Impact of Age on Takeover Behavior in Automated Driving in Complex Traffic Situations: A Case Study of Beijing, China

Research on the influence of age on various automated driving conditions will contribute to an understanding of driving behavior characteristics and the development of specific automated driving systems. This study aims to analyze the relationship between age and takeover behavior in automated driving, where 16 test conditions were taken into consideration, including two driving tasks, two warning times and four driving scenarios. Forty-two drivers in Beijing, China in 2020 were recruited to participate in a static driving simulator with Level 3 (L3) conditional automation to obtain detailed test information of the recorded takeover time, mean speed and mean lateral offset. An ANOVA test was proposed to examine the significance among different age groups and conditions. The results confirmed that reaction time increased significantly with age and the driving stability of the older group was worse than the young and middle groups. It was also indicated that the older group could not adapt to complex tasks well when driving due to their limited cognitive driving ability. Additionally, the higher urgency of a scenario explained the variance in the takeover quality. According to the obtained influencing mechanisms, policy implications for the development of vehicle automation, considering the various driving behaviors of drivers, were put forward, so as to correctly identify the high-risk driving conditions in different age groups. For further research, on-road validation will be necessary in order to check for driving simulation-related effects.

EXAMPLE OF APPLICATION OF THE PONTRYAGIN’S MINIMUM PRINCIPLE “PMP EXTENSION”: ZERMELO PROBLEM (WITH CURRENT SPEED MORE THAN BOAT SPEED HYPOTHESIS)

We present an example of application covering several cases using the extension of the Pontryaguine minimum principle (PMP) in the case where we add a constraint on reaching a target variety at the final time: the Zermelo problem with current speed more than Boat speed hypothesis, where we consider a boat crossing a channel under a strong current and where we try to reach the opposite bank by minimizing the lateral offset or by minimizing the crossing time.

Geologic framework of Mount Diablo, California

ABSTRACT The basic stratigraphic and structural framework of Mount Diablo is described using a revised geologic map, gravity data, and aeromagnetic data. The mountain is made up of two distinct stratigraphic assemblages representing different depocenters that were juxtaposed by ~20 km of late Pliocene and Quaternary right-lateral offset on the Greenville-Diablo-Concord fault. Both assemblages are composed of Cretaceous and Cenozoic strata overlying a compound basement made up of the Franciscan and Great Valley complexes. The rocks are folded and faulted by late Neogene and Quaternary compressional structures related to both regional plate-boundary–normal compression and a restraining step in the strike-slip fault system. The core of the mountain is made up of uplifted basement rocks. Late Neogene and Quaternary deformation is overprinted on Paleogene extensional deformation that is evidenced at Mount Diablo by significant attenuation in the basement rocks and by an uptilted stepped graben structure on the northeast flank. Retrodeformation of the northeast flank suggests that late Early to early Late Cretaceous strata may have been deposited against and across a steeply west-dipping basement escarpment. The location of the mountain today was a depocenter through the Late Cretaceous and Paleogene and received shallow-marine deposits periodically into the late Miocene. Uplift of the mountain itself happened mostly in the Quaternary.

Data fusion based lane departure warning framework using fuzzy logic

Background: Lane detection is a difficult issue because of different lane circumstances. It plays an important part in advanced driver assistance systems, which give information about the centre of a host vehicle such as lane structure and lane position. Lane departure warning (LDW) is used to warn the driver about an unplanned lane exit from the original lane. The objective of this study was to develop a data-fusion LDW framework to improve the rate of detection of lane departure during daylight and at night. Methods: Vision-based LDW is a comprehensive framework based on vision-based lane detection with additional lateral offset ratio computations based on the detected X12 and X22 coordinates. The computed lateral offset ratio is used to detect lane departure based on predefined LDW identification criteria for vision-based LDW. Data fusion-based LDW was developed using a multi-input-single-output fuzzy logic controller. Data fusion involved lateral offset ratio and yaw acceleration response from the vision-based LDW and model-based vehicle dynamics frameworks. Real-life datasets were generated for simulation under the MATLAB Simulink platform. Results: Experimental results showed that fusion-based LDW achieved an average lane departure detection rate of 99.96% and 98.95% with false positive rates (FPR) of 0.04% and 1.05% using road footage clips #5–#27 in daytime and night-time, respectively. The average FPR using data fusion-based LDW reduced by 18.83% and 15.22% compared to vision-based LDW in daytime and night-time, respectively. Conclusions: The data fusion-based LDW is a novel way of reducing false lane departure detection by fusing two types of modalities to determine the correct lane departure information. The limitation is the constant warning threshold value used in the current implementation of LDW in the vision-based LDW framework. An adaptive mechanism of warning threshold taking various road structures into account could be developed to improve lane departure detection.

Nonlinear Differential Braking Control for Collision Avoidance During Lane Change

In this paper, a nonlinear differential braking control method is developed to avoid collision during lane change under driver torque. The lateral dynamics consist of lateral offset error and yaw error dynamics and can be interpreted as a semi-strict feedback form. In the differential braking control problem under the driver torque, a matching condition does not satisfy, and the system is not in the form of, the strict feedback form. Thus, a general backstepping control method cannot be applied. To overcome this problem, the proposed method is designed via the combination of the sliding mode control and backstepping. Two sliding surfaces are designed for differential braking control. One of the surfaces is designed considering the lateral offset error, and the other sliding surface is designed using the combination of the yaw and yaw rate errors as the virtual input of the lateral offset error dynamics. A brake steer force input is developed to regulate the two sliding surfaces using a backstepping procedure under the driver torque. Integral action and a super twisting algorithm are used in the lateral controller to ensure the robustness of the system. The proposed method, which is designed via the combination of the sliding mode control and backstepping, can improve the lateral control performance using differential braking. The proposed method is validated through simulations.

CFD analysis and RSM optimization of obstacle layout in Tesla micromixer

As a kind of fast and efficient mixing equipment, micromixer has been applied to chemical reaction detection. Its application can not only save experimental samples but also reduce the experimental time. In micromixers, Tesla structure is widely used due to its simple structure and special flow mechanism. In this paper, CFD and response surface method are used to analyze and verify the flow field of the configuration of adding diamond obstacles in the Tesla mixer. The results show that the order of layout parameter weight from large to small is obstacle size > vertical offset > horizontal offset. And the Desirability was 0.806, the optimal diamond obstacle size is 46.35 μm and the optimal lateral offset is 18.78 μm. In addition, a constant value OF 20 μm is predicted as the optimal vertical offset of the micromixer. Compared with the Tesla-type micromixer without obstacles, the diamond-shaped barrier Tesla-type micromixer designed in this paper has higher mixing rate and lower pressure drop under the same conditions, which can be applied to chemical reactors, and can also help to improve the accuracy of chemical reaction. It can be demonstrated that the presented optimal design method of obstacles layout in Tesla mixer is a simple and effective technology to improve the liquid mixing in microfluidic devices, and it has a broad application prospect in chemical engineering.