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Journal ArticleDOI

Longitudinal and Lateral Control for Automated Yielding Maneuvers

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TLDR
Simulation results demonstrate the ability of the proposed trajectory planning algorithm to generate smooth collision-free maneuvers which are appropriate for various traffic situations.
Abstract
Automated driving is predicted to enhance traffic safety, transport efficiency, and driver comfort. To extend the capability of current advanced driver assistance systems, and eventually realize fully automated driving, the intelligent vehicle system must have the ability to plan different maneuvers while adapting to the surrounding traffic environment. This paper presents an algorithm for longitudinal and lateral trajectory planning for automated driving maneuvers where the vehicle does not have right of way, i.e., yielding maneuvers. Such maneuvers include, e.g., lane change, roundabout entry, and intersection crossing. In the proposed approach, the traffic environment which the vehicle must traverse is incorporated as constraints on its longitudinal and lateral positions. The trajectory planning problem can thereby be formulated as two loosely coupled low-complexity model predictive control problems for longitudinal and lateral motion. Simulation results demonstrate the ability of the proposed trajectory planning algorithm to generate smooth collision-free maneuvers which are appropriate for various traffic situations.

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Citations
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Journal ArticleDOI

Lane Change Maneuvers for Automated Vehicles

TL;DR: The real-time ability of the lane change maneuver algorithm to generate safe and smooth trajectories is shown by experimental results of a Volvo V60 performing automated lane change maneuvers on a test track.
Journal ArticleDOI

A Novel Local Motion Planning Framework for Autonomous Vehicles Based on Resistance Network and Model Predictive Control

TL;DR: The results show that the proposed method performs very well in the planning and tracking process and takes less than $\text{25 ms}$ for the whole planning process, which can be easily implemented in real-world applications.
Journal ArticleDOI

Automated vehicle-involved traffic flow studies: A survey of assumptions, models, speculations, and perspectives

TL;DR: This survey systematically and comprehensively reviews the existing AV-involved traffic flow models with different levels of details, and examines the relationship among the design of AV-based driving strategies, the management of transportation systems, and the resulting traffic dynamics.
Journal ArticleDOI

Dynamic Modeling and Control of High-Speed Automated Vehicles for Lane Change Maneuver

TL;DR: The dynamic modeling and control of high-speed automated vehicles for lane change maneuver is presented, using a nonlinear single-track vehicle dynamics model and a multisegment lane change process model to ensure longitudinal safety of this maneuver.
Journal ArticleDOI

Hybrid Trajectory Planning for Autonomous Driving in On-Road Dynamic Scenarios

TL;DR: A hybrid trajectory planning scheme to integrate the strength of the sampling and optimization methods to generate a reactive trajectory in a dynamically changing environment is proposed.
References
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Journal ArticleDOI

Sampling-based algorithms for optimal motion planning

TL;DR: In this paper, the authors studied the asymptotic behavior of the cost of the solution returned by stochastic sampling-based path planning algorithms as the number of samples increases.
Book

World Report on Road Traffic Injury Prevention

TL;DR: This paper is a synopsis of a major report by the WHO which collates information on crashes worldwide and summarises the key findings and the recommendations of the report.
Posted Content

Sampling-based Algorithms for Optimal Motion Planning

TL;DR: The main contribution of the paper is the introduction of new algorithms, namely, PRM and RRT*, which are provably asymptotically optimal, i.e. such that the cost of the returned solution converges almost surely to the optimum.
Journal Article

World Report on Road Traffic Injury Prevention.

M Cameron
- 01 Aug 2004 - 
TL;DR: Peden et al. as mentioned in this paper presented a comprehensive catalogue of road safety, the impact of road trauma across the world, the key factors contributing to crashes and consequential injuries, successful interventions which have been applied (mainly in high income countries) to reduce the problem, with the final chapter containing conclusions and recommendations.
Journal ArticleDOI

CVXGEN: a code generator for embedded convex optimization

TL;DR: This paper describes how CVXGEN is implemented, and gives some results on the speed and reliability of the automatically generated solvers.
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