The Relationship of the Information Quantity of Urban Roadside Traffic Signs and Drivers’ Visibility Based on Information Transmission

For the lack of quantitative basis of traffic sign combination information, this paper established a model of information quantity of urban road traffic signs by analyzing the driver’s information processing and the visual recognition of traffic signs combined with theories of informatics. It used various analytical methods to build a model of the relationship between the traffic sign information quantity (TSIQ) and the driver’s visual recognition. Based on factors, the relationship between the TSIQ and the driver’s visual recognition was studied and analyzed to provide a reference for the design of urban traffic sign layout information. The results show that the TSIQ can explain 61% of the driver’s recognition time (DRT). The more information the road traffic sign conveys, the longer DRT will be. The TSIQ’s threshold is 642 bits, and exceeding this value will cause information overload. Different influence factors have a certain impact on drivers’ visual recognition distance (VRD). The male VRD is shorter than the female. The VRD of the young driver is larger than the old driver. The VRD of a novice driver is longer than an experienced driver, while the visual recognition sign of an experienced driver is shorter.

A new car-following model on complex road considering driver’s characteristics

In order to explore the influence of driver’s characteristics in complex traffic flow, experienced, inexperienced attribution and the perception headway of the driver are introduced. Concurrently, an extended car-following model is established. The linear stability of the extended model is derived based on the control theory method, and obtains the stability conditions. This work verifies the impact of driver characteristics on traffic flow stability based on the open boundary simulation environment. The research results show that inexperienced driver will reduce the stability of traffic flow on complex roads, while experienced driver will improve the stability of traffic flow. Compared with the driver’s negative perception headway error, the positive perception headway error can improve the stability of traffic flow. More specifically, an experienced driver is good at predicting the state of the preceding vehicle, while the driver’s positive perception headway error tends to narrow the safe headway, and achieve the stability of traffic flow.

Control of Automobile's Automatic Parking

An automatic parking controller is proposed. Fuzzy control is taken to simulate the action of experienced driver as an alternative to conventional methods. The angle between the midline of the car and ideal path and the distance between the midpoint of the car and the ideal path are taken as the inputs of the fuzzy controller. The angle of the steering wheel is taken as the output of the fuzzy controller. A set of fuzzy logic rules are build for reasoning. With sensors installed in the car to replace people’s eyes and computer to replace people’s brain, the automatic parking system is more precise and quicker than human’s parking. At last, simulation is made and proved the validity of the proposed method.