To reduce the false detection rate of vehicle targets caused by occlusion, an improved method of vehicle detection in different traffic scenarios based on an improved YOLO v5 network is proposed. The proposed method uses the Flip-Mosaic algorithm to enhance the network’s perception of small targets. A multi-type vehicle target dataset collected in different scenarios was set up. The detection model was trained based on the dataset. The experimental results showed that the Flip-Mosaic data enhancement algorithm can improve the accuracy of vehicle detection and reduce the false detection rate.

Fatigue cracking in an asphalt mixture is a process whereby microcracks in the asphalt–aggregate interface propagate into extensive interconnected cracks under repeated loads. The fatigue performance of asphalt is influenced by the load as well as the intrinsic nature of the asphalt–aggregate system. This study used the surface energy concept of asphalt and aggregate systems to characterize the fatigue behavior of asphalt mixtures. The surface energy of asphalt and aggregate at different temperatures were measured using Wilhelmy plate method and contact angle meter, respectively. By using dissipated pseudostrain energy of nonlinear viscoelastic material and micromechanics cracking model, the effect of surface energy on fatigue life of the asphalt mixtures was analyzed. Laboratory test indicated that the surface energy of the asphalt generally decreased with an increase of temperature. Compared with AH70 grade asphalt, the surface energy of styrene-butadiene-styrene block copolymer (SBS)-modified a...

Road lane markings play an essential role in maintaining traffic order and improving traffic safety and efficiency. Active luminous lane markings have emerged with advances in technology recently. However, it is still not completely clear what impact their application will have on drivers. This paper aimed to study the effectiveness of active luminous lane markings on highways at night. A driving simulation experiment was carried out based on advanced driving simulators at Tongji University. The driving simulation experiment involved 31 participants and 9 simulation scenes with 6 different types of lane markings models and the same 2-way highway segment, which was 5300-m long with four 3.75-m wide driving lanes. The study participants drove through the simulated highway while the vehicle operation data and the driver’s eyes changing data were continuously captured. Overall, the pupil area change rate, steering wheel speed, brake pedal force, gas pedal, lane departure, and operating speed indicators were selected to evaluate the effectiveness of the active luminous lane markings. The results are shown as follows: (1) the active luminous lane markings have excellent visual recognition performance at night. Compared with the passive luminous lane markings, the active luminous markings can reduce the mental and physical loads of drivers, increase the early braking distance significantly, improve the lane-keeping ability and smooth the operating speed; (2) for the specific parameter settings of the active luminous lane markings at night, the yellow lane markings are better than the white ones, the point-line-type lane markings are superior to the conventional-type ones, and the blinking frequency is reasonable to set, at a moderate level, as 40 times per min. The results suggest that there are positive effects of active luminous lane markings on the promotion of highway traffic safety and efficiency at night, providing theoretical support for the popularization and application of active luminous road lane markings.

Driving simulation is an efficient, safe, and data-collection-friendly method to examine driving behavior in a controlled environment. However, the validity of a driving simulator is inconsistent when the type of the driving simulator or the driving scenario is different. The purpose of this research is to verify driving simulator validity in driving behavior research in work zones. A field experiment and a corresponding simulation experiment were conducted to collect behavioral data. Indicators such as speed, car-following distance, and reaction delay time were chosen to examine the absolute and relative validity of the driving simulator. In particular, a survival analysis method was proposed in this research to examine the validity of reaction delay time. The result indicates the following: (1) most indicators are valid in driving behavior research in the work zone. For example, spot speed, car-following distance, headway, and reaction delay time show absolute validity. (2) Standard deviation of the car-following distance shows relative validity. Consistent with previous researches, some driving behaviors appear to be more aggressive in the simulation environment.

The cross-sectional width of highways is a major factor that affects the construction cost of engineering projects. With the increasing demand for intensive highway construction, research on dedicated lanes or roadway for car has attracted research attention. The lateral oscillation value of vehicle’s trajectory is the direct factor that affects lane width; however, relevant research is relatively limited, and the characteristics are not yet clear. Therefore, this study utilized an integrated radar–video system to collect real high-precision trajectory data, obtaining 24,697 datasets. Statistical methods were used to reveal the lateral oscillation value and determine the effective lane width of car for safe driving. The research results are as follows: 1. The lateral oscillation value of car present differences on different lanes. Vehicles on the inner two lanes tend to drift leftward, whereas those on the outermost lane drift rightward. 2. When operating speed ranges from 80 km/h to 110 km/h, the lateral oscillation value presents a statistical rule, which obeys a normal distribution for the left and right margins, namely, D_left ∼ N(0.87, 0.15) and D_right ∼ N(0.72, 0.15). This lateral oscillation value is insensitive to fluctuations in operating speed (80km/h∼110km/h) from the standpoint of field data. 3. The fitted expressions of effective lane width for car was proposed and the effective lane width of car at the 95^th, 90^th, and 85^th percentile is 3.2m, 3.0m, and 2.8 m, respectively. These results can provide technical support for dedicated lane width of car and have practical significance for the intensive construction of road infrastructure in highly urbanized areas.