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Advanced emergency braking controller design for pedestrian protection oriented automotive collision avoidance system.

Lie G, Zejian R, Pingshu G, Jing C - ScientificWorldJournal (2014)

Bottom Line: Three typical braking scenarios are defined and the safety situations are assessed by comparing the current distance between the host vehicle and the obstacle with the critical braking distance.To reflect the nonlinear time-varying characteristics and control effect of the longitudinal dynamics, the vehicle longitudinal dynamics model is established in CarSim.Cosimulations utilizing CarSim and Simulink are finally carried out on a CarSim intelligent vehicle model to explore the effectiveness of the proposed controller.

View Article: PubMed Central - PubMed

Affiliation: School of Automotive Engineering, Dalian University of Technology, Dalian 116024, China.

ABSTRACT
Automotive collision avoidance system, which aims to enhance the active safety of the vehicle, has become a hot research topic in recent years. However, most of the current systems ignore the active protection of pedestrian and other vulnerable groups in the transportation system. An advanced emergency braking control system is studied by taking into account the pedestrians and the vehicles. Three typical braking scenarios are defined and the safety situations are assessed by comparing the current distance between the host vehicle and the obstacle with the critical braking distance. To reflect the nonlinear time-varying characteristics and control effect of the longitudinal dynamics, the vehicle longitudinal dynamics model is established in CarSim. Then the braking controller with the structure of upper and lower layers is designed based on sliding mode control and the single neuron PID control when confronting deceleration or emergency braking conditions. Cosimulations utilizing CarSim and Simulink are finally carried out on a CarSim intelligent vehicle model to explore the effectiveness of the proposed controller. Results display that the designed controller has a good response in preventing colliding with the front vehicle or pedestrian.

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Related in: MedlinePlus

The vehicle deceleration.
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fig6: The vehicle deceleration.

Mentions: In this situation, the host vehicle is running at a constant velocity of 40 km/h. The leading vehicle is running at a constant velocity of 40 km/h and conducts the maximum intensity of emergency braking during the time range of 12 s and 12.3 s. The leading vehicle is detected when it is 23 m ahead of the host vehicle. When the real-time distance d between the host vehicle and the leading vehicle appears to be smaller than the critical braking distance dw1, which is introduced in Section 2.1(a), the automatic deceleration control starts to be implemented immediately. During the simulation, the initial position of the leading vehicle is set to 23 m away from original point and the initial velocity is set to 40 km/h and the brake pressure steps from 0 Mpa to 15 Mpa. The host vehicle starts to move from the original point with a constant velocity of 40 km/h. The performance of the designed neuron PID sliding model controller is compared with the standard PID sliding mode controller. The simulation duration is set to 40 s to observe the changes of velocity, acceleration, and relative distance. The simulation results are shown in Figures 6–8.


Advanced emergency braking controller design for pedestrian protection oriented automotive collision avoidance system.

Lie G, Zejian R, Pingshu G, Jing C - ScientificWorldJournal (2014)

The vehicle deceleration.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4109130&req=5

fig6: The vehicle deceleration.
Mentions: In this situation, the host vehicle is running at a constant velocity of 40 km/h. The leading vehicle is running at a constant velocity of 40 km/h and conducts the maximum intensity of emergency braking during the time range of 12 s and 12.3 s. The leading vehicle is detected when it is 23 m ahead of the host vehicle. When the real-time distance d between the host vehicle and the leading vehicle appears to be smaller than the critical braking distance dw1, which is introduced in Section 2.1(a), the automatic deceleration control starts to be implemented immediately. During the simulation, the initial position of the leading vehicle is set to 23 m away from original point and the initial velocity is set to 40 km/h and the brake pressure steps from 0 Mpa to 15 Mpa. The host vehicle starts to move from the original point with a constant velocity of 40 km/h. The performance of the designed neuron PID sliding model controller is compared with the standard PID sliding mode controller. The simulation duration is set to 40 s to observe the changes of velocity, acceleration, and relative distance. The simulation results are shown in Figures 6–8.

Bottom Line: Three typical braking scenarios are defined and the safety situations are assessed by comparing the current distance between the host vehicle and the obstacle with the critical braking distance.To reflect the nonlinear time-varying characteristics and control effect of the longitudinal dynamics, the vehicle longitudinal dynamics model is established in CarSim.Cosimulations utilizing CarSim and Simulink are finally carried out on a CarSim intelligent vehicle model to explore the effectiveness of the proposed controller.

View Article: PubMed Central - PubMed

Affiliation: School of Automotive Engineering, Dalian University of Technology, Dalian 116024, China.

ABSTRACT
Automotive collision avoidance system, which aims to enhance the active safety of the vehicle, has become a hot research topic in recent years. However, most of the current systems ignore the active protection of pedestrian and other vulnerable groups in the transportation system. An advanced emergency braking control system is studied by taking into account the pedestrians and the vehicles. Three typical braking scenarios are defined and the safety situations are assessed by comparing the current distance between the host vehicle and the obstacle with the critical braking distance. To reflect the nonlinear time-varying characteristics and control effect of the longitudinal dynamics, the vehicle longitudinal dynamics model is established in CarSim. Then the braking controller with the structure of upper and lower layers is designed based on sliding mode control and the single neuron PID control when confronting deceleration or emergency braking conditions. Cosimulations utilizing CarSim and Simulink are finally carried out on a CarSim intelligent vehicle model to explore the effectiveness of the proposed controller. Results display that the designed controller has a good response in preventing colliding with the front vehicle or pedestrian.

Show MeSH
Related in: MedlinePlus