Adaptive and efficient lane change path planning for automated vehicles

Heil, Thomas; Lange, Alexander; Cramer, Stephanie

doi:10.1109/itsc.2016.7795598

Cited by 24 publications

(9 citation statements)

References 6 publications

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“…The past decades have witnessed a great progress in trajectory planning. Many researches have been proposed and studied [3], [9]- [11] that they can generate global trajectories connecting a start and a possibly distant end state. Some approaches for trajectory planning follow a discrete sampling or a road map-based scheme [12] [13], which firstly sample multiple rows of points and then generate a finite set of trajectories with cost values, typically by differential functions that describe vehicle dynamics and kinematics.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Generation Method based on Dynamic Curvature of the Reference Curve for Robust Trajectory Planning

Sun¹,

Ren²,

Lian³

et al. 2020

Preprint

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Trajectory planning is a fundamental task on various autonomous driving platforms, such as social robotics and self-driving cars. Many trajectory planning algorithms use a reference curve based Frenet frame with time to reduce the planning dimension. However, there is a common implicit assumption in classic trajectory planning approaches, which is that the generated trajectory should follow the reference curve continuously. This assumption is not always true in real applications and it might cause some undesired issues in planning. One issue is that the projection of the planned trajectory onto the reference curve maybe discontinuous. Then, some segments on the reference curve are not the image of any part of the planned path. Another issue is that the planned path might self-intersect when following a simple reference curve continuously. The generated trajectories are unnatural and suboptimal ones when these issues happen. In this paper, we firstly demonstrate these issues and then introduce an efficient trajectory generation method which uses a new transformation from the Cartesian frame to Frenet frames. Experimental results on a simulated street scenario demonstrated the effectiveness of the proposed method.

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Section: Related Workmentioning

confidence: 99%

An Efficient Generation Method based on Dynamic Curvature of the Reference Curve for Robust Trajectory Planning

Sun¹,

Ren²,

Lian³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…A completely different approach to solving the path planning problem is multi-agent systems, where the necessary calculations are distributed among different units [14]. Most of the path planning approaches plan several paths, evaluate these and choose the best [5,15], but there are also approaches, which plan only one path and iteratively improve this path [16]. Because path planning can become computationally burdensome, a considerable amount of research was done to parallelize it.…”

Section: Related Workmentioning

confidence: 99%

Path Planning for Highly Automated Driving on Embedded GPUs

Fickenscher

Schmidt

Hannig

et al. 2018

JLPEA

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The sector of autonomous driving gains more and more importance for the car makers. A key enabler of such systems is the planning of the path the vehicle should take, but it can be very computationally burdensome finding a good one. Here, new architectures in ECU are required, such as GPU, because standard processors struggle to provide enough computing power. In this work, we present a novel parallelization of a path planning algorithm. We show how many paths can be reasonably planned under real-time requirements and how they can be rated. As an evaluation platform, an Nvidia Jetson board equipped with a Tegra K1 SoC was used, whose GPU is also employed in the zFAS ECU of the AUDI AG.

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“…A few researches only assumed that the acceleration and velocity at the starting and ending points were zeros to generate the PC-based lateral trajectory model (Resende & Nashashibi, 2010;Wang & Zheng, 2013;You et al, 2015;Ntousakis et al, 2016;Chebly et al, 2017). Heil et al (2016) developed the PC-based LCT planning and found the computational cost by using maximum acceleration and overshooting behaviour. Connors and Elkaim (2007) had successfully overcome collision points during LC.…”

Section: Introductionmentioning

confidence: 99%

A New Parametric Function-Based Dynamic Lane Changing Trajectory Planning and Simulation Model

Rahman¹,

Ismail²,

Awang³

et al. 2021

JST

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Lane-changing (LC) problem may cause serious accidents or create a painful traffic jam at multi-lane roads. Existing LC simulation model was created with some limitations (less fitted, without velocity and acceleration profiles, high curvature) by using well known trajectory curve such as Hyperbolic Tangent Curve (HTC), Sine-Based Curve (SC), Polynomial Curve (PC). In this study, a new parametric curve had been proposed by using curvilinear coordinate system and fitted against Next Generation Simulation (NGSIM) real dataset. Further, new profiles of velocity and acceleration were designed using the proposed LC trajectory curve. The curvature of proposed model was zero-based curvature both at LC starting and ending points. This proposed curvature was compared with two models such as HTC and SC. The average root-mean-square-error of proposed model decreased with 1.84% for left LC and 15.48% for right LC compared to HTC model and 1.74% for left LC and 15.60% for right LC compared to SC model. Similarly, the proposed model for velocity and acceleration profiles improved significantly from PC model. The proposed parametric curve solves the gap and collision points of LC vehicle with a front vehicle and rear vehicle at target lane and can be used in real LC path planning.

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Adaptive and efficient lane change path planning for automated vehicles

Cited by 24 publications

References 6 publications

An Efficient Generation Method based on Dynamic Curvature of the Reference Curve for Robust Trajectory Planning

An Efficient Generation Method based on Dynamic Curvature of the Reference Curve for Robust Trajectory Planning

Path Planning for Highly Automated Driving on Embedded GPUs

A New Parametric Function-Based Dynamic Lane Changing Trajectory Planning and Simulation Model

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