Piecewise Trajectory Replanner for Highway Collision Avoidance Systems with Safe-Distance Based Threat Assessment Strategy and Nonlinear Model Predictive Control

Hamid, Umar Zakir Abdul; Ariff, Mohd Shoki Md; Zamzuri, Hairi; Saito, Yuichi; Zakaria, Muhammad Aizzat; Rahman, Mohd Azizi Abdul; Raksincharoensak, Pongsathorn

doi:10.1007/s10846-017-0665-8

Cited by 22 publications

(11 citation statements)

References 47 publications

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“…Secondary collision mitigation strategies can be found in 11,13 . Common strategies employed for MVCCA include Platooning 60 , Active Brake Control 61 , Time-Critical Cooperative Control 37 , Trajectory Re-planning 62 . Authors in 62 proposed avoidance technique for chain crash as shown in Fig.…”

Section: Chain Collision or Mvcs Descriptionmentioning

confidence: 99%

Multiple vehicle cooperation and collision avoidance in automated vehicles: survey and an AI-enabled conceptual framework

Muzahid

Kamarulzaman

Rahman

et al. 2023

Sci Rep

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Prospective customers are becoming more concerned about safety and comfort as the automobile industry swings toward automated vehicles (AVs). A comprehensive evaluation of recent AVs collision data indicates that modern automated driving systems are prone to rear-end collisions, usually leading to multiple-vehicle collisions. Moreover, most investigations into severe traffic conditions are confined to single-vehicle collisions. This work reviewed diverse techniques of existing literature to provide planning procedures for multiple vehicle cooperation and collision avoidance (MVCCA) strategies in AVs while also considering their performance and social impact viewpoints. Firstly, we investigate and tabulate the existing MVCCA techniques associated with single-vehicle collision avoidance perspectives. Then, current achievements are extensively evaluated, challenges and flows are identified, and remedies are intelligently formed to exploit a taxonomy. This paper also aims to give readers an AI-enabled conceptual framework and a decision-making model with a concrete structure of the training network settings to bridge the gaps between current investigations. These findings are intended to shed insight into the benefits of the greater efficiency of AVs set-up for academics and policymakers. Lastly, the open research issues discussed in this survey will pave the way for the actual implementation of driverless automated traffic systems.

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Section: Chain Collision or Mvcs Descriptionmentioning

confidence: 99%

Multiple vehicle cooperation and collision avoidance in automated vehicles: survey and an AI-enabled conceptual framework

Muzahid

Kamarulzaman

Rahman

et al. 2023

Sci Rep

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“…To address these difficulties, researchers in the field of vehicle active safety conducted research, which led to the creation of Advanced Driver Assistance Systems (ADAS). Collision avoidance (Hamid et al, 2017), blindspot monitoring, and automated emergency braking (AEB) (Fildes et al, 2015) applications. AEB is an ADAS feature that works autonomously, without the need for human interaction, to lessen the chance of a collision in dangerous situations by applying braking torque.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Braking System: for Automobile Use

Rahman

Ihsan

2021

MIST International Journal of Science and Technology

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Road fatality and injury are a worldwide issue in the transportation industry. Road traffic accidents are becoming increasingly significant due to higher mortality, injury, and disability across the world, particularly in developing and transitional economies. Eighty-five percent of the total road traffic fatalities occur in developing nations, with Asia-Pacific accounting for roughly half of them. A variety of factors influence road safety, including technological, physical, social, and cultural factors. The purpose of this research was to design an autonomous braking system (AuBS). Using the Adaptive Neuro-Fuzzy Intelligent System (ANFIS), a DC motor, sensors, and SAuBS have been developed to customize the traditional hydraulic braking system. The genetic algorithm has been developed to simulate the fundamental characteristics of the automotive braking system. The AuBS system goal is to slow the car without the driver's help infrequent braking when the vehicle is moving at slower speeds. When the ANFIS performance is compared to that of the AuBS model, it is discovered that the ANFIS performs roughly 15% better.

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“…In terms of the depiction of obstacle, Hu et al 18 presented a real-time dynamic path planning method for autonomous driving that avoids both static and moving obstacles and the obstacles were defined as plane circles. Hamid et al 19 designed a piecewise-kinematic-based trajectory replanning strategy for collision avoidance (CA), considering the physical dimension of the obstacle by providing an invisible rectangular safe region around the obstacle. The foregoing paper assumed the obstacle is in front of the host vehicle, which has side-collision risk when the obstacle orientation is inconsistent with the host vehicle.…”

Section: Introductionmentioning

confidence: 99%

Dynamic path planning and path following control for autonomous vehicle based on the piecewise affine tire model

Chen

Yan

Wang

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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This paper proposes a novel dynamic path planning and path following control method for collision avoidance, which works based on an improved piecewise affine tire model. The main contribution of this work is the design of a dynamic path planning method based on model predictive control, where it replans a maneuverable path to avoid moving obstacle in real time. A hierarchical control framework contains a high-level path replanning model predictive control and a low-level path following model predictive control. A collision avoidance cost function in the high hierarchies was designed to calculate the relative dynamic distance, which copes with the sudden obstacle. Moreover, the replanning path is the optimized output according to reference trajectory, obstacle, and handling stability. The control objective of the low hierarchies is to accurately track the replanning path, especially for the increased nonlinearity of large tire sideslip angle. For this reason, an improved piecewise affine tire model is designed and used for model predictive control to improve the path following performance and reduce calculated burden. The main improvement of the piecewise affine tire model is that the varied lateral stiffness coefficients adapt to the change of the tire sideslip angle in different tire regions. Based on the CarSim and Simulink platform, the dynamic path planning and path following simulations are designed to test the proposed method. The simulation results demonstrate the effectiveness of the proposed method.

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Piecewise Trajectory Replanner for Highway Collision Avoidance Systems with Safe-Distance Based Threat Assessment Strategy and Nonlinear Model Predictive Control

Cited by 22 publications

References 47 publications

Multiple vehicle cooperation and collision avoidance in automated vehicles: survey and an AI-enabled conceptual framework

Multiple vehicle cooperation and collision avoidance in automated vehicles: survey and an AI-enabled conceptual framework

Autonomous Braking System: for Automobile Use

Dynamic path planning and path following control for autonomous vehicle based on the piecewise affine tire model

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