Application of the intellectual decision making system for vessel traffic control

Background/Objectives: Ship trajectories in Vessel Traffic Service (VTS) system are generated by integrating the Automatic Identification System (AIS) or Radar system. However, the AIS system has missing data section caused by AIS device problems, radio jamming, and so on. These data have been confusing ship navigators and VTS operators.Methods/Statistical analysis: In order to extract missing AIS data, time intervals of sequent points from each ship trajectory are calculated. The section with missing AIS data is above a threshold time limit defined by characteristics. Using k-means algorithm, missing AIS data were clustered into several clusters stored by ship’s ID and sailing direction. Using association rule mining analysis, meaningful association pattern were calculated by missing AIS dataset.Findings: As a result of the association rule mining, we found several missing AIS situation patterns. In case of the west route, the probability of missing AIS situation is high when they enter the east and passenger routes. Also, the probability of missing AIS situation of passing the passenger route is high when that ship enter the LNG, east and west routes.Improvements/Applications: These results can be used to predict the probability of missing AIS data in VTS system.

Concise Encyclopedia of Traffic & Transportation Systems

선박교통류 평가는 대상해역 해상교통특성 파악을 통하여 정량화된 체계화된 교통관리를 수행함으로써 해양사고를 예방하는데 중요하다. 해상교통류의 특성은 선박자동식별장치(AIS, Automatic Identification System)가 선박에 설치됨에 따라 이 장치에서 수신된 정보를 토대로 평가할 수 있다. 본 연구에서는 해상교통관제센터(VTS, Vessel Traffic Services)에서 선박으로부터 수집된 위치, 속력, 침로, 시간 정보로부터 항로상에 해상교통류를 평가하기 위한 시뮬레이터를 구현하였다. 그 결과 해상교통관제센터에서 수집된 데이터로부터 선박 통항량, 통항분포, 선박속력분포, 기하학적 충돌빈도가 계산되어 표시된다. 이러한 해상교통류평가 평가는 해상교통관제사가 해상교통관리의 관점에서 해상안전을 위한 서비스를 제공하는데 유효하게 활용될 수 있을 것으로 사료된다. Maritime traffic assessment is important to understand the characteristics of maritime traffic and to prevent maritime accidents. The maritime traffic assessment can be calculated from the ship trajectory data observed by using AIS(Automatic Identification System). This paper developes a maritime traffic assessment tool using ship's position and speed, course, time data from ships navigating waterways. The results are represented in terms of the number of traffic quantity and traffic distribution, speed distribution, geometric collision candidates. The developed tool will contributes to advance maritime traffic safety by VTS(Vessel Traffic Services).

This study developed a decision‐making support system (DMSS) for automatically determining the route priority of vessels entering/exiting the waters surrounding the port monitored by vessel traffic services (VTS). The developed DMSS was combined with marine geographic information systems (GIS), automatic identification systems (AIS), and fuzzy logic theory. The simulations of case studies for the ports of Keelung and Singapore were shown to illustrate the fitness of the developed DMSS. Based on the vessel information received/transmitted by AIS within the waters monitored by VTS, the developed DMSS can compute and output the route priority values for the captains on board and the operators in VTS stations as a point of reference. In other words, each ship in the waters surrounding the port can know the route priority for entering/exiting the port. The simulation results of case studies showed that the developed DMSS seems promising. The developed DMSS could be a useful tool in improving a port's navigation safety.

Traffic congestion especially at road intersections is becoming an issue for which road traffic users contend with daily. The conventional traffic light applies a fixed logic of allocating equal “GO” time to lanes of traffic at road intersections irrespective of the density of traffic on each lane. Using the PIC18F4550 microcontroller interfaced with infrared sensors, a new traffic light control system was developed to ease the flow of traffic at a particular troubled spot in Uyo Metropolis (Abak Road, Udo Eduok, Udo Obio streets intersection) in Akwa Ibom State, Nigeria. Simulation of the proposed design was performed using the Proteus Software while implementation was carried out on a prototype. Performance evaluation of the prototype implemented showed that the 4 arrays (IR Transmitter and Receiver) of infrared sensors interfaced with the microcontroller using AND gates and strategically positioned to read the density of traffic on each lane at the intersection triggered when a vehicle comes between the transmitter and the receiver. Obtaining inputs from these sensors together with the logic from the microcontroller, a new traffic light control system was developed capable of controlling traffic based on the density of each lane of traffic. Results obtained from simulation and implementation of the design indicates that the traffic control system with the PIC18F4550 microcontroller and the infrared sensors gives a better performance compared to the conventional traffic light control system.Keywords: Road traffic density, Traffic light, Uyo metropolis, ‘+’ road intersection, Proteus

