Modeling Drivers' Visual Attention Allocation While Interacting With In-Vehicle Technologies Export

@article{citeulike:898299, abstract = {In 2 experiments, the authors examined how characteristics of a simulated traffic environment and in-vehicle tasks impact driver performance and visual scanning and the extent to which a computational model of visual attention (SEEV model) could predict scanning behavior. In Experiment 1, the authors manipulated task-relevant information bandwidth and task priority. In Experiment 2, the authors examined task bandwidth and complexity, while introducing infrequent traffic hazards. Overall, task priority had a significant impact on scanning; however, the impact of increasing bandwidth was varied, depending on whether the relevant task was supported by focal (e.g., in-vehicle tasks; increased scanning) or ambient vision (e.g., lane keeping; no increase in scanning). The computational model accounted for approximately 95\% of the variance in scanning across both experiments.}, author = {Horrey, William J. and Wickens, Christopher D. and Consalus, Kyle P.}, citeulike-article-id = {898299}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/S1076-898X(06)60239-6}, citeulike-linkout-1 = {http://www.sciencedirect.com/science/article/B6X06-4KHJK1T-1/2/84e61339de2a2f80aa60386a7e046ce6}, doi = {10.1016/S1076-898X(06)60239-6}, journal = {Journal of Experimental Psychology: Applied}, keywords = {attention, driving, fixation, simulation}, month = {June}, number = {2}, pages = {67--78}, posted-at = {2006-10-15 17:10:33}, priority = {3}, title = {Modeling Drivers' Visual Attention Allocation While Interacting With In-Vehicle Technologies}, url = {http://dx.doi.org/10.1016/S1076-898X(06)60239-6}, volume = {12}, year = {2006} }

TY - JOUR ID - citeulike:898299 L3 - citeulike-article-id:898299 N2 - In 2 experiments, the authors examined how characteristics of a simulated traffic environment and in-vehicle tasks impact driver performance and visual scanning and the extent to which a computational model of visual attention (SEEV model) could predict scanning behavior. In Experiment 1, the authors manipulated task-relevant information bandwidth and task priority. In Experiment 2, the authors examined task bandwidth and complexity, while introducing infrequent traffic hazards. Overall, task priority had a significant impact on scanning; however, the impact of increasing bandwidth was varied, depending on whether the relevant task was supported by focal (e.g., in-vehicle tasks; increased scanning) or ambient vision (e.g., lane keeping; no increase in scanning). The computational model accounted for approximately 95% of the variance in scanning across both experiments. IS - 2 JF - Journal of Experimental Psychology: Applied EP - 78 TI - Modeling Drivers' Visual Attention Allocation While Interacting With In-Vehicle Technologies VL - 12 SP - 67 KW - attention KW - driving KW - fixation KW - simulation AU - Horrey, William AU - Wickens, Christopher AU - Consalus, Kyle PY - 2006/06// UR - http://dx.doi.org/10.1016/S1076-898X(06)60239-6 ER -