Transportation Research Part F-Traffic Psychology and Behaviour最新文献_第10页

Do people believe that automated vehicle is the solution to impaired driving? insights from a statewide survey study 人们相信自动驾驶汽车是解决驾驶障碍的办法吗？来自全州调查研究的见解

IF 4.4 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2025-10-16 DOI: 10.1016/j.trf.2025.103411

Song Wang , Shujia Qiao , Zhixia Li , Wenjing Zhao , Hao Frank Yang , Guohui Zhang , Yifan Xu

The emerging Automated Vehicle (AV) technology has the potential to address impaired driving (i.e., driving under the influence of alcohol or drugs), a significant contributor to road fatalities. Previous research on impaired driving behavior has largely relied on simulation-based studies or public surveys. While simulation studies provide valuable insights from the perspective of driving behaviors, overlooking the possibility that impaired drivers may choose to take over voluntarily due to mistrust in AV technology. It is highly needed to explore such behavioral intentions through a statewide survey approach. In other words, prior to these empirical studies, a comprehensive understanding of public perception regarding AVs as a solution for impaired driving is essential. Existing public survey studies, however, tend to refrain from focusing on alcohol-impaired driving only and lack consideration of the level of automation involved. This gap presents challenges for AV policymakers, legislators, and robotaxi service providers seeking to implement AV technologies for driving-impaired individuals. To address the aforementioned issues, this research aims at (1) understanding the public acceptance of using AV to serve driving-impaired people and (2) exploring preferences for the level of automation in such services. An online, statewide survey study was conducted in Kentucky, USA, assessing the public’s opinions on whether AV technology can reduce the number of crashes due to impaired driving and which level of automation should be used to offer services for driving-impaired people. The results show that 70.8% of respondents believe AV technology can reduce crashes caused by impaired driving. Among them, 58.0% prefer riding in a Level 5 AV under such conditions. Structural Equation Modeling (SEM) was used to identify underlying factors, including socio-demographics, affordability, perceptions of AV benefits and concerns, and AV familiarity. The SEM analysis revealed that younger individuals, those with higher income, and those with greater familiarity with AVs are more likely to support Level 5 automation for assisting impaired drivers. Additionally, perceptions of increased driving freedom and lower safety concerns were positively associated with greater acceptance of AV technology for reducing impaired driving-related crashes.

These findings offer valuable implications and recommendations for AV manufacturers and policymakers to facilitate the implementation of AV technologies for impaired driving scenarios.

新兴的自动驾驶汽车（AV）技术有可能解决受损驾驶（即在酒精或药物影响下驾驶）问题，这是造成道路死亡的一个重要因素。以前对驾驶行为受损的研究主要依赖于基于模拟的研究或公众调查。虽然模拟研究从驾驶行为的角度提供了有价值的见解，但忽略了由于对自动驾驶技术的不信任，受损驾驶员可能会选择自愿接管的可能性。非常需要通过全州范围的调查方法来探索这种行为意图。换句话说，在进行这些实证研究之前，必须全面了解公众对自动驾驶解决方案的看法。然而，现有的公众调查研究往往不会只关注酒后驾驶，也没有考虑到所涉及的自动化水平。这一差距给寻求为驾驶障碍人士实施自动驾驶技术的自动驾驶政策制定者、立法者和自动驾驶出租车服务提供商带来了挑战。为了解决上述问题，本研究旨在(1)了解公众对使用自动驾驶汽车为驾驶障碍人士服务的接受程度，以及(2)探索公众对此类服务自动化程度的偏好。在美国肯塔基州进行了一项全州范围的在线调查研究，评估公众对自动驾驶技术是否可以减少因驾驶障碍而导致的车祸数量以及应该使用哪种自动化水平来为驾驶障碍人士提供服务的意见。调查结果显示，70.8%的受访者认为自动驾驶技术可以减少因驾驶障碍造成的交通事故。其中，58.0%的人更愿意在这种情况下乘坐Level 5自动驾驶汽车。使用结构方程模型（SEM）来确定潜在因素，包括社会人口统计学，可负担性，对AV利益和关注点的看法以及AV熟悉度。扫描电镜分析显示，年轻人、收入较高的人以及对自动驾驶汽车更熟悉的人更有可能支持5级自动驾驶，以帮助受损司机。此外，人们认为驾驶自由度的提高和安全问题的降低与自动驾驶技术的接受程度呈正相关，因为自动驾驶技术可以减少与驾驶相关的事故。这些发现为自动驾驶汽车制造商和政策制定者提供了有价值的启示和建议，以促进自动驾驶技术在受损驾驶场景中的实施。

