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The study explores the relationship between subway passenger satisfaction and passenger travel behaviour characteristics from the perspective of subway passengers. This study takes Qingdao as an example and designs a questionnaire that includes the basic personal information and travel behaviour characteristics of passengers and evaluates their subway satisfaction. A total of 6340 valid questionnaires were obtained through the combination of online surveys and on-site random surveys. By using the fuzzy synthetic evaluation, the overall score of passenger satisfaction with the Qingdao subway is determined. According to the relationship between passenger satisfaction and travel behaviour characteristics, the chi-square test is used to select the correlation variables group. The results show that there is no significant correlation among the satisfaction of subway passengers, the main means of transportation and the availability of private cars; the frequency of taking the subway is related to the satisfaction of subway passengers; and the purpose of travelling and the reasons for choosing the subway are significantly related to the satisfaction of subway passengers. Finally, based on the analysis of the differences in satisfaction under different conditions, some suggestions were proposed to improve the satisfaction of subway passengers.

Existing parking guidance systems only provide road guidance outside the parking lot but do not provide accurate guidance to specific parking spaces inside the parking lot. By using a Kalman filter, the Grubbs test, and a neural network algorithm to improve the RSSI-based location fingerprint identification technology, an accurate location method based on indoor Wi-Fi is obtained, which implements precise route guidance and a reverse search function for parking spaces. We utilize Beidou positioning to develop a Gaode map for outdoor navigation and use an integrated system of ultrasonic detector/indicators and ground locks to manage parking spaces. Through the secondary development of an Android system and the application of a MySql database, an app for precise parking guidance was developed. The system makes full use of the Internet and parking information, eliminates information asymmetry, improves the utilization ratio of the urban static traffic resources, allocates parking spaces in real-time, breaks information islands, provides parking search and recommendation functions for users, achieves parking information-sharing, and effectively improves parking efficiency and the parking utilization ratio.

At present, there is no standard or research to define the specific length of the entrance and exit sections of an undersea tunnel. In combination with the unique longitudinal slope of the undersea tunnel and the change in the illumination difference, the lengths of the lane change, transition and adaptation sections of the entrance and exit sections of the undersea tunnel were theoretically deduced, and a model for the entrance and exit sections lengths was established. Considering the Qingdao Jiaozhou Bay undersea tunnel as an experimental subject, the accuracy of the model of the entrance and exit section lengths was verified using two methods. The results indicated that the lengths of the entrance and exit sections of undersea tunnels change with changes in the factors such as the illumination, vehicle speed, and slope. In the case of the Qingdao Jiaozhou Bay undersea tunnel, when the vehicle passes the undersea tunnel at a speed of 70 km/h on a sunny day, according to the studied model, the entrance and exit sections of the undersea tunnel are 146.7 m and 157.1 m long, respectively. The entrance and exit section lengths of the undersea tunnel, determined using test method 1 and test method 2 are 151.0m, 153.6m and 161.0m, 148.9m, respectively. The absolute errors between the results of the model and test method 1 and 2 are less than 10%. These findings indicate that the model for the entrance and exit section lengths of undersea tunnels is reasonably accurate.

Pedestrian crossing chaos has become one of the significant problems of urban traffic nowadays, and the irregular behavior of pedestrians affects traffic operation and regional safety to a certain extent. Aiming at the safety of pedestrian crossing in the advance right-turn lane, the pedestrian path deviation (PPD) is proposed to quantitatively describe the pedestrian crossing path deviation and analyze the impact of PPD on pedestrian crossing safety. With four advance right-turn lanes at an intersection in Qingdao as the investigation site, the spatiotemporal information of pedestrians and motor vehicles is collected to analyze the characteristics of pedestrian path distribution and the influencing factors of pedestrian crossing under the factors of traffic flow and environment. The pedestrian-vehicle conflict characteristics are analyzed from the perspective of conflict rate and deceleration-to-safety. The severity level of human-vehicle conflict is classified according to the cumulative frequency of safety deceleration, and the severity model of human-vehicle conflict based on ordered probit is established. The results show that buildings such as large shopping malls and transportation hubs have an attractive effect on pedestrians. Under the influence of unilateral buildings, the proportion of irregular use of pedestrian crosswalks reaches 46.9%. There is a significant positive correlation between pedestrian flow and PPD index, and the increase of pedestrian flow causes the aggravation of pedestrian path deviation. The results of the analysis of PPD with pedestrian-vehicle conflict rate and conflict severity show that the increase of PPD significantly increases the risk of pedestrian-vehicle conflict occurrence; in addition, motor vehicle speed and PPD have significant effects on the severity of pedestrian-vehicle conflict, and the increase of both vehicle traffic speed and PPD causes the aggravation of the severity level of pedestrian-vehicle conflict. Combined with the above findings, the PPD index has some value in quantifying pedestrian spatial violations as well as regional safety evaluation, and the findings can provide theoretical guidance for the establishment of traffic facilities.

