借助UC-win / Road插件支持驾驶员的认知行为功能，通过驾驶员的注视跟踪信息来生成适当的语音通知。例如“环顾四周”。 合成的语音可以表达诸如愤怒，喜悦和悲伤之类的情绪模式，并且根据驾驶员的情况来选择情绪（例如，紧急回避）。 这项设计旨在减少交通事故。

Our team plans to develop a plugin of UC-win/road that supports a driver's cognitive behavior. Our plugin produces suitable synthetic speech by using the driver's gaze tracking information. For example, if a driver does not look both ways, the plugin alerts him by using synthetic speech "Look around". Moreover, the synthetic speech can express some emotion patterns such as anger, joy, sadness, and so on. The selection of emotions depends on driver's situation, e.g., emergency avoidance. We think our plugin can decrease the number of traffic accidents.

本作品是使用自动驾驶技术和物联网功能来提高紧急车辆通行效率的作品。 EVP会提前提前向私家车发送回避命令消息，以便其他车辆的驾驶员可以让路。 如果驾驶员没有快速响应，也可以指示驾驶员自动改变车道。 这实现了该插件的主要目的，即尽快驾驶应急车辆。

In order to improve the traffic efficiency of emergency vehicles, with the help of the technology of autopilot and Internet of Things function, EVP can send avoidance command messages to other civilian cars front in real time, and help other drivers make ways in time. Or even make other vehicles automatically direct the lane-changing tasks if their drivers fail to respond quickly. Thereby realizing the main goal of the plugin - let the emergency vehicle pass through as soon as possible.

由于“潮汐现象”，每天早上进入城市的汽车流量大，而反向流量小。 另一方面，交通在夜间从城市流出，交通拥堵变得更加严重。 在这项工作中，使用可变车道来改变交通流量，从而避免了这种情况。 换句话说，在早晨，流入城市的车道数量增加，在夜晚的高峰，去往城市的车道数量减少，离开城市的车道数量增加。
Because of the "tidal phenomenon" of traffic, the traffic flow in the direction of entering the city is large and the reverse flow is small every morning, while the traffic flow in the direction of leaving the city is large at night, which aggravates the congestion phenomenon. In view of this situation, traffic organization is carried out in the way of variable lane in the transformation of traffic diversion, that is, increasing the number of lanes in the direction of entering the city, reducing the number of lanes in the direction of leaving the city, increasing the number of lanes in the direction of leaving the city in the late peak, and reducing the number of lanes in the direction of entering the city in the way of increasing the number of lanes in the direction of leaving the city in the late peak.

这个世界正在被数字孪生所复制构造。通过融合全景相机和Lidar传感器来获取有关车辆周围环境的信息，并使用YOLO将融合传感器的同步图像用作训练数据来检测其他车辆和物体。 此外，可以直观地掌握驾驶员的意图，并且在具有该信息的数字世界中，可以从CAN总线网络获得车辆状态，并可以看到现实世界

We constructed the digital twin which is a digital replica of a living world.
We got information about the surroundings of the vehicle by fusing panoramic camera and Lidar sensor.To detect other cars and things, we used YOLO with synchronized Images from fused sensors as training data.Additionally, we can apprehend driver's intention through his/her eyes.In the digital world with that information, we get our vehicle's status from CAN bus network and we can monitor the real world.

尽管无人驾驶汽车可以在城市中行驶，但与汽车不同，自行车的运动轨迹很难预测。 这项工作的主要目的是开发一种自动驾驶策略，该策略考虑到城市环境中的横向干扰，从而使自动驾驶汽车即使受到自行车的横向干扰也能像手动驾驶一样进行操作。 目的是改变原来的自动驾驶算法。

When a self-driving vehicle is driving under urban conditions, cyclists may appear around the vehicle. The trajectory of cyclists is different from that of vehicles traveling on the road, which is more difficult to predict. The main purpose of this work is to develop an automatic driving strategy considering the lateral interference under urban conditions, and modify the original automatic driving algorithm of the driving vehicle so that the automated vehicle can drive anthropomorphically under the lateral interference of cyclists.

本作品的目的是开发一种使用UC-win / Road的仿真系统，实施基于CVIS（协作车辆基础设施系统）增强的安全提前警告算法，并通过模拟器测试对其进行验证。在这项工作中，首先，使用UC-win / Road和座舱构建基本的驾驶模拟器，并创建交叉路口场景。接下来，通过使用UC-win / Road SDK获取交叉路口场景中本车（HV）的实时信息和交叉路口的目标（车辆或行人）信息，可以指定交叉路口的碰撞风险。 另外，还通过UC-win / Road和驾驶模拟测试验证了用于提示信息提示的车载HMI（人机界面）硬件。

The objective of this work is to develop a simulation system under UC-win/Road environment, to implement an enhanced safety pre-warning algorithm based on CVIS (Cooperative Vehicle Infrastructure System), and to demonstrate the algorithm by simulator operational test.
Firstly, UC-win/Road and cockpit are used to build the basic driving simulator, and to construct conflicting intersection scenarios. Secondly, the UC-win/Road SDK is used to acquire the real-time information of host vehicle (HV) in the intersection scenarios, as well as the target (vehicle or pedestrian) information in the intersection. Next, the intersection collision risk is identified according to the real-time interactive data ; Finally, the hardware of on-board HMI (Human-Machine Interface) are developed for pre-warning information prompt. The above functions are demonstrated on UC-win/Road and driving simulation tests.