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Abstract
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Zijun Jiang, Zhigang Xu, Yunchao Li, Haigen Min and Jingmei Zhou
Precise vehicle localization is a basic and critical technique for various intelligent transportation system (ITS) applications. It also needs to adapt to the complex road…
Abstract
Purpose
Precise vehicle localization is a basic and critical technique for various intelligent transportation system (ITS) applications. It also needs to adapt to the complex road environments in real-time. The global positioning system and the strap-down inertial navigation system are two common techniques in the field of vehicle localization. However, the localization accuracy, reliability and real-time performance of these two techniques can not satisfy the requirement of some critical ITS applications such as collision avoiding, vision enhancement and automatic parking. Aiming at the problems above, this paper aims to propose a precise vehicle ego-localization method based on image matching.
Design/methodology/approach
This study included three steps, Step 1, extraction of feature points. After getting the image, the local features in the pavement images were extracted using an improved speeded up robust features algorithm. Step 2, eliminate mismatch points. Using a random sample consensus algorithm to eliminate mismatched points of road image and make match point pairs more robust. Step 3, matching of feature points and trajectory generation.
Findings
Through the matching and validation of the extracted local feature points, the relative translation and rotation offsets between two consecutive pavement images were calculated, eventually, the trajectory of the vehicle was generated.
Originality/value
The experimental results show that the studied algorithm has an accuracy at decimeter-level and it fully meets the demand of the lane-level positioning in some critical ITS applications.
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SungKwan Ku, Hojong Baik and Taehyoung Kim
The surveillance equipment is one of the most important parts for current air traffic control systems. It provides aircraft position and other relevant information including…
Abstract
Purpose
The surveillance equipment is one of the most important parts for current air traffic control systems. It provides aircraft position and other relevant information including flight parameters. However, the existing surveillance equipment has certain position errors between true and detected positions. Operators must understand and account for the characteristics on magnitude and frequency of the position errors in the surveillance systems because these errors can influence the safety of aircraft operation. This study aims to develop the simulation model for analysis of these surveillance position errors to improve the safety of aircrafts in airports.
Design/methodology/approach
This study investigates the characterization of the position errors observed in airport surface detection equipment of an airport ground surveillance system and proposes a practical method to numerically reproduce the characteristics of the errors.
Findings
The proposed approach represents position errors more accurately than an alternative simple approach. This study also discusses the application of the computational results in a microscopic simulation modeling environment.
Practical implications
The surveillance error is analyzed from the radar trajectory data, and a random generator is configured to implement these data. These data are used in the air transportation simulation through an application programing interface, which can be applied to the aircraft trajectory data in the simulation. Subsequently, additionally built environment data are used in the actual simulation to obtain the results from the simulation engine.
Originality/value
The presented surveillance error analysis and simulation with its implementation plan are expected to be useful for air transportation safety simulations.
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Jianfeng Zhao, Bodong Liang and Qiuxia Chen
The successful and commercial use of self-driving/driverless/unmanned/automated car will make human life easier. The paper aims to discuss this issue.
Abstract
Purpose
The successful and commercial use of self-driving/driverless/unmanned/automated car will make human life easier. The paper aims to discuss this issue.
Design/methodology/approach
This paper reviews the key technology of a self-driving car. In this paper, the four key technologies in self-driving car, namely, car navigation system, path planning, environment perception and car control, are addressed and surveyed. The main research institutions and groups in different countries are summarized. Finally, the debates of self-driving car are discussed and the development trend of self-driving car is predicted.
Findings
This paper analyzes the key technology of self-driving car and illuminates the state-of-art of the self-driving car.
Originality/value
The main research contents and key technology have been introduced. The research progress as well as the research institution has been summarized.
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Mo He, Xiaogang Wang and Naigang Cui
The purpose of this paper is to present a high accuracy path following method for low-cost fixed-wing UAVs.
Abstract
Purpose
The purpose of this paper is to present a high accuracy path following method for low-cost fixed-wing UAVs.
Design/methodology/approach
The original vector field (VF) algorithm is condensed. A spatial integration mechanism is added to the existing VF and nonlinear guidance law, aiming to decrease steady-state cross-track-error and cope with long-term disturbance.
Findings
Numerical simulations show the proposed method could diminish steady-state cross-track-error effectively. Test flights show the proposed method is applicable on low-cost fixed-wing UAVs.
Practical implications
The path following accuracy shown in simulations and test flights indicates the proposed method could be deployed in scenarios including inflight rendezvous, formation, trafficway take-off and landing.
Originality/value
This paper provides an improved high-accuracy path following method for low-cost fixed-wing UAVs.
Details
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Joan Mileski, Christopher Clott and Cassia Bomer Galvao
The maritime industry is increasingly impacted by the Internet of things (IoT) through the automation of ships and port activities. This increased automation creates new security…
Abstract
Purpose
The maritime industry is increasingly impacted by the Internet of things (IoT) through the automation of ships and port activities. This increased automation creates new security vulnerabilities for the maritime industry in cyberspace. Any obstruction in the global supply chain due to a cyberattack can cause catastrophic problems in the global economy. This paper aims to review automatic identification systems (AISs) aboard ships for cyber issues and weaknesses.
Design/methodology/approach
The authors do so by comparing the results of two receiver systems of the AIS in the Port of Houston; the JAMSS system aboard the Space Station and the “Harborlights” system for traffic control in the Port.
Findings
The authors find that inconsistent information is presented on the location of same ships at the same time in the Port. Upon further investigation with pilots, the authors find that these inconsistencies may be the result of the strength of power with which an AIS is transmitted. It appears the power may be reduced to the AIS in port but that it varies within port and varies by pilot operators. This practice may open the AIS system for tampering.
Originality/value
Further, this inconsistency may require further policy regulation to properly address cyber information in a port.
Details