Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions

Katrakazas, Christos; Quddus, Mohammed; Deka, Lipika

doi:10.1016/j.trc.2015.09.011

Cited by 617 publications

(294 citation statements)

References 98 publications

Supporting

Mentioning

283

Contrasting

Unclassified

Order By: Relevance

“…Autonomous vehicles (AVs), as one of the most promising topics in both academia and industry in recent decades, are expected to change the future of the world in various ways [1]. AVs can benefit the next generation of transportation systems due to their safety, mobility, and efficiency advantages [2].…”

Section: Introductionmentioning

confidence: 99%

“…AVs can benefit the next generation of transportation systems due to their safety, mobility, and efficiency advantages [2]. Moreover, AVs are effective test platforms for various advanced technologies, such as artificial intelligence, automation control, machine learning, and so on [1]. Based on efforts from around the world, related technologies have been studied in depth [1,3].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Scenario-Adaptive Driving Behavior Prediction Approach to Urban Autonomous Driving

Geng

Liang

et al. 2017

Applied Sciences

View full text Add to dashboard Cite

Driving through dynamically changing traffic scenarios is a highly challenging task for autonomous vehicles, especially on urban roadways. Prediction of surrounding vehicles' driving behaviors plays a crucial role in autonomous vehicles. Most traditional driving behavior prediction models work only for a specific traffic scenario and cannot be adapted to different scenarios. In addition, priori driving knowledge was never considered sufficiently. This study proposes a novel scenario-adaptive approach to solve these problems. A novel ontology model was developed to model traffic scenarios. Continuous features of driving behavior were learned by Hidden Markov Models (HMMs). Then, a knowledge base was constructed to specify the model adaptation strategies and store priori probabilities based on the scenario's characteristics. Finally, the target vehicle's future behavior was predicted considering both a posteriori probabilities and a priori probabilities. The proposed approach was sufficiently evaluated with a real autonomous vehicle. The application scope of traditional models can be extended to a variety of scenarios, while the prediction performance can be improved by the consideration of priori knowledge. For lane-changing behaviors, the prediction time horizon can be extended by up to 56% (0.76 s) on average. Meanwhile, long-term prediction precision can be enhanced by over 26%.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Scenario-Adaptive Driving Behavior Prediction Approach to Urban Autonomous Driving

Geng

Liang

et al. 2017

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…Concerning the trajectory planning, mainly approaches at a local on-road level have been inventoried and summarized in the survey [3], some of them are presented below.…”

Section: Introductionmentioning

confidence: 99%

A Markov Decision Process-based approach for trajectory planning with clothoid tentacles

Mouhagir

Talj

Cherfaoui

et al. 2016

2016 IEEE Intelligent Vehicles Symposium (IV)

View full text Add to dashboard Cite

Abstract-The work presented in this paper focuses on reactive local trajectory planning which plays an essential role for future autonomous vehicles. The challenge is to avoid obstacles in respect to road rules while following a global reference trajectory. The planning approach used in this work is the method of clothoid tentacles generated in the egocentered reference frame related to the vehicle. Generated tentacles in a egocentered grid represent feasible trajectories by the vehicle, and in order to choose the right one, we formulate the problem as a Markov Decision Process.

show abstract

“…Car-like robots can assume positions on the 2-D plane, different headings and steering angles, thus adding up to four degrees of freedom. But it has two kinematic constraints: a) the vehicle is allowed to move only forward and backward and b) the steering angle is bounded (KATRAKAZAS et al, 2015). In fact, there is only control over the longitudinal velocity and the steering wheel angle in order to control four states.…”

Section: Configuration Spacementioning

confidence: 99%

“…Straight lines and circumferences are used to represent the navigable path. However, the path is no longer geometrical continuous at the point of the link between the straight lines and the circumference due to the abrupt change of the orientation angle, which is not allowed in car-like robots since non-holonomic constraints might be present (KATRAKAZAS et al, 2015). Smoother paths using Bézier curves were described in (PÉREZ et al, 2013) and practical results presented in (RASTELLI; PEÑAS, 2015).…”

Section: Dynamic Pathsmentioning

confidence: 99%

Piecewise linear continuous-curvature path planning for autonomous vehicles

Silva¹

View full text Add to dashboard Cite

2018Trata-se da versão corrigida da dissertação. A versão original se encontra disponível na EESC/USP que aloja o Programa de Pós-Graduação de Engenharia Elétrica. Autonomous vehicles have increasingly become an attractive field due its promising capabilities of improvements regarding safety, comfort, traffic flow etc. A required attribute for those vehicles is the ability of autonomously compute its path towards a destination point. The path must be planned considering the constructive aspects of the vehicle in order to guarantee the maneuver feasibility. This work consists on computing a feasible path for autonomous vehicles with non-holonomic constraints. Piecewise linear continuouscurvature paths constituted of clothoids, circular arcs, and straight lines are used for this purpose, providing passenger's comfort. The road network is modeled from GPS (Global Positioning System) vehicle trajectories by defining lanes, roundabouts and intersections. GPS points are used later to parameterize lanes using clothoids and to extract roundabout centers and radii. This approach provides a sparse road network model since GPS points are replaced by parameterized curves. The information about connections between roads coming from the model is used by a global path planner, which computes a minimal length route from the vehicle current position to the destination point. After that, path planners compute intersection and roundabout paths depending on the nature of connections between roads. Also, lanes changes are performed to obey traffic rules. These three path planners that connects adjacent roads use clothoids, circular arc, and straight lines as interpolating curves whose curvature is constrained to that the vehicle can perform: the intersection path planner uses only a minimal amount of steering to perform the maneuver, increasing the comfort level; the roundabout path planner takes the roundabout center and radius as well as parameters that defines the entrance and exit maneuvers to compute the path; the lane change path planner connects lanes belonging to the same road with a prescribed longitudinal traveled distance depending on whether this maneuver is required. In the end, an global continuous-curvature path is generated. As the result of this work, a real urban scenario is modeled and the proposed approaches are validated. Veículos autônomos têm cada vez mais se tornado um campo atraente de pesquisa devido às suas capacidades promissoras de melhorias em segurança, conforto, fluxo de tráfego, etc. Um atributo necessário para esses veículos é a capacidade de calcular, de forma autônoma, o seu caminho para um ponto de destino. O percurso deve ser planejado considerando os aspectos construtivos do veículo para que a viabilidade das manobras a serem executadas seja garantida. Este trabalho consiste no planejamento de trajetória para veículos autônomos com restrições não-holonômicas. Utilizam-se, para esse efeito, trajetórias cuja curvatura seja contínua e linear por partes, constituídas por clotóides, arcos de circun...

show abstract

Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions

Cited by 617 publications

References 98 publications

A Scenario-Adaptive Driving Behavior Prediction Approach to Urban Autonomous Driving

A Scenario-Adaptive Driving Behavior Prediction Approach to Urban Autonomous Driving

A Markov Decision Process-based approach for trajectory planning with clothoid tentacles

Piecewise linear continuous-curvature path planning for autonomous vehicles

Contact Info

Product

Resources

About