Browse Topic: Reaction and response times

Items (420)
Abstract Test cycle simulation is an essential part of the vehicle-in-the-loop test, and the deep reinforcement learning algorithm model is able to accurately control the drastic change of speed during the simulated vehicle driving process. In order to conduct a simulated cycle test of the vehicle, a vehicle model including driver, battery, motor, transmission system, and vehicle dynamics is established in MATLAB/Simulink. Additionally, a bench load simulation system based on the speed-tracking algorithm of the forward model is established. Taking the driver model action as input and the vehicle gas/brake pedal opening as the action space, the deep deterministic policy gradient (DDPG) algorithm is used to update the entire model. This process yields the dynamic response of the output end of the bench model, ultimately producing the optimal intelligent driver model to simulate the vehicle’s completion of the World Light Vehicle Test Cycle (WLTC) on the bench. The results indicate that
Gong, XiaohaoLi, XuHu, XiongLi, Wenli
This SAE Information Report provides definitions and discussions of key terms concerning driver drowsiness and fatigue, and basic information on measuring drowsiness and fatigue. It also includes information and concepts for driver drowsiness as they relate to the safe operation of a vehicle. The key driver drowsiness and fatigue causal factors include the following: (1) sleep quality and quantity, (2) time of day, (3) time awake, (4) time on task (modulated by characteristics of the driving task), (5) task-related fatigue (variations of arousal levels related to task underload and overload), and (6) combinations of these factors. Medical conditions, medication, alcohol, or drugs exacerbate drowsiness; however, the discussion in this report is limited to fatigue concepts. This report has two primary outputs: (1) definitions and discussions of key terms concerning driver drowsiness and fatigue, and (2) basic information on measuring drowsiness and fatigue and its effects on the safe
Driver Metrics, Performance, Behaviors and States Committee
The response time of the air braking system is the main parameter affecting the longitudinal braking distance of vehicles. In this article, in order to predict and control the response time of the braking system of semitrailers, an AMESim model of the semitrailer braking system involving the relay emergency valve (REV) and chambers was established on the basis of analyzing systematically the working characteristics of the braking system in different braking stages: feedback braking, relay braking, and emergency braking. A semitrailer braking test bench including the brake test circuit and data acquisition system was built to verify the model with typical maneuver. For further evaluating the semitrailer braking response time, an experiment under different control pressures was carried out. Experimental results revealed the necessity of controlling the response time. As a result, a braking pressure compensation system was designed through adding intake and exhaust solenoid valves to the
He, RenXu, Chang
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