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Progressed efforts have been made on the development of Vehicle to Vehicle communication technology. The European Telecommunications Standard Institute has allocated a dedicated frequency band of 5.855 - 5.925 GHz to vehicular communication. Numerous on road measurement campaigns have been conducted by joint consortium to evaluate the performance of Vehicle to Vehicle (V2V) communication around the world. However due to the scalability limitation of on road measurements, light-weight simulation tools are more widely implemented to gain general insights into Vehicle to Vehicle communication. Hence, the needs of simulation regarding evaluation on the performance of this technology have been aroused. In order to ensure the reliability of the simulation, propagation model on Vehicle to Vehicle communication should be accurate to have realistic results. In this paper, we conducted a survey of the available propagation models in urban, suburban and highway area.

Progressed efforts have been made on the development of Vehicle to Vehicle communication technology. The European Telecommunications Standard Institute has allocated a dedicated frequency band of 5.855 - 5.925 GHz to vehicular communication. Numerous on road measurement campaigns have been conducted by joint consortium to evaluate the performance of Vehicle to Vehicle (V2V) communication around the world. However due to the scalability limitation of on road measurements, light-weight simulation tools are more widely implemented to gain general insights into Vehicle to Vehicle communication. Hence, the needs of simulation regarding evaluation on the performance of this technology have been aroused. In order to ensure the reliability of the simulation, propagation model on Vehicle to Vehicle communication should be accurate to have realistic results. In this paper, we conducted a survey of the available propagation models in urban, suburban and highway area.

Decreasing fossil energy sources require the search for alternative ways of individual transport. An important step is the electrification of the drive train and further vehicle components, enabling a total control of the overall energy flow while at the same time offering more degrees of freedom in optimizing the vehicle architecture. This paper describes an energy management system for battery electric vehicles. Main component of the system is a load balancing strategy which smoothens the energy flow and reduces high current fluctuations, reducing energy losses while increasing the battery lifetime. The first part of the paper describes a central ECU, which has been developed as a vehicle management unit. Driving strategy as well as the energy management strategy are implemented on this ECU. A bench test has been developed to test the ECU hardware as well as software in a laboratory environment.

This paper deals with the use of biometric methods of driver identification in the vehicle. It compares different methods and evaluates their possible uses in the vehicle. The methods of fingerprint, iris recognition and face recognition are dealt with in particular. The second part of the paper describes the implementation of a face recognition system in the vehicle. Important system components are a camera, preferably mounted in the instrument cluster or on the steering column, IR lighting and a computer unit that implements the necessary algorithm. The system observes the driver as he or she enters the vehicle, chooses the images suitable for identification from the image sequence and is able to re-recognize a person it has “seen” before. This paper focuses on integration in the vehicle with regard to the vehicle-specific environment and connection to the vehicle-specific procedures and requirements.

This paper discusses an interior camera system, monitoring the driver's state, to extend the comfort as well as the safety of future vehicles. The system consists of a CMOS-based camera, illumination units in the near infrared spectrum, and a control unit. The software is able to measure head position and orientation and thereby calculates the field of view of the driver. In addition, it measures the driver's eyelid opening and is able to detect micro-sleep events and to estimate the driver's state of vigilance. While detection of drowsiness and distraction are safety related issues, the system is also able to enhance the convenience of the vehicle. Head position and orientation are used to automatically adjust the headrest and to dynamically adjust the mirrors to ensure an optimal view for the driver.