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This paper proposes how to develop an autonomous vehicle for factory and/or storehouse use. Where the geometric arrangement changes frequently due to the turnover of the cargo. We apply the sensor fusion technique by use of the Omni directional image sensor and laser radar generate the map of such situations. We propose a new update algorithm called SMT (Shift Matching Transform) that obtains region segments with trusted semi-real-time geometric map. We demonstrate how to determined the absolute position of the vehicle by the position information of arbitrary wall. Experimental results on the corridor, Shows the semi-real-time map reconstruction with enough validity.

An automatically guided vehicle by vision that recognizes the two white guidelines has been developed. The vehicle can run on a mildly bumpy grass course like as golf course up to 3 km/hour, staying in between two white lines with span of 3m to 3.6m avoiding obstacles within lanes. In this paper, the construction of the vehicle, the sensing strategy, the control algorithm, as well as practical aspects of the implementation are described. Employment of 1D image sensor which detects two white lanes yields the remarkable feature of the proposed system. The advantage of 1-D image sensor is the simplicity as well as significant reduction of the task for image processing in comparison with the conventional 2D-camera vision. Through the actual experiments at International Ground Robotics Competition '97, which held at Oakland University in June, we demonstrated the superior performance compared with conventional 2D vision type vehicles.

The airbag systems in the first generation had been developed and are equipped in real automobiles. This paper is aimed at describing a new airbag scheme that might be categorized in the 1.5 generation. The airbag system always needs some delay time between the triggering and complete expanding. The existence of the delay time is the main cause of difficulty for accurate airbag triggering. The predictive airbag expanding algorithm that compensates the delay time was proposed and the validity was examined in the first generation development. Development of the 1.5 generation airbag systems with the higher performance are our next problem. Airbag equipped in automobiles must receive driver's body at the optimal timing when collision by which the effect of airbag is extremely improved. The more accurate predictive airbag system is required.

The advanced safe driving of vehicles have fully depended on the development of the safe driving systems. The final strategy must take the drivers skill into account. This paper describes a method to detect and evaluate driving skill. We present a new system to measure the curvature of driving loci against the distance by using speed and rate gyro sensors and present a method to extract the driving curvature from that of road itself. It includes the information of drivers' skill by which the driving conditions can be evaluated.

An airbag upon collision of automobiles must finish expanding at the time when the driver's body arrives at the surface of the expanded airbag from the normal position and it must receive the body softly. Either early or late expansion reduce the effect. Determination of the optimal timing for trigger the airbag is quite important. But it is a difficult job, due to the time delay in the bag filling with the gas after collision. This paper focuses on the issue of the airbag technology to how to find the optimal trigger timing and presents a new and straightforward algorithm to determine the timing by introducing the concept of the prediction. The algorithm first predicts how the driver's body will move in the future time for a time equivalent to the delay time and triggers the airbag by the predicted information so that it can compensate the delay by the airbag operation.

This paper describes a new method of measuring the absolute speed of moving objects such as people who are walking or running, running animals, vehicles, sailing boats and the like. The method estimates speed using the time delay between spatial values (patterns) detected by the front and rear sensors which are separately disposed on an object and aligned in the direction of movement. It is known that the electric field intensity of radio waves in the VHF/UHF range exhibit a spatial periodic pattern due to the multi-pass fading phenomenon. It is also known that this phenomenon is a source of noise in automotive telecommunications. In experiments we make use this pattern for speed measurement and investigate if the pattern can be used to provide a spatial value which permits the estimation of the speed of the above mentioned types of objects.