Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Detecting aggressive driving behavior is essential for safe transport systems as it leads to the awareness of risks of accidents. Using smartphone-equipped sensors would be promising approach considering the penetration ratio to the consumers. ,  have used a large dataset of accelerometer readings collected by smartphones of drivers. The experiment was performed to explore the accident risk indexes which statistically separate the safe drivers and risky drivers. By the statistical analysis, it is found that the frequency of acceleration exceeding 2.4 m/s2, that of deceleration exceeding 1.4 m/s2, and that of left acceleration exceeding 1.1 m/s2 separate the safe drivers and risky drivers. The classifier using these three criteria achieves 70 % classification accuracy and 83 % detection accuracy of risky drivers.
['Tatsuaki Osafune', 'Toshimitsu Takahashi', 'Noboru Kiyama', 'Tsuneo Sobue', 'Hirozumi Yamaguchi', 'Teruo Higashino']
I am writing a research paper on a idea Analysis of Accident Risks from Driving Behaviors
[{"from": "human", "value": "I am writing a research paper on a idea Analysis of Accident Risks from Driving Behaviors"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Detecting aggressive driving behavior is essential for safe transport systems as it leads to the awareness of risks of accidents. Using smartphone-equipped sensors would be promising approach considering the penetration ratio to the consumers. ,  have used a large dataset of accelerometer readings collected by smartphones of drivers. The experiment was performed to explore the accident risk indexes which statistically separate the safe drivers and risky drivers. By the statistical analysis, it is found that the frequency of acceleration exceeding 2.4 m/s2, that of deceleration exceeding 1.4 m/s2, and that of left acceleration exceeding 1.1 m/s2 separate the safe drivers and risky drivers. The classifier using these three criteria achieves 70 % classification accuracy and 83 % detection accuracy of risky drivers."}]