Revisiting the level-of-service framework for pedestrian comfortability: Velocity depicts more accurate perceived congestion than local density

The evaluation of pedestrian comfortability is important for the construction and management of walkable spaces. Pedestrian level-of-service (LOS), which is mostly categorized by density, has been widely applied and is believed to be capable of indicating the comfortability of the crowd. However, there is a lack of evidence that physically measured LOS reflects psychological comfortability, let alone the comparison between the performances of different candidate indicators, including the velocity and different local densities. Here, we show that walking velocity depicts pedestrian perceived congestion more accurately than density. In our experiments on pedestrians in a room-egress scenario with an inner obstacle, we obtained objective physical trajectory data from video analysis as well as subjective perception data from a questionnaire survey. The performance of the velocity and four types of local densities in reproducing pedestrian perceptions were numerically evaluated. We found that the velocity outperformed the local density. The lower performance of local densities was mainly caused by the pedestrians located at the back of the crowd, who walked at lower velocities and perceived higher congestion, despite their lower local densities that would correspond to less crowdedness from a physical viewpoint. Besides, the perceived congestion of pedestrians was shown to be affected by the initial pedestrian positions at the crowd, the obstacle layout, and the pedestrians’ age and gender. Furthermore, we suggest that the larger the gap between the desired and actual velocities, the larger the extent of the perceived congestion. We expect that our findings will contribute to a more accurate evaluation of pedestrian comfortability, which could help improve the walkable spaces of various infrastructures.     

Investigating the effect of contextual factors on driving: An experimental study

Alongside human factors, contextual factors are believed to have an ongoing and complex impact on driving outcomes. However, how and to what extent the components of context influence driving outcomes (e.g. rule violations, crash, stress, fatigue) are far beyond full understanding. The purpose of this study is to explore the effects of weather condition, lighting condition and traffic density on driving outcomes. Thirty-six volunteers were enrolled to participate into a driving simulator-based experiment. Each participant was required to complete twelve trials of simulated driving under different sets of scenarios. Driving outcome was measured by five dependent variables: frequency of speeding, frequency of lane deviations, number of correct sign recognition, completion time and workload. The results showed the frequency of speeding was significantly affected by weather condition, lighting condition and traffic density. Lighting condition had a significant effect on number of correct sign recognition. Weather condition, lighting condition and traffic density had significant effects on task completion time. Weather condition and lighting condition had significant effects on driver’s workload. The implications of the results could help traffic safety professionals better understand the risk factors that may lead to human errors during driving. Practically, countermeasures could be inspired and developed to mitigate the adverse impacts brought by driving context to minimum.     

汉语歧义词加工中抑制机制的作用过程

两个实验探讨对汉语同形歧义词和同音歧义词不适当意义（与句子语境不一致）抑制的时间进程。被试为128名大学生,实验采用意义适合性判断任务,即要求被试又快又准地判断探测词的意义与刚呈现的句子意义是否相符合,探测词分别在ISI（interstimulus interval）为200和800ms时呈现。实验结果表明：（1）ISI为200ms时对同形歧义词的不适当次要意义的抑制尚未完成;但是对同音歧义词的不适当次要意义的抑制基本完成。（2）ISI为800ms时对同形歧义词的不适当次要意义的抑制基本完成;（3）即使延长加工时间,同形歧义词和同音歧义词的不适当主要意义还是难以被完全抑制。     

Learning to read facilitates the retrieval of phonological representations in rapid automatized naming: Evidence from unschooled illiterate,ex‐illiterate,and schooled literate adults

Rapid automatized naming (RAN) of visual items is a powerful predictor of reading skills. However, the direction and locus of the association between RAN and reading is still largely unclear. Here, we investigated whether literacy acquisition directly bolsters RAN efficiency for objects, adopting a strong methodological design, by testing three groups of adults matched in age and socioeconomic variables, who differed only in literacy/schooling: unschooled illiterate and ex‐illiterate, and schooled literate adults. To investigate in a fine‐grained manner whether and how literacy facilitates lexical retrieval, we orthogonally manipulated the word‐form frequency (high vs. low) and phonological neighborhood density (dense vs. spare) of the objects' names. We observed that literacy experience enhances the automaticity with which visual stimuli (e.g., objects) can be retrieved and named: relative to readers (ex‐illiterate and literate), illiterate adults performed worse on RAN. Crucially, the group difference was exacerbated and significant only for those items that were of low frequency and from sparse neighborhoods. These results thus suggest that, regardless of schooling and age at which literacy was acquired, learning to read facilitates the access to and retrieval of phonological representations, especially of difficult lexical items.     

Spatio-temporal accident analysis for accident prevention in relation to behavioral factors in driving: The case of South Anatolian Motorway

Analyzing the pattern of traffic accidents on road segments can highlight the hazardous locations where the accidents occur frequently and help to determine problematic parts of the roads. The objective of this paper is to utilize accident hotspots to analyze the effect of different measures on the behavioral factors in driving. Every change in the road and its environment affects the choices of the driver and therefore the safety of the road itself. A spatio-temporal analysis of hotspots therefore can highlight the road segments where measures had positive or negative effects on the behavioral factors in driving. In this paper 2175 accidents resulted in injury or death on the South Anatolian Motorway in Turkey for the years between 2006 and 2009 are considered. The network-based kernel density estimation is used as the hotspot detection method and the K-function and the nearest neighbor distance methods are taken into account to check the significance of the hotspots. A chi-square test is performed to find out whether temporal changes on hotspots are significant or not. A comparison of characteristics related driver attributes like age, experience, etc. for accidents in hotspots vs. accidents outside of hotspots is performed to see if the temporal change of hotspots is caused by structural changes on the road. For a better understanding of the effects on the driver characteristics, the accidents are analyzed in five groups based on three different grouping schemes. In the first grouping approach, all accident data are considered. Then the accident data is grouped according to direction of the traffic flow. Lastly, the accident data is classified in terms of the vehicle type. The resultant spatial and temporal changes in the accident patterns are evaluated and changes on the road structure related to behavioral factors in driving are suggested.