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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 velocity.
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Related In: Results  -  Collection


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fig10: The vehicle velocity.

Mentions: As shown in Figure 9, the actual braking deceleration is nearly accordant with the desired braking deceleration, and the actual braking deceleration reaches the maximum braking deceleration −6.6 m/s2 at 0.25 s. At that time, the passengers would feel uncomfortable to some extent. Some little fluctuations can be observed between 2 s and 5 s. The actual braking deceleration reaches zero at 22 s. From Figure 10, it can be known that the velocity drops rapidly within the first five seconds and reduces to 9 km/h at the time of 5 s. At the time of 15 s the velocity is already reduced to 1.2 km/h and finally reaches the desired value of zero at 22 s. Figure 11 shows that the relative distance of the vehicle and the target pedestrian is 50 m at the initial time and quickly reduces to 16.5 m within the first five seconds. Finally, the relative distance reaches the desired distance at the time of 22 s when the host vehicle stops completely.


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 velocity.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig10: The vehicle velocity.
Mentions: As shown in Figure 9, the actual braking deceleration is nearly accordant with the desired braking deceleration, and the actual braking deceleration reaches the maximum braking deceleration −6.6 m/s2 at 0.25 s. At that time, the passengers would feel uncomfortable to some extent. Some little fluctuations can be observed between 2 s and 5 s. The actual braking deceleration reaches zero at 22 s. From Figure 10, it can be known that the velocity drops rapidly within the first five seconds and reduces to 9 km/h at the time of 5 s. At the time of 15 s the velocity is already reduced to 1.2 km/h and finally reaches the desired value of zero at 22 s. Figure 11 shows that the relative distance of the vehicle and the target pedestrian is 50 m at the initial time and quickly reduces to 16.5 m within the first five seconds. Finally, the relative distance reaches the desired distance at the time of 22 s when the host vehicle stops completely.

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