Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Advanced driver assistance systems are the nest addition to vehicular technology. Such systems use a wide array of sensors to provide a superior driving experience. Vehicle safety and driver alert are important parts of these system.  proposes a driver alert system to prevent and mitigate adjacent vehicle collisions by proving warning information of on-road vehicles and possible collisions. A dynamic Bayesian network (DBN) is utilized to fuse multiple sensors to provide driver awareness. It detects oncoming adjacent vehicles and gathers ego vehicle motion characteristics using an on-board camera and inertial measurement unit (IMU). A histogram of oriented gradient feature based classifier is used to detect any adjacent vehicles. Vehicles front-rear end and side faces re considered in training the classifier. Ego vehicles heading, speed and acceleration are captured from the IMU and feed into the DBN. The network parameters re learned from data via expectation maximization(EM) algorithm. The DBN is designed to provide two type of warning to the driver, a cautionary warning and a brake alert for possible collision with other vehicles. Experiments re completed on multiple public databases, demonstrating successful warnings and brake alerts in most situations.
['Asif Iqbal', 'Carlos Busso', 'Nicholas R. Gans']
I am writing a research paper on a idea Adjacent Vehicle Collision Warning System using Image Sensor and Inertial Measurement Unit
[{"from": "human", "value": "I am writing a research paper on a idea Adjacent Vehicle Collision Warning System using Image Sensor and Inertial Measurement Unit"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Advanced driver assistance systems are the nest addition to vehicular technology. Such systems use a wide array of sensors to provide a superior driving experience. Vehicle safety and driver alert are important parts of these system.  proposes a driver alert system to prevent and mitigate adjacent vehicle collisions by proving warning information of on-road vehicles and possible collisions. A dynamic Bayesian network (DBN) is utilized to fuse multiple sensors to provide driver awareness. It detects oncoming adjacent vehicles and gathers ego vehicle motion characteristics using an on-board camera and inertial measurement unit (IMU). A histogram of oriented gradient feature based classifier is used to detect any adjacent vehicles. Vehicles front-rear end and side faces re considered in training the classifier. Ego vehicles heading, speed and acceleration are captured from the IMU and feed into the DBN. The network parameters re learned from data via expectation maximization(EM) algorithm. The DBN is designed to provide two type of warning to the driver, a cautionary warning and a brake alert for possible collision with other vehicles. Experiments re completed on multiple public databases, demonstrating successful warnings and brake alerts in most situations."}]