Motion Planning Solution with Constraints Based on Minimum Distance Model for Lane Change Problem of Autonomous Vehicles

Tho, Quach Hai; Pháp, Huỳnh Công; Phuong, Pham Anh

doi:10.18280/mmep.090131

Cited by 4 publications

(5 citation statements)

References 21 publications

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“…Relationship between coordinate systems also a direct basis for control the operation of autonomous vehicles [26].…”

Section: Building the Lane-change Trajectory Equationmentioning

confidence: 99%

“…To complete the motion‐planning problem, the vehicle must move in accordance with the defined trajectory. In other words, trajectory is the basic element to describe the operation of autonomous vehicles, and the design of motion trajectory will provide input data for the control system; it is also a direct basis for control the operation of autonomous vehicles [26].…”

Section: Building a Mathematics Model For Lane‐change Solutionmentioning

confidence: 99%

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Building a mathematics model for lane‐change technology of autonomous vehicles

2022

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In the process of autonomous vehicle motion planning and to create comfort for vehicle occupants, factors that must be considered are the vehicle's safety features and the road's slipperiness and smoothness. In this paper, we build a mathematical model based on the combination of a genetic algorithm and a neural network to offer lane‐change solutions of autonomous vehicles, focusing on human vehicle control skills. Traditional moving planning methods often use vehicle kinematic and dynamic constraints when creating lane‐change trajectories for autonomous vehicles. When comparing this generated trajectory with a man‐generated moving trajectory, however, there is in fact a significant difference. Therefore, to draw the optimal factors from the actual driver's lane‐change operations, the solution in this paper builds the training data set for the moving planning process with lane change operation by humans with optimal elements. The simulation results are performed in a MATLAB simulation environment to demonstrate that the proposed solution operates effectively with optimal points such as operator maneuvers and improved comfort for passengers as well as creating a smooth and slippery lane‐change trajectory.

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“…Relationship between coordinate systems also a direct basis for control the operation of autonomous vehicles [26].…”

Section: Building the Lane-change Trajectory Equationmentioning

confidence: 99%

Section: Building a Mathematics Model For Lane‐change Solutionmentioning

confidence: 99%

Building a mathematics model for lane‐change technology of autonomous vehicles

2022

Self Cite

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“…The stability of the global tracking error dynamics Eq. ( 27) is equivalent to the stability of the following 𝑁 characteristic equations, 𝜆 3…”

Section: Proof Of the Uniformly Bounded Of 𝑒 𝑖mentioning

confidence: 99%

“…Research on vehicle and transportation technology is progressing rapidly, including electric vehicles [1], autonomous vehicles [2,3], connected vehicles [2], traffic management [4] and the possibility of collaboration between unmanned ground vehicles and unmanned aerial vehicles [5]. As we know that the future of transportation is predicted to be connected and automated which allows information to be exchanged between vehicles, pedestrians and infrastructures in the intelligent transportation system (ITS) scheme.…”

Section: Introductionmentioning

confidence: 99%

Distributed Model Reference Adaptive Control Based on Cooperative Observer with Optimal Control Modification for Synchronization of Heterogeneous Vehicle Platoon

Prayitno¹,

Indrawati²,

Nilkhamhang³

2022

MMEP

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Many distributed controllers for vehicle platoon are designed based on homogeneous assumption and full state information. In reality, vehicle platoon may consist of heterogeneous vehicles and may have limited information due to sensor constraints. Therefore, this paper proposes a distributed model reference adaptive control based on cooperative observer for a heterogeneous vehicle platoon with limited output information and subjected to uncertain dynamics. Cooperative observer provides a full state estimation of the system. Each follower has a reference model that is designed based on its nominal model and cooperative state variable feedback. Main control system is composed of (i) nominal control that utilized the cooperative state estimation tracking error and (ii) adaptive term that adopted an optimal control modification as an adaptation law. The tracking error of followers to the reference model is shown uniformly bounded and the stability of the platoon is guaranteed through detailed analysis. Performance of the proposed controller is verified by using numerical simulation. To show the advantage of the proposed control, simulation results are compared to the standard distributed model reference adaptive control that is applied for heterogeneous vehicle platoon. It is shown that the proposed control eliminated the high frequency oscillation in the control input.

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“…Chen et al [13] developed an artificial intelligence inverse problem solution for traffic collision reconstruction. Tho et al [14] proposed a motion planning method based on minimum distance for lane change of autonomous vehicles.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Modelling of Docking Autonomous PODs in Tandem Configuration

Al-Habahbeh¹,

Al-Adwan²

2022

MMEP

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An adaptable transportation concept is proposed; comprising a fleet of autonomous PODs that can merge and separate based on passengers’ demand. The purpose is to match the number of seats with the number of passengers, thereby reducing vehicle size and energy consumption. It enables passengers’ in-person communication and simultaneous arrival. Since each POD has its own motor, if full power is not needed, one of the motors can be turned-off to save energy. The merging process is investigated so as to find the safe docking speeds when two PODs merge in tandem configuration. If the docking is not done at the right speed, it may cause damage to the vehicle, or else be inefficiently slow. The PODs are represented by finite element models, which are simulated to determine the safe merging speeds. The speeds are determined for different docking scenarios and POD materials; ranging from 1.4-16 km/h. The safe speeds depend on the type of material and adopted damage criterion; Nonmetallic materials showed higher tolerance than metallic materials in response to docking impact. As a recommendation for future work, other materials and configurations can be investigated, and the effect of the proposed system on traffic conditions can be evaluated.

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Motion Planning Solution with Constraints Based on Minimum Distance Model for Lane Change Problem of Autonomous Vehicles

Cited by 4 publications

References 21 publications

Building a mathematics model for lane‐change technology of autonomous vehicles

Building a mathematics model for lane‐change technology of autonomous vehicles

Distributed Model Reference Adaptive Control Based on Cooperative Observer with Optimal Control Modification for Synchronization of Heterogeneous Vehicle Platoon

Dynamic Modelling of Docking Autonomous PODs in Tandem Configuration

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