This paper delves into the effects of a toroidal propeller’s geometrical characteristics on its thrust and efficiency. The focus is on three distinct numerical distributions: the outward inclination angle, the pitch angle, and the number of blades. The Reynolds-Averaged Navier–Stokes (RANS) method is employed to analyze the propeller’s open-water performance, taking into account cavitation flow, and a test bed was constructed to verify the rationality of CFD simulation. The findings reveal that the toroidal propeller’s efficiency and thrust coefficient initially increase with the outward inclination angle, followed by a decline; the angle of maximum efficiency is identified at 23.25°. A reduction in the pitch angle leads to a temporary rise in efficiency, which subsequently falls, accompanied by a continuous decrease in the thrust coefficient. The optimal selection angle should consider this to prevent negative thrust at lower advance coefficients, which could further impact overall efficiency. An increased number of blades elevates the thrust coefficient and reduces the force on each blade, yet has a minimal effect on efficiency. Additionally, the orthogonal test method was utilized to explore the interactions between these three parameters. The outcomes indicate that, in terms of final power, there is no significant interaction among the three parameters under investigation. However, notable interactions are observed between the pitch angle and the number of blades, the outward inclination angle and the pitch angle, and the outward inclination angle and the number of blades. Consequently, the study’s findings facilitate the selection of parameter combinations that yield higher efficiency or thrust coefficients.

Work zones present unique risks to both workers and road users due to its complex and dynamic nature. This study developed a two-stage in-vehicle warning system aimed at refining driver behavior when approaching work zones and mitigating lane-changing risks. To accurately capture the thorough behavioral processes of drivers near work zones, a driving simulation experiment was conducted involving 38 participants of diverse genders and occupations. Different warning modes (baseline vs. two-stage warning), speed limits (60 km/h vs. 80 km/h), and visibility conditions (clear vs. fog) were incorporated into the experimental design. The entire behavioral performance was segmented into approaching and lane-changing processes. Generalized Estimating Equation (GEE) models were employed to analyze behavioral changes during the approaching process under different conditions, and Fuzzy C-Means (FCM) clustering algorithm was utilized for risk assessments. Influencing analysis was then applied to examine the relationship between behavioral changes during the approaching process and lane-changing risk levels. The findings reveal that, compared to the baseline group, the two-stage warning effectively reduced the average approaching speed by 2.25 %, increased the headway distance by 19.02 %, and advanced the starting point of lane-changing maneuvers by approximately 42.8 m on average, all of which contributed to a decrease in overall lane-changing risks. Under high speed limits, despite all drivers adhering to the speed limit, the phenomenon of relatively higher deceleration still persists, leading to unsafe and uncomfortable conditions.Additionally, the risk faced by drivers is significantly heightened when traveling at higher speeds in dense fog, further corroborating the necessity of the two-stage warning. The findings provide a theoretical foundation for the development of in-vehicle warning systems for work zone areas, offering practical implications for safe and efficient operations within work zones.

Lane changing poses a great threat to traffic safety in the work zone areas. This study aims to conduct an in-depth investigation of drivers' lane-changing behavior and to propose and verify the efficacy of an intelligent in-vehicle audio prompt through a driving simulator experiment. Forty-two participants, comprising 22 males (12 professional drivers and 10 normal drivers) and 20 females (10 professional drivers and 10 normal drivers), took part in the study. Three traffic density levels (20pcu/km, 40pcu/km, and 60pcu/km) and five locations (baseline, 250m, 500m, 750m, and 1000m) to release the audio prompt information were set to collect eye movement and driving behavior data. A multistage lane-changing process including the perception stage, preparation stage, and action stage was developed, and three types of variables, namely experiment variable, behavioral variable, and risk assessment variable, were defined. The results indicated that the audio prompt set at 500m, 750m, and 1000m could noticeably improve lane-changing behavior (i.e., triggering lane changes more in advance and providing drivers with more preparation time). However, the audio prompt set at 250m upstream of the work zone showed limited efficacy, which is not recommended in practical application. Male drivers and professional drivers performed better during lane changing, and they had a more active observation of the surrounding environment and tended to adopt safer vehicle operations than their counterparts. A high traffic density could increase the collision risks even if drivers had made sufficient preparations, while in low traffic density conditions, drivers who failed to change lanes tended to apply hard braking when they approached the work zone.