In this paper, we propose an efficient vehicle trajectory prediction framework based on recurrent neural network. Basically, the characteristic of the vehicle's trajectory is different from that of regular moving objects since it is affected by various latent factors including road structure, traffic rules, and driver's intention. Previous state of the art approaches use sophisticated vehicle behavior model describing these factors and derive the complex trajectory prediction algorithm, which requires a system designer to conduct intensive model optimization for practical use. Our approach is data-driven and simple to use in that it learns complex behavior of the vehicles from the massive amount of trajectory data through deep neural network model. The proposed trajectory prediction method employs the recurrent neural network called long short-term memory (LSTM) to analyze the temporal behavior and predict the future coordinate of the surrounding vehicles. The proposed scheme feeds the sequence of vehicles' coordinates obtained from sensor measurements to the LSTM and produces the probabilistic information on the future location of the vehicles over occupancy grid map. The experiments conducted using the data collected from highway driving show that the proposed method can produce reasonably good estimate of future trajectory.

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Cold weather is one of the biggest challenges in establishing a large-scale microalgae culture facility in temperate regions. In order to develop a strain that is resistant to low temperatures and still maintains high photosynthetic efficiency, transgenic studies have been conducted targeting many genes. Early light-inducible proteins (ELIPs) located in thylakoid membranes are known to protect photosynthetic machinery from various environmental stresses in higher plants. An ELIP homolog was identified from Chlamydomonas reinhardtii and named ELIP3. The role of the gene was analyzed in terms of photosynthetic CO 2 assimilation under cold stress. Western blot results showed a significant accumulation of ELIP3 when the cells were exposed to cold stress (4 • C). High light stress alone did not induce the accumulation of the protein. Enhanced expression of ELIP3 helped survival of the cell under photo-oxidative stress. The influx of CO 2 to the photobioreactor induced strong accumulation of ELIP3, and enhanced survival of the cell under high light and cold stress. When the oxidative stress was reduced by adding a ROS quencher, TEMPOL, to the media the expression of ELIP3 was reduced. A knockdown mutant showed much lower photosynthetic efficiency than wild type in low temperature, and died rapidly when it was exposed to high light and cold stress. The overexpression mutant survived significantly longer in the same conditions. Interestingly, knockdown mutants showed negative phototaxis, while the overexpression mutant showed positive phototaxis. These results suggest that ELIP3 may be involved in the regulation of the redox state of the cell and takes important role in protecting the photosystem under photooxidative stress in low temperatures.

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