加拿大论文代写-自动驾驶汽车技术

加拿大论文代写-自动驾驶汽车技术。自动驾驶汽车是一种无人驾驶汽车，没有人类驾驶员也有自动导航的能力(Rosenzweig & Bartl, 2015)。这项技术可以制造出不需要司机帮助就能从一个地方移动到另一个地方的汽车。这类汽车可以被视为无人驾驶的机器人汽车，可以从一个目的地行驶到另一个目的地。为了获得完全自动驾驶的资格，车辆必须具有在任何人为干扰下自动导航的能力，并且必须有预先确定的目的地，以便在不适合使用此类车辆的道路上行驶(Bagloee et al.， 2016)。大多数技术在用于自动化应用程序时似乎并不重要。这是因为附加的挑战是由不重要的技术造成的不可预测的障碍，在道路上和天气的变化。

Autonomous vehicles or driverless cars are also called as the intelligent vehicles that have the autonomous capabilities and functions. There had been various motivations behind the development of the driverless cars and intelligent vehicles. The technology of the driverless cars includes sense in vehicles, sensing environment, ability to work with digital maps, communication ability with transportation infrastructure and understanding satellite navigation (Broggi et al., 2016). Such cars have been predicted in science fiction and are highly discussed in popular media. Such cars are seen as the future of the transportation system, as these cars will help in reducing the parking cost, traffic, roadway cost, rate of accidents and also pollution emission (Litman, 2014). The savings and benefits are so high that everybody will be virtually benefitted by this technology
The research on the autonomous vehicles is getting mature every day and many such vehicles can run on the road in near future. Such vehicles have high degree of control and have the capability to respond instantaneous situation in an effective and efficient manner (Lam, Leung & Chu, 2014). Some of the early works of engineering that revolutionized the technique of the automotive industry include advanced tracking system, optimal filtering techniques and multi sensor data fusion techniques. Multiple sensor combination or fusions have been used in the automotive industry. One of the most significant projects funded by the European Union for the autonomous vehicles was named as PreVENT. This project aimed towards providing the safety to the drivers by avoiding road accidents. This project was mainly dedicated towards implementing the sensor data fusion technique for creating the effective crash mitigation strategies. The project concluded that low level fusion of the sensor data is effective and beneficial in producing the combined effect of the sensors, while the high level combinations will be beneficial for scalability, modularity and would be able to handle the communication load.
The sensors for the driverless cars can be classified in two different types, Active sensors and Passive sensors. This classification is done on the basis of their capability and physical phenomenon. They are able to measure by actively probing the environment or by passively perceiving the environment (Yenkanchi, 2016). Active sensors are mainly those which send the radiations for detecting an object around the vehicle and it also eliminates the noise of emissions. However, the passive sensors are those perceiving the information that is based on the illumination of the environment. Passive sensors are considered to be less expensive in the way of their mechanism. Some of the examples of the active sensors are radar based sensors, laser based sensors and ultrasonic based sensors. One significant example of the passive sensor is camera. Since the autonomous automated cars are the next evolution of the transportation that will increase the safety, it will enhance driving experience and traffic efficiency (Petit et al., 2015). A completely automated vehicle will significantly rely on the sensor reading for the long term (planning) and short term (related to safety) driving decisions.

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