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Road traffic accidents resulting from alcohol-impaired driving are increasing globally despite several measures, currently in place, to curb the trend. For this reason, recent research aims at integrating alcohol early-detection systems and driving simulator experiments to identify intoxicated drivers. However, driving simulator experiments on drunk driving have focused mostly on male participants than female drivers whose characteristics have scarcely been explored. Hence in this paper, vehicle dynamic control inputs on steering, braking, and acceleration performance of 75 licensed female drivers with an upshot of alcohol at four different blood alcohol concentration (BAC) levels (0%, 0.03%, 0.05%, and 0.08%) were investigated. The participants completed simulated driving in a fixed-based simulator experiment coupled with real-time ecological scenarios to extract discrete responses.

To prevent braking recession, heavy commercial vehicles are often equipped with fluid auxiliary braking devices, such as hydraulic retarder. Hydraulic retarder can convert the vehicle’s kinetic energy to the fluid heat energy, which can enormously alleviate the main brake’s workload. The traditional hydraulic retarder can provide enough braking torque but has a delay during the braking. In this paper, a new type of magnetorheological fluid (MR fluid) hydraulic retarder is introduced by replacing the traditional fluid with magnetorheological fluid because of its linear braking torque and quick response. By changing the magnetic field intensity, it is easier to control the braking torque than the traditional hydraulic retarder. The rise of magnetorheological fluid temperature during the braking period will reduce the hydraulic retarder’s performance.

With the increase of car ownership and the complex and crowded parking environment, it is difficult for drivers to complete the parking operation quickly and accurately, which may cause traffic accidents such as vehicle collisions and road jams because of poor parking skills. The emergence of an automatic parking system can help drivers park safely and reduce the occurrence of safety accidents. In this paper, the neural network identifier on the control method of an adaptive integral derivative of a neural network is proposed for an automatic parallel parking system with front-wheel steering is studied by using MATLAB/Simulink environment, and the simulation is carried out. Firstly, according to vehicle parameters and obstacle avoidance constraints, the minimum parking space, and parking starting position are calculated. Meanwhile, the path planning of parallel parking spaces is carried out by quintic polynomial.