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引用次数: 0

What if passengers experienced cyberattacks in a level 5 automated and connected shuttle? Impact of cyberattack type and contextual factors on perceived safety: A scenario-based study 如果乘客在5级自动连接的班车上遭遇网络攻击怎么办？网络攻击类型和情境因素对感知安全的影响：基于场景的研究

IF 4.4 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2025-10-15 DOI: 10.1016/j.trf.2025.103405

Emilie Ferriès , William Payre , Loïc Caroux , Amélie Rousseau , Céline Lemercier

Connected and Automated shuttles are increasingly accessible on public roads. These vehicles, will be characterized by extensive connectivity, enabling them to make driving decisions and share information. This connectivity will increase exposure to malicious attacks, which could lead to accidents, thereby causing psychological or physical harm to passengers. However, the effects of such attacks on passengers remain understudied. This study explored the effect of the type of cyberattack (target, consequences, alert message source) and contextual factors (social presence, traffic density) on perceived safety. A total of 420 participants were exposed to scenarios in which a character had a ride in an automated shuttle under different conditions and rated their level of perceived safety. Results highlighted that the target of the attack, consequences of the attack, alert message source and traffic density influenced perceived safety, except for social presence. Perceived safety scores were the greatest when the target of the attack was the passenger’s mobile phone, when the consequences of the attack were mild, when the alert message was provided by the vehicle’s antivirus, when the traffic density was low, with few vulnerable road users crossing the road. Cluster analyses highlighted three passenger profiles: alarmed, pondered and relaxed. This cluster formation was linked to sociodemographic characteristics, anxiety levels as car passengers and subjective cybersecurity knowledge. This research contributes to understanding passengers’ reactions to cyberattacks in public transport. Future studies should focus on cyberattacks’ impact on trust, acceptance, and on the specific information to provide passengers with during such events.

在公共道路上，联网和自动化的班车越来越多。这些车辆的特点将是广泛的连接，使它们能够做出驾驶决策并共享信息。这种连接将增加遭受恶意攻击的风险，这可能导致事故，从而对乘客造成心理或身体伤害。然而，此类袭击对乘客的影响仍未得到充分研究。本研究探讨了网络攻击类型（目标、后果、警报消息来源）和情境因素（社交存在、交通密度）对感知安全的影响。共有420名参与者被暴露在一个角色在不同条件下乘坐自动穿梭车的场景中，并对他们的感知安全水平进行评级。结果强调，攻击目标、攻击后果、警报消息来源和交通密度影响感知安全，但社会存在除外。当攻击目标是乘客的手机、攻击后果较轻、警报信息由车辆的防病毒系统提供、交通密度较低、很少有弱势道路使用者过马路时，感知安全得分最高。聚类分析突出了三种乘客特征：警觉、沉思和放松。这种集群的形成与社会人口特征、汽车乘客的焦虑水平和主观网络安全知识有关。这项研究有助于了解乘客对公共交通网络攻击的反应。未来的研究应该关注网络攻击对信任、接受度的影响，以及在此类事件中向乘客提供的具体信息。

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引用次数: 0

User acceptance of AI in transport: The case of SAE Level 3 Conditional Automated Driving 用户对人工智能在交通中的接受程度：以SAE 3级有条件自动驾驶为例

IF 4.4 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2025-10-13 DOI: 10.1016/j.trf.2025.103359

