A Real-Time Autonomous Highway Accident Detection Model Based on Big Data Processing and Computational Intelligence
| Autor: | Gokhan Kucukayan, Erdogan Dogdu, Murat Ozbayoglu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
FOS: Computer and information sciences
Computer science Computer Science - Artificial Intelligence Population Real-time computing Decision tree Computational intelligence Machine Learning (stat.ML) ComputerApplications_COMPUTERSINOTHERSYSTEMS 02 engineering and technology Computer security computer.software_genre Statistics - Machine Learning 0502 economics and business 0202 electrical engineering electronic engineering information engineering education Intelligent transportation system 050210 logistics & transportation education.field_of_study 05 social sciences 68TXX Traffic flow Artificial Intelligence (cs.AI) Traffic congestion 020201 artificial intelligence & image processing computer |
| Zdroj: | IEEE BigData ResearcherID |
| Popis: | Due to increasing urban population and growing number of motor vehicles, traffic congestion is becoming a major problem of the 21st century. One of the main reasons behind traffic congestion is accidents which can not only result in casualties and losses for the participants, but also in wasted and lost time for the others that are stuck behind the wheels. Early detection of an accident can save lives, provides quicker road openings, hence decreases wasted time and resources, and increases efficiency. In this study, we propose a preliminary real-time autonomous accident-detection system based on computational intelligence techniques. Istanbul City traffic-flow data for the year 2015 from various sensor locations are populated using big data processing methodologies. The extracted features are then fed into a nearest neighbor model, a regression tree, and a feed-forward neural network model. For the output, the possibility of an occurrence of an accident is predicted. The results indicate that even though the number of false alarms dominates the real accident cases, the system can still provide useful information that can be used for status verification and early reaction to possible accidents. |
| Databáze: | OpenAIRE |
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