Nishizaki et al., 2011 - Google Patents
Development of a method for marine accident analysis with bridge simulatorNishizaki et al., 2011
- Document ID
- 7901287542055409037
- Author
- Nishizaki C
- Itoh H
- Yoshimura K
- Hikida K
- Mitomo N
- Publication year
- Publication venue
- 2011 6th International Conference on System of Systems Engineering
External Links
Snippet
The ship operation is system of systems consisted of various systems such as ship management, navigational support, cargo handling and port facility. The marine accidents cause considerable damage to logistics and environment. So, it is effective to ensure the …
- 238000004458 analytical method 0 title abstract description 22
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in preceding groups
- G01C21/20—Instruments for performing navigational calculations
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Sepehri et al. | The impact of shipping 4.0 on controlling shipping accidents: A systematic literature review | |
| Xin et al. | A simulation model for ship navigation in the “Xiazhimen” waterway based on statistical analysis of AIS data | |
| Kang et al. | Maritime simulator based determination of minimum DCPA and TCPA in head-on ship-to-ship collision avoidance in confined waters | |
| CN109032102A (en) | Automatic driving vehicle test method, device, equipment and storage medium | |
| Madni | Integrating humans with and within complex systems | |
| Gil et al. | Know your safety indicator–A determination of merchant vessels Bow Crossing Range based on big data analytics | |
| CN111765904A (en) | Test method, device, electronic device and medium for automatic driving vehicle | |
| EP3009990B1 (en) | Method and system for performing crash analysis of one or more vehicles | |
| Baldauf et al. | e-Navigation and situation-dependent manoeuvring assistance to enhance maritime emergency response | |
| Wu et al. | Clustering of several typical behavioral characteristics of commercial vehicle drivers based on GPS data mining: Case study of highways in China | |
| Nishizaki et al. | Development of a method for marine accident analysis with bridge simulator | |
| Nishizaki et al. | Process of judgment error on collision risk by modeling judgment patterns of officers | |
| Wu et al. | Reliability and safety assessment of automated driving systems: review and preview | |
| Xu et al. | Novel fast safety assessment method for the buffer section of maintenance work zone | |
| Artana et al. | Real-time monitoring of subsea gas pipelines, offshore platforms, and ship inspection scores using an Automatic Identification System | |
| Nordkvist | An advanced method for detecting exceptional vessel encounters in open waters from high resolution ais data | |
| Farahbod et al. | Engineering situation analysis decision support systems | |
| Ding et al. | A novel deep learning framework for detecting seafarer’s unsafe behavior | |
| CN104122111B (en) | A kind of three class comprehensive safety method for early warning of bridge structure | |
| Akkermann et al. | Scenario-based V&V in a maritime co-simulation framework | |
| Yoshimura et al. | A Method for Quantifying the Risks of Human Error from Experiments with the ship Bridge Simulator | |
| Psarros | Comparing the navigator’s response time in collision and grounding accidents | |
| Zhou et al. | Determination of Ship Collision Avoidance Timing Using Machine Learning Method | |
| CN113486843A (en) | Improved YOLOv 3-based multi-scene crew unsafe behavior detection method | |
| Celik et al. | AN APPLICATION OF AGENT-BASED TRAFFIC FLOW MODEL FOR MARITIME SAFETY MANAGEMENT EVALUATION |