S. Nordhoff , S. Calvert , M. Hagenzieker , Y. M. Lee , N. Merat

This study applies an extended version of one of the most popular technology acceptance models, the Unified Theory of Acceptance and Use of Technology (UTAUT2), to predict user acceptance of SAE Level 3 conditional automated driving among more than 9,000 car drivers from nine European and non-European countries. We extend the model by two factors, trust and teaming, that we consider pivotal for user acceptance of conditional automated driving. We also investigate the factors impacting the determinants of acceptance and use of conditional automated driving, addressing a well-known gap in research. In this study we find that 40% of respondents did not intend to buy, and 39% of respondents did not express an intention to use conditional automated driving when available. 71% of respondents indicated a preference to stay engaged in the driving task to respond to requests from the car to resume manual control. The structural equation modeling analysis revealed that performance expectancy is the strongest predictor of driver’s behavioral intentions to use conditional automated driving, followed by trust and social influence. Contrary to common beliefs positioning trust as one of the most influential drivers of user acceptance of AVs, the influence of trust on behavioral intention to use conditional automated driving is small. The availability of facilitating conditions supporting the use conditional automated driving (e.g., knowledge, getting help from friends, family, or car dealers) has a small influence on the acceptance of AVs. We also found significant effects of the factors impacting the determinants of acceptance and use. The effect of performance expectancy on hedonic motivation is positive, suggesting that the perceived usefulness positively enhances the perceived enjoyment. Similarily, the effect of social influence on performance expectancy and trust is positive, suggesting the social network of the individual plays an important role in promoting positive beliefs about the effectiveness of the technology and trust in the technology. Access to participation in the questionnaire was limited to respondents with access to internet, which is why future research should be performed with respondents without internet accessibility to examine differences in attitudes and conditional automated driving acceptance between these internet-affine and less internet-affine groups.

这项研究应用了最流行的技术接受模型之一的扩展版本，即技术接受和使用统一理论（UTAUT2），以预测来自9个欧洲和非欧洲国家的9000多名汽车驾驶员对SAE 3级有条件自动驾驶的接受程度。我们通过信任和团队这两个因素扩展了模型，我们认为这两个因素对于用户接受有条件自动驾驶至关重要。我们还研究了影响有条件自动驾驶接受和使用决定因素的因素，解决了研究中一个众所周知的空白。在这项研究中，我们发现40%的受访者不打算购买，39%的受访者表示在可用的情况下没有使用条件自动驾驶的意图。71%的受访者表示，为了响应汽车恢复手动控制的请求，他们更愿意继续从事驾驶任务。结构方程模型分析显示，性能预期是驾驶员使用有条件自动驾驶行为意愿的最强预测因子，其次是信任和社会影响。通常认为信任是影响用户接受自动驾驶汽车的最重要因素之一，但与此相反，信任对使用有条件自动驾驶的行为意愿的影响很小。是否具备支持有条件自动驾驶的便利条件（例如，知识、从朋友、家人或汽车经销商那里获得帮助）对自动驾驶的接受程度影响不大。我们还发现了影响接受和使用决定因素的因素的显著影响。表现期望对享乐动机的影响为正，表明感知有用性对感知享受有正向促进作用。同样，社会影响对绩效期望和信任的影响是正向的，这表明个体的社会网络在促进对技术有效性的积极信念和对技术的信任方面起着重要作用。参与调查问卷的机会仅限于可以上网的受访者，这就是为什么未来的研究应该与无法上网的受访者一起进行，以检查这些互联网亲和性和互联网亲和性较低的群体之间的态度和条件自动驾驶接受度的差异。

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引用次数: 0

E-scooters and bicycles: A behavior comparison based on analysis of microscopic trajectory data 电动滑板车与自行车：基于微观轨迹数据分析的行为比较

IF 4.4 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2025-10-11 DOI: 10.1016/j.trf.2025.103402

Meng Zhang , Claudia Leschik , Nils Kornfeld , Michael Hardinghaus , Kay Gimm

Background

Recently, safety issues related to e-scooters have attracted attention. The behavior of e-scooter riders − such as using pedestrian infrastructures and wrong-way riding as well as their interactions with pedestrians, have raised concerns among people. The safety of e-scooters can be evaluated by comparing them to bicycles. Hence, the aim of the presented study is to reveal the differences between e-scooters and bicycles in terms of infrastructure usage, wrong-way behavior, and interactions with other road users.

Method

To compare the microscopic trajectories of e-scooters and bicycles, traffic was observed for three days at three locations in Berlin. Using image recognition technology, road users were identified, and their positions, as well as kinematic data such as speed and acceleration, were extracted.

Results

At all three locations, e-scooter riders (straight road: 16.3%, intersection: 50.7%, shared space: 67.7%) used pedestrian infrastructures (pedestrian paths and pedestrian crossings) more frequently than cyclists (straight road: 9.5%, intersection: 20.5%, shared space: 46.3%). Additionally, e-scooter riders (18.9%) rode more frequently in the wrong direction in comparison to cyclists (14.4%). With regard to the comparison of interactions with pedestrians, in head-on interactions on pedestrian crossings, e-scooter riders showed riskier behavior (higher speed and lower TTC) than cyclists. In crossing interactions, there was little difference between e-scooter riders and cyclists.

