Driving on freeways is a daily activity across the world. Poor driving performance on freeways can cause severe injuries and deaths. However, few studies have examined whether and to what extent different types of freeway landscapes influence driving performance. A simulated driving task was designed to measure the impacts of six types of freeway landscape on 33 participants’ driving performance. Each participant completed a driving experiment with six blocks of 90-minute driving sessions in a random sequence. During the experiment, participants’ driving performance was measured through eight parameters. A set of repeated-measure one-way ANOVA analyses show that landscapes with three-dimensional branch and foliage (shrub & tree) were generally more beneficial for driving performance than barren (concrete-paved ground) or low green landscape conditions (turf). Furthermore, a repeated-measure two-way ANOVA analysis of four conditions with vertical green foliage (two shrub and two tree conditions) showed moderate levels of greenness and complexity are optimal for driving performance.

在高速公路上开车是世界各地的日常活动。高速公路上的不良驾驶性能可能导致严重的伤害和死亡。但是，很少有研究检查不同类型的高速公路景观是否以及在多大程度上影响驾驶性能。设计了模拟驾驶任务，以测量六种类型的高速公路景观对33名参与者的驾驶表现的影响。每个参与者以随机顺序完成了六个块90分钟的驾驶课程的驾驶实验。在实验过程中，通过八个参数测量了参与者的驾驶表现。一组重复测量的单向方差分析表明，具有三维分支和叶子（灌木和 树木）通常比贫瘠（混凝土铺成的地面）或低矮的绿色景观（草皮）对驾驶性能更有利。此外，对垂直绿叶的四个条件（两个灌木和两个树的条件）进行的重复测量双向ANOVA分析表明，中等水平的绿色度和复杂度对于驾驶性能而言是最佳的。