An integrated pen interface system was developed to allow effective Japanese text entry. It consists of sub-systems for handwriting recognition, contextual post-processing, and enhanced Kana-to-Kanji conversion. The recognition sub-system uses a hybrid algorithm consisting of a pattern matcher and a neural network discriminator. Special care was taken to improve the recognition of non-Kanji and simple Kanji characters frequently used in fast data entry. The post-processor predicts consecutive characters on the basis of bigrams modified by the addition of parts of speech and substitution of macro characters for Kanji characters. A Kana-to Kanji conversion method designed for ease of use with a pen interface has also been integrated into the system. In an experiment in which 2,900 samples of Kanji and non-Kanji characters were obtained from 20 subjects, it was observed that the original recognition accuracy of 83.7% (the result obtained by using the pattern matching recognizer) was improved to 90.7% by adding the neural network discriminator, and that it was further improved to 94.4% by adding the post-processor. The improved recognition accuracy for non-Kanji characters was particularly marked.

Energy conservation is one of the hot topics within the domain of traffic problems. It is well known that shortening the distance between vehicles reduces the aerodynamic drag of the lagging (or following) vehicle and leads to energy savings, which benefits the drivers. Recently, systems have been developed in which trucks or vehicles travel in a platoon with reduced headway from the preceding vehicle by using automated driving or driver assistance systems. The objective of the present study is to investigate how human factors, such as driving style, a driver's condition, or a driver's personal characteristics, influence the decision of a driver to close the gap with a preceding vehicle and obtain the benefit of aerodynamic drag reduction. We developed a realistic experimental paradigm for investigating the relationship between distance and several factors including the driver's personal characteristics and the size of preceding vehicle. Our experimental setup made use of real vehicles on a test track, as opposed to a vehicle simulator. We examined behavior of subjects that drove the following vehicle as well as subjects that sat in the passenger seat in the following vehicle. The experimental results demonstrate that all subjects attempted to reduce the distance to the preceding vehicle in order to gain the benefit. Based on the experimental and questionnaire results, we conclude that there are relationships between the category of subjects and subject's following distances.