A Balance-Artificial Potential Field Method for Autonomous Surface Vessel Navigation in Unstructured Riverine Environment

Hong, Mei; Arshad, Mohd Rizal

doi:10.1016/j.procs.2015.12.341

Cited by 11 publications

(8 citation statements)

References 8 publications

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“…Besides the COLREGs related studies, Hong and Arshad (2015) introduced a balance-APF hybrid method which helps the ASV successfully avoid static obstacles in challenging situations. Serigstad et al (2018) reported a hybrid dynamic window (HDW) algorithm which acts as both collision avoidance method and trajectory tracker for ASVs.…”

Section: Methodology and Categoriesmentioning

confidence: 99%

“…Brief discussions regarding trajectory following problems can also be found in Breivik and Loberg (2011), Sharma et al. (2012), Hong and Arshad (2015), Serigstad et al. (2018), and Mousazadeh et al.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Besides the COLREGs‐related studies, Hong and Arshad (2015) introduced a balance‐APF hybrid method that helps the ASV successfully avoid static obstacles in challenging situations. Serigstad et al.…”

Section: Literature Reviewmentioning

confidence: 99%

“…• Category 1: Safety Collision Avoidance Wang et al (2018b); Naeem et al (2016); Zhao et al (2016); Campbell and Naeem (2012); Beser and Yildirim (2018); Naeem et al (2012); Lu et al (2016); Lee et al (2015b); Mei and Arshad (2017); Hu et al (2017); Xu et al (2018); Savvaris et al (2014); Bertaska et al (2015); Hong and Arshad (2015); Serigstad et al (2018); Praczyk (2015); Krishnamurthy et al (2008); Hermann et al (2015); Bovcon et al (2018); Statheros et al (2008); Burmeister et al (2014); Rolls-Royce (2016); Escario et al (2012); Singh et al (2018); Song et al (2017); Kim et al (2017a); Breivik and Loberg (2011); Niu et al (2018); Mousazadeh et al (2018); Liu and Bucknall (2018); Niu et al (2016); Thakur et al (2012); Wang et al (2019b); Du et al (2018); Ma et al (2018); Crasta et al (2018); Liu and Bucknall (2015); Yang et al (2015); Liu and Bucknall (2016); Liu et al (2017b); Ma et al (2014) Cyber Security Hogg and ...…”

Section: Appendixmentioning

confidence: 99%

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Autonomous vessels: state of the art and potential opportunities in logistics

Góez

Guajardo

et al. 2020

Int Trans Operational Res

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The growth in technology on autonomous transportation systems is currently motivating a number of research initiatives. This paper first presents a survey of the literature on autonomous marine vessels in general. By identifying the main research interests in this field, we define 10 thematic categories. The collected articles are then classified according to these categories. We show that research on autonomous vessels has increased dramatically in the past decade. However, most of the published articles have focused on navigation control and safety issues. Studies regarding other topics, such as transport and logistics, are very limited. Although our main interest is the literature on autonomous vessels, we contrast its development with respect to the literature on autonomous cars so as to have a better understanding about the future potentials in the research on autonomous vessels. The comparison shows that there are great opportunities for research about transportation and logistics with autonomous vessels. Finally, several potential research areas regarding logistics with autonomous vessels are proposed. As the technology behind remote‐controlled or autonomous ships is maturing rapidly, we believe that it is already time for researchers in the field to start looking into future water‐borne transport and logistics using autonomous vessels.

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Section: Methodology and Categoriesmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Appendixmentioning

confidence: 99%

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Autonomous vessels: state of the art and potential opportunities in logistics

Góez

Guajardo

et al. 2020

Int Trans Operational Res

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“…Obstacle-avoidance algorithms for robots can be implemented in designing the obstacle-avoidance algorithms for controlling CAVs. Because of the advantage of the artificial potential field in robot path planning, and the resemblance in control of AVs and robots, researchers have investigated utilizing potential field for controlling vehicles ( 10 – 17 ).…”

mentioning

confidence: 99%

Using Artificial Potential Field Theory for a Cooperative Control Model in a Connected and Automated Vehicles Environment

et al. 2020

Transportation Research Record: Journal of the Transportation R

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Artificial potential field (APF) theory has been extensively applied in traffic path planning as an efficient method to avoid collision. However, studies in collision avoidance based on APF theory only considered the movement of single vehicle. In this paper, a vehicle cooperative control model for avoiding collision in the connected and autonomous vehicles (CAVs) environment is presented, using APF theory. The proposed model not merely guarantees the travel safety of vehicles in avoiding collision, but also promotes driving comfort and improves traffic efficiency. To verify the cooperative control model, simulations of four scenarios are designed and compared with the human driving environment. Five indicators are selected to evaluate the results, that is, time–space diagram, time mean speed (TMS), the rate of large deceleration time (large deceleration is that deceleration larger than –2 m/s2), the inverse time-to-collision ([Formula: see text]), and lane-changing times. According to the simulation results, the cooperative control model could alleviate the capacity drop and increase the TMS to improve traffic efficiency, reduce the rate of the large deceleration time to promote driving comfort, and decrease [Formula: see text] to promote safety in small and large input flow rates. The results reveal the proposed model is significantly superior to the human driving environment whether in free or congested situations, except for the lane-change times, which are slightly larger.

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