Discussion

The study discusses the impact of user characteristics on the illegal use of pedestrian infrastructure, wrong-way riding, and risky head-on interactions with pedestrians. In terms of practical applications, the effective guidance for users was suggested.

Conclusion

In this study, riding behavior of e-scooters and bicycles was compared based on the analysis of microscopic trajectory data. E-scooter riders exceeded cyclists in the illegal use of pedestrian infrastructure, wrong-way riding, and risky head-on interaction with pedestrians, suggesting a higher potential risk. The results of the study aim to inspire future research and safety policies.

最近，与电动滑板车有关的安全问题引起了人们的关注。电动滑板车使用者的行为——比如使用行人基础设施、逆行骑行以及与行人的互动——引起了人们的关注。电动滑板车的安全性可以通过与自行车的比较来评估。因此，本研究的目的是揭示电动滑板车和自行车在基础设施使用、错误行为和与其他道路使用者的互动方面的差异。方法为了比较电动滑板车和自行车的微观轨迹，在柏林的三个地点观察了三天的交通。利用图像识别技术对道路使用者进行识别，并提取其位置以及速度和加速度等运动学数据。结果在所有三个地点，电动滑板车骑行者（直道：16.3%，十字路口：50.7%，共享空间：67.7%）使用行人基础设施（步行路和人行横道）的频率高于骑自行车者（直道：9.5%，十字路口：20.5%，共享空间：46.3%）。此外，与骑自行车的人（14.4%）相比，骑电动滑板车的人（18.9%）更频繁地朝错误的方向骑行。在与行人的互动比较中，在人行横道上的正面互动中，电动滑板车骑手比骑自行车的人表现出更危险的行为（速度更快，TTC更低）。在交叉互动方面，骑电动滑板车的人和骑自行车的人几乎没有区别。该研究讨论了使用者特征对非法使用行人基础设施、错误骑行以及与行人正面互动的影响。在实际应用方面，对用户提出了有效的指导意见。结论本研究在微观轨迹数据分析的基础上，比较了电动滑板车和自行车的骑行行为。骑电动滑板车的人在非法使用行人基础设施、错误骑行、与行人正面碰撞等方面都超过了骑自行车的人，潜在风险更高。这项研究的结果旨在启发未来的研究和安全政策。

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引用次数: 0

Social comparison drives green transport switching: Travel satisfaction as the bridge 社会比较驱动绿色交通转换：出行满意度为桥梁

IF 4.4 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2025-10-11 DOI: 10.1016/j.trf.2025.103371

Hao Dong , Haslinda Hashim , Nitty Hirawaty Kamarulzaman

Transitioning from private car travel to green public transportation faces substantial challenges. Private cars satisfy basic travel needs and symbolize owner pride and socioeconomic status, creating psychological barriers to switching modes. This study investigates the influence of social comparison on travel mode switching intention. A theoretical framework is developed, and hypotheses are tested using structural equation modeling. Results show that social comparison does not directly affect switching intention. Instead, it exerts an indirect effect through travel satisfaction, which fully mediates the relationship. This mediating effect is significantly moderated by switching costs. Multi-group analysis reveals significant differences in the roles of switching costs, travel satisfaction, and its mediating effect across gender and private car ownership. The study provides the first empirical evidence that social comparison indirectly drives green transportation switching intention via travel satisfaction. The findings contribute a novel theoretical perspective on the psychological mechanisms underlying green travel promotion. Practical implications include guidance for policymakers and marketers to design targeted interventions that encourage adoption of green public transportation, thereby alleviating traffic congestion and improving environmental quality.

