the vehicle often slows down in advance in the condition of high traffic risk. This process leads to the change of vehicle speed and the problem of optimal vehicle speed planning. Accurate speed prediction is the key to energy management, reduce emissions, and improved energy-saving control of NEVs [6,7], that is, "green" driving. Therefore, it is of great significance to accurately predict and reasonably plan vehicle speed for balancing the relationship among "safe", "efficient", and "green" of vehicles in the future traffic system.

**Figure 1.** The relationship between "safety", "efficiency", "green", and speed of intelligent networked vehicles.

The automobile industry is now undergoing an electrification revolution. Take China as an example, in 2018, the production and sales of NEVs reached 1.27 million and 1.256 million units, respectively. In 2019, the production and sales of NEVs reached 1.242 million units and 1.206 million units, respectively. From January to December in 2020, the production of NEVs reached 1.366 million units, and the sales volume reached 1.367 million units [8].

The above data is briefly described in Figure 2. On the whole, China's new energy vehicle production and sales are greatly affected by government policy. In 2019, due to the retreat of subsidy policies, the production and sales of NEVs decreased compared with 2018. Due to the impact of the epidemic, China restored the subsidy policy of NEVs in 2020, and the production and sales increased accordingly.

**Figure 2.** Comparison of production and sales volume of new energy vehicles in China in recent three years.