Lane-changing in undersea tunnels has a negative impact on the normal traffic flow, and even lays hidden dangers for the occurrence of traffic accidents. Lane-changing behavior in undersea tunnels was divided into free, compulsory, and collaborative lane-changing types according to the characteristics of traffic flow to explore lane-changing risk in undersea tunnels. A fuzzy inference analysis on the three lane-changing behaviors was conducted on the basis of the behavior characteristics of fuzzy uncertainty of drivers. The most representative influencing variables, including speed difference, initial space of vehicles, traffic density, and distance for minimum lane-changing, were selected as fuzzy input variables, and lane-changing risk was used as an output variable to construct fuzzy rules for different lane-changing behavior. Risks of the three lane-changing behaviors were simulated by MATLAB/Simulink. Results demonstrated that the compulsory lane-changing in undersea tunnel was the riskiest, followed by collaborative and free lane-changing. Slope considerably influenced lane-changing risk. Specifically, the lane-changing risk at the downhill section was the highest, and the lane-changing risk at the uphill section was the lowest. The lane-changing risk at the flat section was between them.

In recent years, there are more and more applications of traffic violation monitoring in some countries. The present work aims to analyze the vehicle speeds nearby road traffic violation monitoring area on urban main roads and find out the impact of road traffic violation monitoring on the vehicle speeds. A representative urban main road section was selected and the traffic flow was recorded by camera method. The vehicle speeds before, within, and after the road traffic violation monitoring area were obtained by the calculation method. The speed data was classified and processed by SPSS software and mathematical method to establish the vehicle speed probability density models before, within, and after the road traffic violation monitoring area. The results show that the average speed and maximum speed within the traffic violation monitoring area are significantly slower than those before and after the traffic violation monitoring area. 70.1% of the vehicles before the road traffic violation monitoring area were speeding, and 80.2% of the vehicles after the road traffic violation monitoring area were speeding, while within the road traffic violation monitoring area, the speeding vehicles were reduced to 15.9%. When vehicles pass through the road traffic violation monitoring area, the vehicle speeds tend to first decrease and subsequently increase. In its active area, road traffic violation monitoring can effectively regulate driving behaviors and reduce speeding, but this effect is limited to the vicinity of the traffic violation monitoring. The distribution of vehicle speeds can be calculated from vehicle speed probability density models.

Countdown signal control is a relatively new control mode that can inform a driver in advance about the remaining time to pass through intersections or the time needed to wait for other drivers and pedestrians. At present, few countries apply vehicular countdown signals. However, in China, some cities have applied vehicular countdown signals for years, though it is unclear how and how much such signals influence driving psychologies and behaviors compared with non-countdown signal controls. The present work aims to clarify the impact of vehicular countdown signals on driving psychologies and behaviors on the cognitive level. A questionnaire survey with 32 questions about driving psychologies and behaviors was designed, and an online survey was conducted. A total of 1051 valid questionnaires were received. The survey data were analyzed, and the main results indicate that most of the surveyed drivers prefer countdown signal controls and think that such controls can improve not only traffic safety but also traffic operational efficiency. The surveyed drivers also think that countdown signal controls have an impact on driving psychologies and behaviors and the survey results have demonstrated that the driving behaviors of female drivers surveyed are not conservative under the clear conditions of green countdown signal control. Further studies and methods concerning the effects of countdown signals on driving psychologies and behaviors are discussed.