Impacts of different feedback features on driver behaviour: Findings from a multiphase naturalistic study

IF 5 2区 工程技术 Q1 PSYCHOLOGY, APPLIED
Armira Kontaxi, Apostolos Ziakopoulos, George Yannis
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引用次数: 0

Abstract

Rapid technological advances, especially in telematics and Big Data analytics, as well as the increasing penetration and use of information technology by drivers (e.g. smartphones), provide new capabilities for monitoring and analyzing driving behaviour. This paper examines the impact of driver feedback delivered through a smartphone application on driving behaviour risk indicators, within a 21-month multiphase naturalistic driving experiment involving a sample of 175 car drivers. First, a preliminary analysis utilizing summary statistics and Wilcoxon signed-rank test shed light upon the effects of upgraded feedback features on key risk indicators across experiment phases. Subsequently, Structural Equation Models (SEM) on a 73,869 trip dataset provided significant insights into how feedback mechanisms and exposure factors influence driving behaviours. Results indicate that the examined feedback mechanisms are effective in reducing the percentage of speeding time and harsh braking events, although there is an increase in harsh accelerations, which may require further refinement of the feedback system. The scorecard feature has the highest positive effect, indicating its crucial role in modifying driving habits, with gamification (competition and challenges) being the second most influential feedback mechanism. Regarding the exposure indicators, driving during the morning peak is associated with more unsafe behaviour (e.g., speeding, harsh accelerations), while driving during the afternoon peak exhibit fewer risky driving indicators (e.g., harsh braking). Additionally, results showcase strong positive correlations between speeding, harsh braking, and harsh accelerations highlighting the interconnected nature of risky driving behaviours. These findings may be beneficial for insurance companies, fleet management applications, and policymakers, enabling them to leverage results to improve traffic safety and driver behaviour.
不同反馈特征对驾驶员行为的影响:一项多阶段自然主义研究的结果
快速的技术进步,特别是远程信息处理和大数据分析,以及司机对信息技术(如智能手机)的日益普及和使用,为监测和分析驾驶行为提供了新的能力。本文对175名汽车司机进行了为期21个月的自然驾驶实验,研究了通过智能手机应用程序提供的驾驶员反馈对驾驶行为风险指标的影响。首先,利用汇总统计和Wilcoxon sign -rank检验进行初步分析,揭示了各阶段反馈特征升级对关键风险指标的影响。随后,基于73,869次出行数据集的结构方程模型(SEM)为反馈机制和暴露因素如何影响驾驶行为提供了重要见解。结果表明,所研究的反馈机制在减少超速时间和严重制动事件的百分比方面是有效的,尽管严重加速事件有所增加,这可能需要进一步改进反馈系统。记分卡功能的积极效应最高,表明其在改变驾驶习惯方面发挥了至关重要的作用,而游戏化(竞争和挑战)是第二大影响最大的反馈机制。就暴露指标而言,在早高峰驾驶与更多的不安全行为(如超速、剧烈加速)相关,而在下午高峰驾驶表现出较少的危险驾驶指标(如剧烈刹车)。此外,研究结果显示超速、急刹车和急刹车之间存在强烈的正相关关系,突出了危险驾驶行为的内在联系。这些发现可能对保险公司、车队管理应用程序和政策制定者有益,使他们能够利用这些结果来改善交通安全和驾驶员行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.60
自引率
14.60%
发文量
239
审稿时长
71 days
期刊介绍: Transportation Research Part F: Traffic Psychology and Behaviour focuses on the behavioural and psychological aspects of traffic and transport. The aim of the journal is to enhance theory development, improve the quality of empirical studies and to stimulate the application of research findings in practice. TRF provides a focus and a means of communication for the considerable amount of research activities that are now being carried out in this field. The journal provides a forum for transportation researchers, psychologists, ergonomists, engineers and policy-makers with an interest in traffic and transport psychology.
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