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.

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.

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.

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.

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.

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.

• All contents of the awarded VR data is the copyright of each applicants.
• The submitted VR data will not be distributed, but FORUM8 has a right to use the data and works, edit and reproduce the images and videos etc. and post or introduce it on website, magazines, books, newspaper etc. as a sales activity or an advertisement as a secondary user of VR data.

• Detail Page
• Prize-winning works and results

• Detail Page
• Prize-winning works and results

• Detail Page
• Prize-winning works and results

• Detail Page
• Prize-winning works and results

Virtual Design World Cup
The 2nd Cloud Programming World Cup

• Detail Page
• Prize-winning works and results

Virtual Design World Cup
The 1st Cloud Programming World Cup

• Detail Page
• Prize-winning works and results