Binocular coordination of the eyes during reading

Saccadic eye movements and fixations are the behavioral means by which we visually sample text during reading. Human oculomotor control is governed by a complex neurophysiological system involving the brain stem, superior colliculus, and several cortical areas [1, 2]. A very widely held belief among researchers investigating primate vision is that the oculomotor system serves to orient the visual axes of both eyes to fixate the same target point in space. It is argued that such precise positioning of the eyes is necessary to place images on corresponding retinal locations, such that on each fixation a single, nondiplopic, visual representation is perceived [3]. Vision works actively through a continual sampling process involving saccades and fixations [4]. Here we report that during normal reading, the eyes do not always fixate the same letter within a word. We also demonstrate that saccadic targeting is yoked and based on a unified cyclopean percept of a whole word since it is unaffected if different word parts are delivered exclusively to each eye via a dichoptic presentation technique. These two findings together suggest that the visual signal from each eye is fused at a very early stage in the visual pathway, even when the fixation disparity is greater than one character (0.29 deg), and that saccade metrics for each eye are computed on the basis of that fused signal.

Heuristic based evolution for the coordination of autonomous vehicles in the absence of speed lanes

The current state of the art in the planning and coordination of autonomous vehicles is based upon the presence of speed lanes. In a traffic scenario where there is a large diversity between vehicles the removal of speed lanes can generate a significantly higher traffic bandwidth. Vehicle navigation in such unorganized traffic is considered. An evolutionary based trajectory planning technique has the advantages of making driving efficient and safe, however it also has to surpass the hurdle of computational cost. In this paper, we propose a real time genetic algorithm with Bezier curves for trajectory planning. The main contribution is the integration of vehicle following and overtaking behaviour for general traffic as heuristics for the coordination between vehicles. The resultant coordination strategy is fast and near-optimal. As the vehicles move, uncertainties may arise which are constantly adapted to, and may even lead to either the cancellation of an overtaking procedure or the initiation of one. Higher level planning is performed by Dijkstra's algorithm which indicates the route to be followed by the vehicle in a road network. Re-planning is carried out when a road blockage or obstacle is detected. Experimental results confirm the success of the algorithm subject to optimal high and low-level planning, re-planning and overtaking.