# Research on Geometric Design Standards for Freeways under a Fully Autonomous Driving Environment
###### Abstract
The driver's reaction time is mainly controlled by factors such as age, gender, psychological and physiological conditions, driving experience, and driving skill proficiency. It is difficult to ensure the timeliness and uniformity of information processing by drivers. For this reason, countries often need to take into account the needs of low-level drivers when designing geometric standards. As a result, the value of the specification is relatively conservative, and it is a great waste of engineering construction and land resources. In a fully autonomous driving (L5) environment, the on-board sensors of autonomous vehicles act as the driver's sensory organs, thereby sensing the driving status of surrounding vehicles and road traffic environment information. The vehicle's central processing system acts as a human brain. It analyzes, fuses, and processes the information perceived by the sensor and finally gives out instructions to control the vehicle's operation. In addition, the roadside monitoring system will also collect the road traffic flow, road conditions, and road alignment information back to vehicles in time [4; 5] to improve road safety and driving efficiency. In this process, the vehicles are not isolated from each other. With the help of the Internet of vehicles [6], autonomous vehicles use an in-vehicle intelligent system to monitor the driving conditions and surrounding traffic environment information in real time and share this information with other vehicles in a timely manner. The ability of information acquisition and decision making of an autonomous vehicle is much better than that of a traditional driver. Autonomous vehicles can quickly perceive and recognize obstacles, which takes much less time than the driver, and the perception results are more accurate. The central processing system quickly analyzes and calculates the obstacle information and vehicle's driving state information and then sends a braking command to the vehicle's control center to achieve emergency avoidance. Therefore, the reaction time of autonomous vehicles must be shorter than traditional drivers, and the braking success rate is higher. With the support of Internet-of-vehicles technology and high-precision satellites, through the interaction and transmission of information, autonomous vehicles can predict their driving environment and driving route in advance [7]. As a result, under the premise of no emergencies, vehicles can drive smoothly and safely on straight lines or curves with suitable angle, speed, and acceleration. When driving on a curve, the uniformly changing acceleration of autonomous vehicles can reduce the impact of the lateral motion of the vehicle and improve the driving stability and passenger comfort [8]. To sum up, in a fully autonomous driving environment, the vehicle is no longer controlled by the driver, and human factors no longer affect traffic safety. Vehicle operation does not need to consider the driver's psychological and physical characteristics, but passenger comfort at high speed still needs to be considered. Therefore, in a fully autonomous driving environment, autonomous vehicles have different requirements for the geometric design standards of highways. The current road design standards in various countries are not fully applicable to autonomous driving. Existing freeway transport standards and infrastructures need to be retrofitted to match new requirements and create an adaptive, comfortable, and economical operating environment for autonomous vehicles. It will be a while before fully autonomous driving technology is successfully achieved. There will be a transition period between the human driving phase and the autonomous driving phase. At present, the geometric design of freeways in China still adopts the road design standards and specifications under the manual driving environment. However, many scholars have begun to explore and study how to build an intelligent freeway that can support unmanned driving in the future.