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AAAI Workshop on AI in Intelligent Vehicle and Highway Systems, Washington, DC, 1993.
meets criteria established by the Secretary in conjunction with the intelligent vehicle highway systems corridors program.
First, an intelligent vehicle model is proposed to better understand environment information and traffic situation.
Real experiments show the actual working of the developed intelligent vehicle application.
In order to achieve the lateral control of the intelligent vehicle, use the bi-cognitive model based on cloud model and cloud reasoning, solve the decision problem of the qualitative and quantitative of the lateral control of the intelligent vehicle.
It realizes that the intelligent vehicle can track random trajectory through controlling the linear velocity and the angular velocity.
This chapter focuses on procedures and tools used in the testing stages of the intelligent vehicle design process.
For the development of intelligent vehicle tires, especially for future self-driving cars, suitable strain sensors are mandatory.
As an alternative, we introduce an agent-based approach where intelligent vehicle agents schedule their own routes.
The third generation is currently developing cooperative control technology and intelligent vehicle control technologies employing external sensors.
The framework is also compared to two recent frameworks applied in the safety assessment of intelligent vehicle safety systems.
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