Drinking driving is responsible for a high proportion of traffic accidents. To study the effects of alcohol on drivers and driving performance, 25 drivers’ subjective feelings and driving performance data in different blood‐alcohol concentration (BAC) levels were collected with simulated driving experiment. The investigation results revealed that alcohol affected drivers in many aspects, including attitude, judgment, vigilance, perception, reaction, and controlling. The analysis of accident rate showed that higher BAC level would lead to higher accident rate. The statistical analysis results of driving performance indicated that average speed, speed standard deviation, and lane position standard deviation were significantly higher under the influence of alcohol. They also had a statistically significant linear trend as the function of BAC level. The discrimination of drinking driving based on driving performance was performed with Fisher discrimination method. The results showed that drinking driving with higher BAC level was easier to discriminate from normal driving. Also, the results indicated that the three significant indicators on straight roadway could be used in the discrimination of drinking driving state. The conclusions can provide references for the study of drinking driving and the identification of driving state and then contribute to traffic safety.

Intelligent transportation has become a hot research field in recent years The development direction of road traffic construction in the future, the relevant technologies and methods in the process of gradual promotion and application of intelligent connected vehicles continue to attract the attention of scholars and engineers. There are more and more relevant theories, methods and systems. This paper summarizes the current state of microscopic and macroscopic traffic models, characteristic analysis methods of mixed traffic flow, and lane management methods in connected vehicle environments. At the end of this paper, the conclusions of this work are presented, and possible future directions for safety warning research under connected vehicle environments are discussed. This paper represents the current research status of traffic flow characteristics under connected vehicle environments to some extent, which can provide references for future traffic flow characteristic research in terms of framework, methods and technologies, etc.

We establish an adaptive learning support system of air traffic control, sending different teaching content to learners, in order to design a support system with adaptive learning based on aerodrome four-word codes. The system can determine learning strategies according to learners’ own learning style. Two groups of learners use a traditional learning method and an adaptive learning method, and we then determined their effects. The results show that average scores of the first group increased from 25 to 82, or about 228%; the average scores of the second group increase from 49 to 77, a growth rate of about 57%. For the first and second groups, the adaptive learning system reduced the time learners took to answer questions. We can conclude that the adaptive learning system can effectively improve the study efficiency for air traffic control learners.

Air traffic controllers’ working while fatigued threatens air traffic safety. Air-ground communication speech is related to a speaker’s physical state and can be used to identify fatigue states. To explore the effect of fatigue on speech, a tower control simulation was designed using 30 participants’ air-ground communication speech data in sober and fatigued states. The speech indices were defined and calculated, and a statistical analysis made of speech characteristic changes. The results show that speed, stability, and energy are lower in fatigued states. When fatigued, the ratio of unvoiced sound in controllers’ speech is higher than in a sober state, indicating that controllers hesitate more in decision-making. Five significant indices were extracted and used to establish an identification function with Fisher discriminant method. The evaluation and validation results showed the applicability of this method. These results provide a reference for detecting fatigue in on-duty air traffic controllers.

The purpose of this study was to analyze the effects of fatigue and tension on the physical characteristics and abilities of air traffic controllers (ATCOs) and determine their influence mechanisms. A simulated experiment was designed to evaluate the responses of ATCOs in four states: alertness, fatigue, tension, and fatigue and tension. Thirty young male ATCOs participated in the experiment. Fifteen parameters of their physical characteristics and abilities were collected and analyzed to estimate the effects and the decreasing order of influence of fatigue and tension on the indicators. The results showed that most of the parameters of the ATCOs were significantly affected by fatigue and tension. The attention, perception, reaction time, decision-making ability, and comprehensive performance of the ATCOs were adversely affected by fatigue, and tension had negative effects on their attention, decision-making ability, and comprehensive performance. Fatigue and tension impair the physical characteristics and abilities of ATCOs. Both states initially affected the physical characteristics of the ATCOs and then impaired their abilities. However, the influence mechanisms involved were different. The primary effect of the fatigue state was slowing down, whereas the effect of the tense state was instability. These results provide a reference for the evaluation and management of fatigue and tension states in ATCOs.