Lyu Nengchao

Design and implementation of an ARM-based embedded system for an automatic traffic cone placement and retrieval vehicle

In order to ensure the safety of the operators who work with traffic cones in the freeway, we design an automatic traffic cone placement and retrieval vehicle. This vehicle can be used to place traffic cones rapidly under the maintenance of the freeway or to isolate the scenes of traffic accidents. By placing and retrieving traffic cones automatically with this vehicle, the operating efficiency will be increased, and the security risks of operators will be limited. In this paper, an ARM based embedded hardware and software control system for an automatic traffic cone placement and retrieval vehicle is designed and implemented. This work might be a reference to the research and development of an embedded control system for such kind of equipment.

Analysis traffic safety for highway off-rampbased on visual reaction time on traffic signs

To ensure traffic safety of highway off-ramp area, it should leave enough reaction time for drivers taking corresponding actions after traffic signs. And the recognition time for traffic signs depends on information volume. In this study, traffic sign recognition process in highway off-ramp were analyzed and visual recognition time model was set up. Then, the information volume contained in traffic signs was calculated using the information theory, and the information was divided it into four grades. In order to analyze the recognition time for different information grades, a simulation driving experiment was implemented. 20 participants took part in this experiment and the time for four grades was obtained. An evaluation approached was proposed, which identifies the safety conditions of highway off-ramp into four levels according to the time ranges after recognition. The proposed traffic safety evaluation method may provide a new way to evaluate the safety for highway off-ramp for its intuitive, easy operation and reasonable, especially for setting traffic signs information volume.

Study on the Reaction Time forRoad Traffic Signs Information Volume

Driving errors may result from high workload caused by traffic signs with too much information; it could result in traffic crash significantly. Therefore, the information volume of traffic signs must keep to a reasonable level to be recognized well. In order to make drivers recognize traffic signs, the information volume that the driver could endure in different workload levels should be known clearly. In this study, we designed and implemented experiments to analyze drivers’ recognition time and workload on different traffic signs information volume. The probe Shannon Theory was adopted to measure the information volume of traffic signs; the participants are required to search the target road name from traffic signs with different information. The Reaction Time (RT) would be compared with the available visual recognition time under real driving scene conditions. If the RT was almost equal to the available visual recognition time, the information volume included in the sign was considered to be the maximum information of the sign under this situation. Subjective difficulty questionnaire was used in the experiment to value driving workload. Results indicate that the information of traffic signs will increase driving workload; the maximum information in different driving speeds is also gained through the experiment. The results contribute to a better understanding of the information volume of traffic signs in different driving speed, it also has positive effects on traffic sign design.