高速机车司机心理选拔指标研究

目的从安全驾驶适应性方面研究高速机车司机应具备的心理素质。方法根据高速列车机车驾驶特性,提出心理选拔指标并应用于现场,通过现场对直达和特快机车司机的测量及应用从而确立高速机车司机应具备的心理素质指标。结果实验机车司机413名,年龄组在39岁以下和40岁以上机车司机有明显不同：39岁以下较40岁以上机车司机的作业能力和反应速度及注意分配、集中、转移等方面的能力均明显加快（P〈0.05,P〈0.01）;机车司机的认知能力受文化程度的影响（P〈0.01）,其中,四数和计算是初中与高中以上文化程度之间有极显著性差异（P〈0.01）,比较刻度、按规律检数是高中以下和大专之间存在着极显著性差异（P〈0.01）,即具备一定文化程度的机车司机其计算速度和操作技能都明显较好。指标间的相关矩阵分析存在极密切关系（r=0.16-0.59,P〈0.01）;同期效标检验各指标的相关效度为0.14-0.33（P〈0.05,P〈0.01）,组合分相关效度为0.315（P〈0.01）;验证预测合格符合率为91.96%,预测淘汰符合率为23.89%。

Reseach of Psychological Selection Index for Locomotive Driver in High-speed Train

Objective： To sdudy the required psychological quality of locomotive driver in high-speed train from adaptability of safe driving. Methods： Psychological selection index were brought forward and applied to filed test according to driving characteristic of high-speed train. The required psychological quality of locomotive driver in high-speed train were established after tested and applied in the filed aimed at train locomen and red ball locomen. Results ： 413 locomen were sdudied. Compered with locomen above 40 years of age, the ability of locomen below 39 years old showed a significant well on management skill, response, attention distribution, attention concentration and transfer etc. （P 〈 0.05 or P 〈 0.01）. The cognitive performance were significantly different in the distributions of different degree of education. Senior high school degree or above locomen showed a significant well on four number aristhmetic（ P 〈 0.01）. And there is a significant score of comparing simulated scales and regularity array in junior college degree or above locomen （ P 〈 0.01 ）. These showed that locomen with higher degree of education seemed to have a better calculating speed and management skill. The correlation matrix analysis of index showed a significant difference between each other（ P 〈 0.01）. The correlation validity of index via the test of concurrent validity was 0.14 - 0.33（ P 〈 0.05 or P 〈 0.01）. And the correlation validity of combined score was 0.315（ P 〈 0.01 ）. The hit rate of predicted pass was 91.96%, while the hit rate of predicted fail was 23.89%.