A control system for autonomous vehicle valet parking

Min, Kyoungwook; Choi, Jeongdan

doi:10.1109/iccas.2013.6704211

Cited by 18 publications

(8 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The outdoor environment included various weather conditions (sunny, cloudy, rainy, and snowy). Also, it was confirmed to have successfully implemented AVP services and that the unmanned vehicle performs parking space navigation, driving, and parking through a combination of proposed algorithms and AVP control technology [3].…”

Section: Experimental Environmentmentioning

confidence: 83%

“…An autonomous valet parking (AVP) system is a complete autonomous unmanned vehicle system that drives the car to a safe parking lot and parks it there on behalf of the driver. Also, the system drives the car to a position where the driver can board it [3]. An AVP system drives a car at a low speed or parks it within a limited area, such as a parking area, or surrounding road.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Parking Space Recognition for Autonomous Valet Parking Using Height and Salient-Line Probability Maps

Han¹,

Choi²

2015

ETRI J

Self Cite

View full text Add to dashboard Cite

An autonomous valet parking (AVP) system is designed to locate a vacant parking space and park the vehicle in which it resides on behalf of the driver, once the driver has left the vehicle. In addition, the AVP is able to direct the vehicle to a location desired by the driver when requested. In this paper, for an AVP system, we introduce technology to recognize a parking space using image sensors. The proposed technology is mainly divided into three parts. First, spatial analysis is carried out using a height map that is based on dense motion stereo. Second, modelling of road markings is conducted using a probability map with a new salient‐line feature extractor. Finally, parking space recognition is based on a Bayesian classifier. The experimental results show an execution time of up to 10 ms and a recognition rate of over 99%. Also, the performance and properties of the proposed technology were evaluated with a variety of data. Our algorithms, which are part of the proposed technology, are expected to apply to various research areas regarding autonomous vehicles, such as map generation, road marking recognition, localization, and environment recognition.

show abstract

Section: Experimental Environmentmentioning

confidence: 83%

Section: Introductionmentioning

confidence: 99%

Parking Space Recognition for Autonomous Valet Parking Using Height and Salient-Line Probability Maps

Han¹,

Choi²

2015

ETRI J

Self Cite

View full text Add to dashboard Cite

show abstract

“…Some work focuses on AV parking. [25] developed a control system for AV valet parking with a focus on steering control. [26] designed an intelligent vehicle system to implement the AV valet parking service.…”

Section: Related Workmentioning

confidence: 99%

Coordinated Autonomous Vehicle Parking for Vehicle-to-Grid Services: Formulation and Distributed Algorithm

Lam

Hou

et al. 2018

IEEE Trans. Smart Grid

View full text Add to dashboard Cite

Autonomous vehicles (AVs) will revolutionarize ground transport and take a substantial role in the future transportation system. Most AVs are likely to be electric vehicles (EVs) and they can participate in the vehicle-to-grid (V2G) system to support various V2G services. Although it is generally infeasible for EVs to dictate their routes, we can design AV travel plans to fulfill certain system-wide objectives. In this paper, we focus on the AVs looking for parking and study how they can be led to appropriate parking facilities to support V2G services. We formulate the Coordinated Parking Problem (CPP), which can be solved by a standard integer linear program solver but requires long computational time. To make it more practical, we develop a distributed algorithm to address CPP based on dual decomposition. We carry out a series of simulations to evaluate the proposed solution methods. Our results show that the distributed algorithm can produce nearly optimal solutions with substantially less computational time. A coarser time scale can improve computational time but degrade the solution quality resulting in possible infeasible solution. Even with communication loss, the distributed algorithm can still perform well and converge with only little degradation in speed.

show abstract

“…Among the different planning techniques it is possible to distinguish between geometric approaches, with either constant turning radius [4], [5] using saturated feedback controllers, or continuous-curvature planning using clothoids [6]; heuristic approaches [7] and machine learning techniques [8]. It is worth to note that parking maneuvers with forward motions are seldom considered, with [9] for the parallel parking case and [10] for the perpendicular case being some of the few works on this regard.…”

Section: Introductionmentioning

confidence: 99%

Laser-Based Control Law for Autonomous Parallel and Perpendicular Parking

Morales

Kermorgant

Quijada

et al. 2018

2018 Second IEEE International Conference on Robotic Computing (IRC)

View full text Add to dashboard Cite

Abstract-This paper addresses the perpendicular and parallel parking problems of car-like vehicles for both forward and reverse maneuvers in one trial by extending the work presented in [1] using a multi sensor based controller with a weighted control scheme. The perception problem is discussed briefly considering a Velodyne VLP-16 and a SICK LMS151 as the sensors providing the required exteroceptive information. The results obtained from simulations and real experimentation for different parking scenarios show the validity and potential of the proposed approach. Furthermore, it is shown that, despite the need of handling several constraints for collision avoidance, the required computation time of the proposed approach is small enough to be used online.

show abstract

A control system for autonomous vehicle valet parking

Cited by 18 publications

References 3 publications

Parking Space Recognition for Autonomous Valet Parking Using Height and Salient-Line Probability Maps

Parking Space Recognition for Autonomous Valet Parking Using Height and Salient-Line Probability Maps

Coordinated Autonomous Vehicle Parking for Vehicle-to-Grid Services: Formulation and Distributed Algorithm

Laser-Based Control Law for Autonomous Parallel and Perpendicular Parking

Contact Info

Product

Resources

About