Most computerized traffic control systems that are now operational use a central computer to perform virtually all data processing tasks. These systems operate satisfactorily, but it is believed that this system design approach is now stretched to its limit of practical capability. The recent availability of economical microprocessors and their successful application to traffic signal controllers suggests that investigations should be conducted into the formulation of traffic control system concepts that make full use of microprocessor capabilities and thereby identify improved systems for future applications, particularly those that relate to the concept of traffic management systems that is currently in favor. This paper describes a Multilevel Distributed System (MLDS) concept designed to meet future traffic control and traffic management system requirements as currently envisioned.

Navigation safety has become one of the important issues to the entire world community. Automatic Identification System (AIS) firstly has been used to comply with safety and security regulations, functioning as collision avoidance, vessel traffic services, maritime security, aids to navigation, search and rescue and accident investigation. This paper presents marine navigation collision preventing system between ships and ships using AIS. In the system, the raw data from AIS is crossed with database based MMSI number to find detail information then, location of each ship was plotted on to Google Map. The safety distance is assessed based actual and stopping distance. The system was tested in the Batam and Singapore Channel.

This paper describes the application method of bumper area defined in the ship domain theory and it is to identify risky sectors in VTS(Vessel Traffic Services) area. The final goal of this work is to develop early warning system providing the location information with high traffic risks in Mokpo VTS area and to prevent the human errors of VTS Officer(VTSO). The current goal of this paper is to find evaluation and detection method of risky sectors. The ratio between overlapped bumper area of each vessels and the summing area of a designated sector, Ratio to Evaluate Risk(RER) <TEX>${\gamma}$</TEX> is used as one of evaluation and detection parameter. The usability of overlapped bumper area is testified through three kinds of scenarios for various traffic situations. The marine traffic data used in the experiments is collected by AIS(Automatic Identification System) receiver and then compiled in the SQL(Structured Query Language) Server. Through the analysis of passing vessel's tracks within the boundary of Mokpo VTS area, the total of 11 sectors are identified as evaluation unit sector. As experiment results from risk evaluation for the 11 sectors, it is clearly known that the proposed method with RER <TEX>${\gamma}$</TEX> can provide the location information of high risky sectors which are need to keep traffic tracks of vessel movements and to maintain traffic monitoring by VTSO.

Traffic congestion is one of the main problems in transportation sector and it causes a lot of drawbacks to public. The traffic light system is used to reduce the level of occurring traffic congestion. Generally, the available traffic light systems use a fixed time setting. This old traffic control system is no longer able to manage the ever-changing traffic conditions effectively and efficiently, causing a long queue of vehicles. To overcome this problem, a traffic light control system that can adapt to actual conditions of road density and can run automatically is offered. This system utilizes Google Map API as a road density data source. The result of this study is a traffic control system that can adjust the green light time duration based on the obtained density values and density trends, simulation of this adaptive system as well as simulation results analysis. A prototype of this adaptive control system was also produced in this study.

This paper proposes a new intelligent traffic control (ITC) system which is more efficient than the traffic control system currently used in the state of Kuwait.The proposed ITC system is designed as a dynamic system by using a fuzzy expert system; the fuzzy rules are applied in the visual basic and computer-based program (Excel) to run the validation process.The developed control system applied on five intersections in the grid network at four periods.The results show that the number of vehicles passing the intersection phases is increased in most phases by an average of 12.9% at the first period, 23.3% at the second period, 10.4% at the third period and by 21.2% at the fourth period.For the same periods, the phases green time is increased by an average of 9.1%, 5.8%, 9.9% and 6.3%.And the number of intersection cycles remains constant at the most time which means that the developed control system distributes the phases green time dynamically based on the traffic situation.

