Speed behaviour and mental workload of small-spacing expressway interchanges based on field driving test.

Many small-spacing interchanges (SSI) appear with the improvement of the expressway network. To investigate the speed and mental workload characteristics in the SSI and acquire the mechanism of the influence of speed on the drivers' workload, 37 participants were recruited to perform a field driving test. Each driver performed four driving conditions (i.e. ramp-mainline, mainline-ramp, mainline driving, and auxiliary lane driving). The speed and drivers' electrocardiogram (ECG) data were collected using SpeedBox speed acquisition equipment and PhysioLAB physiological instrument. The heart rate increase (HRI) index was used to analyse the drivers' mental workload regularity. The relationship model between speed and HRI was developed to examine the impact of speed on HRI. The results show that the speed variation in the SSI displayed two patterns: 'decrease - increase and continuous decrease.' The drivers' HRI variation presented four patterns: 'convex curve, continuously increasing, continuously decreasing and concave curve'. SSI's influenced area length is given based on the speed and HRI variation regularity. HRI is significantly higher when driving in the ramp-mainline condition in the SSI than when driving in other conditions, indicating that drivers are more nervous when merging with the mainline traffic. HRI increases significantly in the first 50% of the weaving area in four driving conditions, indicating that vehicle weaving greatly influences the drivers' mental workload. A positive correlation exists between vehicle speed and drivers' HRI without interference from other vehicles and road alignment.

The shorter spacing of the interchange will result in a more difficult driving task for the drivers. This study shows that drivers have the highest mental workload in ramp-mainline driving condition at small-spacing interchanges. The first half of the weaving area is the area where drivers' mental workload increases significantly, and is a high-risk section for small-spacing interchanges. This study can provide a reference for the revision of the allowable minimum interchange spacing in the corresponding specification, and the calibration of the simulation test parameters for similar scenarios.

Analysis on Risk Characteristics of Traffic Accidents in Small-Spacing Expressway Interchange.

Many small-spacing interchanges (SSI) appear when the density of the expressway interchanges increases. However, the characteristics of traffic accidents in SSI have not been explained clearly. Therefore, this paper systematically takes the G3001 expressway in Xi'an as the research object to explore the accident characteristics of SSI. Firstly, the expressway is divided into four sections. Furthermore, their safety can be evaluated by the number of accidents per unit distance of 100 million vehicles (NAP). Subsequently, eight indexes, such as mean spacing distance (MSD), are selected to explain the cause affecting expressway safety by developing the least square support vector machine (LSSVM). Secondly, the difference between SSI and normal-spacing interchanges (NSI) is clarified by statistical analysis. Finally, LSSVM, random forest, and logistic regression models are built using 12 indicators, such as the time spent exploring the causes of serious accidents. The results show that the inner ring NAP in Sections I and II with SSI is 27.2 and 33.7, higher than in other sections. The density, annual average daily traffic, and MSD adversely affect expressway traffic safety. The road condition mainly influences the serious traffic accidents in the SSI. This study can provide the theoretical basis for traffic management and accident prevention in the SSI of the expressway.

The Influence of Individual Differences on Diverging Behavior at the Weaving Sections of an Urban Expressway.

Urban expressway weaving sections suffer from a high crash risk in urban transportation systems. Studying driving behavior is an important approach to solve safety and efficiency issues at expressway weaving sections. This study aimed to investigate the influence of drivers' individual differences on diverging behavior at expressway weaving sections. First, a k-means cluster analysis of 650 questionnaires was performed, to classify drivers into three categories: aggressive, conservative and normal. Then, the driving behavior of 45 drivers from the three categories was recorded in a driving simulator and analyzed by an analysis of variance. The results show that different types of drivers have different driving behaviors at weaving sections. Aggressive drivers have a higher mean speed and mean longitudinal deceleration, followed by normal and conservative drivers. Significant differences in the range of lane-change positions were found between 100, 150 and 200 m of weaving length for the same type of drivers, and the duration of weaving for aggressive drivers was significantly smaller than for normal and conservative drivers. A significant correlation was found between lane-change position and weaving duration. These results can help traffic engineers to propose effective control strategies for different types of drivers, to improve the safety of weaving sections.