A New Method for Target Object Selection for ACC System Based on Analysis of Vehicle Trajectories

Author(s):  
Shifeng Geng ◽  
Jian Wu ◽  
Weiwen Deng ◽  
Yang Zhao
Author(s):  
Rebecca L. Monk ◽  
Lauren Colbert ◽  
Gemma Darker ◽  
Jade Cowling ◽  
Bethany Jones ◽  
...  

Abstract Background Theory of mind (ToM), the ability to understand that others have different knowledge and beliefs to ourselves, has been the subject of extensive research which suggests that we are not always efficient at taking another’s perspective, known as visual perspective taking (VPT). This has been studied extensively and a growing literature has explored the individual-level factors that may affect perspective taking (e.g. empathy and group membership). However, while emotion and (dis)liking are key aspects within everyday social interaction, research has not hitherto explored how these factors may impact ToM. Method A total of 164 participants took part in a modified director task (31 males (19%), M age = 20.65, SD age = 5.34), exploring how correct object selection may be impacted by another’s emotion (director facial emotion; neutral × happy × sad) and knowledge of their (dis)likes (i.e. director likes specific objects). Result When the director liked the target object or disliked the competitor object, accuracy rates were increased relative to when he disliked the target object or liked the competitor object. When the emotion shown by the director was incongruent with their stated (dis)liking of an object (e.g. happy when he disliked an object), accuracy rates were also increased. None of these effects were significant in the analysis of response time. These findings suggest that knowledge of liking may impact ToM use, as can emotional incongruency, perhaps by increasing the saliency of perspective differences between participant and director. Conclusion As well as contributing further to our understanding of real-life social interactions, these findings may have implications for ToM research, where it appears that more consideration of the target/director’s characteristics may be prudent.


2019 ◽  
Vol 30 (3) ◽  
pp. 1779-1796 ◽  
Author(s):  
Mikiko Kadohisa ◽  
Kei Watanabe ◽  
Makoto Kusunoki ◽  
Mark J Buckley ◽  
John Duncan

Abstract Complex cognition is dynamic, with each stage of a task requiring new cognitive processes appropriately linked to stimulus or other content. To investigate control over successive task stages, we recorded neural activity in lateral frontal and parietal cortex as monkeys carried out a complex object selection task, with each trial separated into phases of visual selection and learning from feedback. To study capacity limitation, complexity was manipulated by varying the number of object targets to be learned in each problem. Different task phases were associated with quasi-independent patterns of activity and information coding, with no suggestion of sustained activity linked to a current target. Object and location coding were largely parallel in frontal and inferior parietal cortex, though frontal cortex showed somewhat stronger object representation at feedback, and more sustained location coding at choice. At both feedback and choice, coding precision diminished as task complexity increased, matching a decline in performance. We suggest that, across successive task steps, there is radical but capacity-limited reorganization of frontoparietal activity, selecting different cognitive operations linked to their current targets.


2013 ◽  
Vol 25 (3) ◽  
pp. 538-544 ◽  
Author(s):  
Kazuyuki Nagase ◽  
◽  
Yasumichi Aiyama

In this paper, we propose a new method of grasp planning for a manipulator with a parallel jaw gripper in obstacle environment. We consider collision avoidance as a problem of motion planning in obstacle environments. In general, however, a redundant degree of freedom (DOF) is required to avoid obstacle and to grasp. In our proposal, we pay attention to redundant DOF in a grasping pose. Using redundant DOF in a grasping pose, a manipulator can avoid obstacles and grasp a target object. It does not require any redundant manipulators.


Author(s):  
Jendrik Seipp

Pattern databases are the foundation of some of the strongest admissible heuristics for optimal classical planning. Experiments showed that the most informative way of combining information from multiple pattern databases is to use saturated cost partitioning. Previous work selected patterns and computed saturated cost partitionings over the resulting pattern database heuristics in two separate steps. We introduce a new method that uses saturated cost partitioning to select patterns and show that it outperforms all existing pattern selection algorithms.


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