Development of a Gridded Maritime Traffic DB for e-Navigation

This research is focused on laboratory based analysis on hardware module of traffic light with Programmable Logic Controller (PLC) software. There are four ways in hardware model for detection of vehicle; each way has one sensor button, three Light Emitted Diodes (LEDs) with individual colors say red, yellow and green represents the traffic light in each lane. Sensor and LEDs are connected to Mitsubishi Programmable Logic Controller (PLC) and each part on hardware being controlled by PLC. Ladder diagrams are programmed by software to monitor the system and helps to improve public transportation services, thereby improving traffic guidance and traffic light control. The system was developed by setting the appropriate time for the traffic lights to respond accordingly. The controller checks the priority and provides an exit signal to the traffic light post to turn the red, yellow or green lights on or off. Finally, the signal lights were successfully controlled by the PLC. Hence the system used in traffic control systems contain low power consumption, low engineering cost and increased safety.

The article presents the issue of digital standard interfaces of railway traffic control systems. The digitization and standardization of interfaces are digital rail elements, an essential feature of integrating various devices, facilities, and processes in one coherent system. The authors described the problems of connecting computer systems, starting from the interface's definition, including technical and functional aspects. Examples of interface types selected problems resulting from connecting incompatible devices and attempts to solve them are presented. It then provides background information on the project to develop a digital interface standard for selected rail traffic control systems. The project described in this article, under the name of "Standardization of selected interfaces of railway traffic control equipment and systems" POIR.04.01.01-00-0005/17, has been created as part of the BRIK (Research and Development in Railway Infrastructure) program and has been cofinanced both by the NCBiR (The National Centre for Research and Development), as well as the PKP Polskie Linie Kolejowe S.A. (PKP PLK - Polish State Railways). The project's goal is to develop, through research, specifications, and requirements for interfaces used in railway traffic control systems, which will become a standard enabling linking of systems from different manufacturers. The project results will be dedicated to using on the railway network managed by PKP PLK (and potentially also by other infrastructure managers) and documentation containing descriptions of standards, guidelines for the application and design of these interfaces.

이 논문에서는 도심 지역의 교통 제어 시스템의 동적 응답 성능 향상을 위하여 적응형 Q-Learning 강화 학습 메커니즘을 설계 하였다. 도로, 자동차, 교통 제어 시스템을 지능 시스템으로 모델링 하고, 자동차와 도로 사이는 무선 통신을 이용한 네트워크가 구성된다. 도로와 대로변에 필요한 센터네트워크가 설치되고 Q-Learning 강화 학습은 제안한 메커니즘의 구현을 위해 핵심 알고리즘으로 채택하였다. 교통 신호 제어 규칙은 자동차와 도로에서 매 시간 업데이트된 정보에 따라서 결정되며, 이러한 방법은 기존의 교통 제어 시스템에 비하여 도로를 효율적으로 활용하며 결과적으로 교통 흐름을 개선 한다. 알고리즘을 활용한 최적의 신호 체계는 온라인상에서 자동으로 학습함으로서 구현된다. 시뮬레이션을 통하여 제안한 알고리즘이 기존 시스템에 비하여 효율성 개선과 차량의 대개 시간에 대한 성능 지수가 모두 30% 이상 향상되었다. 실험 결과를 통하여 제안한 시스템이 교통 흐름을 최적화함을 확인하였다. A flexible mechanism is proposed in this paper to improve the dynamic response performance of a traffic flow control system in an urban area. The roads, vehicles, and traffic control systems are all modeled as intelligent systems, wherein a wireless communication network is used as the medium of communication between the vehicles and the roads. The necessary sensor networks are installed in the roads and on the roadside upon which reinforcement learning is adopted as the core algorithm for this mechanism. A traffic policy can be planned online according to the updated situations on the roads, based on all the information from the vehicles and the roads. This improves the flexibility of traffic flow and offers a much more efficient use of the roads over a traditional traffic control system. The optimum intersection signals can be learned automatically online. An intersection control system is studied as an example of the mechanism using Q-learning based algorithm, and simulation results showed that the proposed mechanism can improve the traffic efficiency and the waiting time at the signal light by more than 30% in various conditions compare to the traditional signaling system.

A smart city has being studied to improve the quality of life. A traffic control system is a part of what smart cities need to deal with. The traffic control system identifies the traffic flow and controls the vehicle at an intersection. This study proposes a traffic signal control system that uses Q-learning to maximize throughput and minimize waiting time. The proposed system has optimized traffic signals by adjusting the time of the green signal and allocating the green signal. We conducted an experiment by applying two kinds of traffic load. The performance is also analyzed by applying data with urban traffic density distribution.