从私家车到绿色公共交通的转变面临着巨大的挑战。私家车满足了人们基本的出行需求，象征着车主的自豪感和社会经济地位，给人们的出行模式转换制造了心理障碍。本研究探讨社会比较对出行方式转换意愿的影响。建立了理论框架，并使用结构方程模型对假设进行了检验。结果表明，社会比较对交换意向没有直接影响。相反，它通过旅行满意度产生间接影响，充分中介关系。这种中介效应被转换成本显著地调节。多组分析显示，转换成本、出行满意度及其中介效应在性别和私家车拥有量之间存在显著差异。本研究首次提供了社会比较通过出行满意度间接驱动绿色交通转换意愿的实证证据。研究结果为研究绿色旅游促进的心理机制提供了新的理论视角。实际意义包括指导决策者和营销人员设计有针对性的干预措施，鼓励采用绿色公共交通，从而缓解交通拥堵，改善环境质量。

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引用次数: 0

Young drivers’ next day drink driving: The role of social norms 年轻司机酒后驾车的第二天：社会规范的作用

IF 4.4 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2025-10-10 DOI: 10.1016/j.trf.2025.103404

Michelle Nicolls, Lisa Buckley

Drink driving is a leading contributor to road-related crashes and injuries. There has been less attention on driving the following morning after drinking while potentially above the legal blood alcohol concentration limit (next day drink driving; ND-DD). Notably, factors associated with ND-DD remain unclear. As such, the current study explored demographic factors that have been previously associated with drink driving (e.g., gender, residential location), as well as the role of social norms (as measured through the Social Norm Theory). The current study aimed to (a) examine the relationship between younger drivers’ perceptions of others’ (i.e., friends and family) engagement in (descriptive norms), and approval of (injunctive norms), ND-DD on their engagement in the behaviour, and (b) examine whether such factors (i.e., descriptive and injunctive norms) explain the variance above demographic factors and harmful drinking behaviour. In total, 295 young drivers (M_age = 20.74 years; ranging 18–25 years) completed an online survey. Logistic regressions were employed to address the study aims. ND-DD was predicted by drinking at harmful levels, being a male, living in metropolitan locations, approving of ND-DD, and descriptive norms (related to friends only). It was also identified that engagement in ND-DD was more common compared to drink driving. This study presented an early attempt to explore the occurrence of ND-DD among younger drivers and potential predictors of the behaviour. Further research is needed to explore younger drivers’ understanding of, and experiences with ND-DD, which could lead to the development of countermeasures to reduce this behaviour.

酒驾是造成道路交通事故和伤害的主要原因。在可能超过法定血液酒精浓度限制（第二天酒后驾驶；ND-DD）的情况下，对第二天早上驾驶的关注较少。值得注意的是，与ND-DD相关的因素仍不清楚。因此，目前的研究探索了先前与酒驾相关的人口因素（例如，性别，居住地点），以及社会规范的作用（通过社会规范理论测量）。目前的研究旨在(a)检验年轻司机对他人（即朋友和家人）参与（描述性规范）的看法与对（禁令性规范）的认可之间的关系，ND-DD对他们参与行为的影响，以及(b)检验这些因素（即描述性和禁令性规范）是否解释了上述人口因素和有害饮酒行为的差异。共有295名年轻司机（年龄20.74岁，18-25岁）完成了在线调查。采用Logistic回归来解决研究目的。通过饮酒过量、男性、居住在大都市、认可ND-DD和描述性规范（仅与朋友有关）来预测ND-DD。研究还发现，与酒驾相比，ND-DD更常见。本研究提出了一项早期尝试，旨在探索年轻司机中ND-DD的发生情况以及该行为的潜在预测因素。需要进一步的研究来探索年轻司机对ND-DD的理解和经验，这可能会导致制定减少这种行为的对策。

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引用次数: 0

What affects driver’s vulnerability under spoofing cyberattacks at a connected intersection? – A mechanism analysis of how and why 是什么影响了司机在互联路口的欺骗网络攻击下的脆弱性？-如何和为什么的机制分析

IF 4.4 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2025-10-10 DOI: 10.1016/j.trf.2025.103403

Jun Guo , Zhixia Li , Yifan Xu , Heng Wei , Mohamed M. Ahmed , John E. Ash , Guohui Zhang , Yupeng Zhang , Kailai Wang

