School of Highway, Chang'an University, Xi'an, Shaanxi, China.
CCCC First Highway Consultants Co., Ltd, Xi'an, Shaanxi, China.
PLoS One. 2023 Oct 13;18(10):e0287489. doi: 10.1371/journal.pone.0287489. eCollection 2023.
Low-speed driving is an underestimated dangerous behavior that may cause safety issues, such as speed dispersion and traffic flow bottlenecks. To investigate the influence mechanism of low-speed driving behavior, this study constructed the low-speed specific model (LSSM) by extending theory of planned behavior (TPB). The LSSM incorporated two factors, namely, risk perception and behavior habit, into the standard TPB components (attitude, subjective norm, perceived behavioral control, and behavior intention). Web-based questionnaires were used to collect data from a valid sample of 374, of which males accounted for 50%. The participants were aged from 18 to 65 years (M = 35.40, SD = 0.88). The structural equation model was applied to calculate and validate the interrelationships among the components of LSSM. Results showed that the LSSM could explain the variance in low-speed driving behavior and behavior intention by 46% and 76%, respectively. Meanwhile, attitude (β = 0.52, p < 0.001) and behavior habit (β = 0.48, p < 0.001) had the strongest positive influence and prediction power over low-speed driving behavior, respectively, whereas subjective norm (β = 0.05, p > 0.01) and perceived behavioral control (β = -0.12, p > 0.01) showed few significant in influencing the intention. LSSM also showed that people who were sensitive to driving risk perception would avoid low-speed driving behaviors and attitudes. Our findings may provide theoretical support for interventions on low-speed driving behavior.
低速驾驶是一种被低估的危险行为，可能会导致安全问题，如速度分散和交通流瓶颈。为了研究低速驾驶行为的影响机制，本研究通过扩展计划行为理论（TPB）构建了低速特定模型（LSSM）。LSSM 将风险感知和行为习惯这两个因素纳入到标准 TPB 成分（态度、主观规范、感知行为控制和行为意向）中。本研究采用基于网络的问卷从有效样本中收集了 374 名参与者的数据，其中男性占 50%。参与者年龄在 18 至 65 岁之间（M = 35.40，SD = 0.88）。结构方程模型用于计算和验证 LSSM 各成分之间的相互关系。结果表明，LSSM 可以分别解释 46%和 76%的低速驾驶行为和行为意向的方差。同时，态度（β=0.52，p<0.001）和行为习惯（β=0.48，p<0.001）对低速驾驶行为具有最强的正向影响和预测能力，而主观规范（β=0.05，p>0.01）和感知行为控制（β=-0.12，p>0.01）对行为意向的影响较小。LSSM 还表明，对驾驶风险感知敏感的人会避免低速驾驶行为和态度。本研究结果可能为干预低速驾驶行为提供理论支持。