In the context of the Internet of Vehicles (IoV), cyberattacks targeting on onboard traffic signal displays can make drivers vulnerable and compromise traffic safety. However, it remains unclear why and how such cyberattacks increase driver vulnerability, specifically at connected intersections. This study identifies and explains factors contributing to driver vulnerability through questionnaire surveys and trajectory simulations. First, the Latent Class Model (LCM) is applied to analyze both datasets. The results show that under cyberattacks, drivers fall into two classes: Safe (54%) and Unsafe (46%). Considering both benchmark and attack scenarios, drivers are further divided into three types: Stable Safe Drivers (19%), Vulnerable Drivers (72%), and Stable Unsafe Drivers (9%). Second, Hypotheses testing identified six significant factors: age, driving experience, driving frequency, commuting time, average speed, and reaction time. Finally, three Structural Equation Models (SEMs) are built for the three types of drivers (each regarded as a binary variable). The results show that each factor affects driver types differently. Driving frequency (0.64) and age (−0.56) are the main factors contributing to vulnerability. Commuting time (−0.33) and reaction time (0.25) have a moderate impact, followed by average speed (0.17) and driving experience (−0.11). In addition, the analysis reveals the influence paths between these variables. By understanding the mechanism of driver vulnerability, this study provides a theoretical basis to improve driver safety under cyberattacks.

在车联网（IoV）的背景下，针对车载交通信号显示器的网络攻击会使驾驶员容易受到攻击，并危及交通安全。然而，目前尚不清楚这种网络攻击为什么以及如何增加司机的脆弱性，特别是在相互连接的十字路口。本研究通过问卷调查和轨迹模拟来识别和解释导致驾驶员脆弱性的因素。首先，应用潜类模型（Latent Class Model， LCM）对两个数据集进行分析。结果显示，在网络攻击下，司机分为两类：安全（54%）和不安全（46%）。考虑到基准和攻击场景，驱动程序进一步分为三类：稳定安全驱动程序（19%）、脆弱驱动程序（72%）和稳定不安全驱动程序（9%）。其次，假设检验发现年龄、驾驶经验、驾驶频次、通勤时间、平均车速和反应时间6个显著因素。最后，为三种类型的驱动程序（每个被视为一个二元变量）建立了三个结构方程模型（sem）。结果表明，各因素对驾驶员类型的影响不同。驾驶频率（0.64）和年龄（- 0.56）是影响脆弱性的主要因素。通勤时间（- 0.33）和反应时间（- 0.25）的影响中等，其次是平均速度（- 0.17）和驾驶经验（- 0.11）。此外，分析还揭示了这些变量之间的影响路径。通过了解驾驶员漏洞的形成机制，为提高网络攻击下驾驶员的安全性提供理论依据。

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引用次数: 0

A qualitative exploration of risky riding behaviors and road safety challenges among motorcycle taxi riders in Dar es Salaam 达累斯萨拉姆摩托车出租车乘客的危险驾驶行为和道路安全挑战的定性探索

IF 4.4 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2025-10-10 DOI: 10.1016/j.trf.2025.103399

Katondo Salvatory Nambiza , An Neven , Wilfred Gordian Kazaura , Kris Brijs

Motorcycle taxis are a critical mode of transport in many low- and middle-income countries, offering affordable and flexible mobility. However, they are disproportionately involved in road traffic crashes, often linked to risky riding behaviors. In Dar es Salaam (DSM), such behaviors persist despite regulatory measures, underscoring the necessity to understand their underlying causes.

This qualitative study investigates the factors contributing to risky riding behaviors among motorcycle taxi riders (MTRs) in DSM. Data were gathered through focus group discussions (FGDs) with riders and key informant interviews with enforcement and regulatory officials. Thematic analysis was employed to identify patterns in rider behaviors, risk perceptions, and enforcement challenges.

Riders reported frequently engaging in speeding, running red lights, overloading, and inadequate use of protective gear. Many perceived these actions as low-risk, driven by overconfidence, habitual risk-taking, and perceived absence of consequences. Economic pressures, peer influence, and customer expectations further motivated unsafe behaviors. Weak enforcement, limited road safety education, and inadequate infrastructure were also reported as contributing factors. Institutional challenges, including fragmented oversight, inconsistent penalties, and resource limitations, were found to hinder effective regulation and rider compliance.

The findings highlight the need for a coordinated strategy to improve motorcycle taxi safety. Key recommendations include structured rider training, consistent law enforcement, financial incentives, and targeted infrastructure upgrades. Strengthened collaboration among riders, authorities, and stakeholders is essential to raise risk awareness and build a culture of safety. These efforts can reduce crashes and support safer, more sustainable urban transport systems in rapidly growing cities like DSM.

在许多低收入和中等收入国家，摩托车出租车是一种重要的交通方式，提供负担得起的灵活机动性。然而，他们不成比例地参与道路交通事故，通常与危险的骑行行为有关。在达累斯萨拉姆（DSM），尽管采取了监管措施，但这种行为仍然存在，这凸显了了解其根本原因的必要性。本定性研究探讨了DSM中摩托车出租车乘客危险驾驶行为的影响因素。通过与乘客的焦点小组讨论（fgd）和与执法和监管官员的关键信息提供者访谈收集数据。采用主题分析来确定骑手行为、风险认知和执法挑战的模式。据报告，骑车者经常超速、闯红灯、超载以及没有充分使用防护装备。许多人认为这些行为是低风险的，是由过度自信、习惯性冒险和认为没有后果所驱动的。经济压力、同伴影响和顾客期望进一步激发了不安全行为。据报告，执法不力、道路安全教育有限和基础设施不足也是造成事故的因素。制度上的挑战，包括分散的监督、不一致的处罚和资源限制，阻碍了有效的监管和附加条款的遵守。研究结果强调需要采取协调一致的策略来提高摩的安全性。主要建议包括有组织的骑手培训、一致的执法、财政激励和有针对性的基础设施升级。加强乘客、当局和利益相关者之间的合作对于提高风险意识和建立安全文化至关重要。这些努力可以减少交通事故，并在DSM等快速发展的城市中支持更安全、更可持续的城市交通系统。

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引用次数: 0

Driver monitoring systems mitigate visual distraction only when drivers are adequately instructed and driving in assisted mode 驾驶员监控系统只有在驾驶员得到充分指导并在辅助模式下驾驶时才能减轻视觉干扰

IF 4.4 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2025-10-09 DOI: 10.1016/j.trf.2025.103396

Ina Koniakowsky , Yannick Forster , Josef F. Krems , Andreas Keinath

With the introduction of assisted driving, new challenges regarding visual attention have emerged, as drivers’ primary task has shifted from driving to monitoring. Driver Monitoring Systems (DMS) have been developed as a countermeasure for visual distraction. The DMS triggers warnings, prompting drivers to redirect their attention to the road when it considers them as distracted. To date, research on DMS is limited, particularly regarding the impact of driving mode (manual vs. assisted) on its effectiveness. Furthermore, it remains unclear whether the DMS is effective, when no further instructions on the system are given. Therefore, a driving simulator study was conducted to examine both the impact of the driving mode and the system instruction, as well as their interplay on drivers’ visual distraction. Participants (N = 125) drove either in manual or assisted mode, with the DMS being either inactive, active or active and instructed and glance metrics being measured in the initial and repeated trial. The proportion of long glances, number of glances and total glance duration served as dependent variables. Results show a significant effect of DMS, characterized by a reduced proportion of long glances and an increased number of glances, but only in assisted driving mode and when the DMS was instructed. There was no effect of the DMS in manual driving. Also, no effects of an active but uninstructed DMS regarding visual distraction were found. Therefore, the effectiveness of DMS is not inherently guaranteed but is contingent upon the driving mode and instruction.

随着辅助驾驶的引入，随着驾驶员的主要任务从驾驶转向监控，视觉注意力也出现了新的挑战。驾驶员监控系统（DMS）是一种针对视觉干扰的对策。DMS会触发警告，当它认为司机分心时，会提醒司机将注意力转移到道路上。迄今为止，对DMS的研究有限，特别是关于驾驶模式（手动与辅助）对其有效性的影响。此外，当没有给出关于该系统的进一步指示时，DMS是否有效仍不清楚。因此，本研究通过驾驶模拟器研究驾驶模式和系统指令对驾驶员视觉分心的影响，以及两者的相互作用。参与者（N = 125）在手动或辅助模式下驾驶，DMS在初始和重复试验中分别处于非活动、活动或活动状态，并测量指示和glance指标。长时间注视的比例、注视次数和总注视时间作为因变量。结果表明，只有在辅助驾驶模式和DMS有指示的情况下，DMS的作用才会显著，其特征是长时间注视的比例降低，注视的次数增加。DMS对手动驾驶没有影响。此外，没有发现主动但未指示的DMS对视觉分心的影响。因此，DMS的有效性并不是固有的保证，而是取决于驾驶模式和指导。

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引用次数: 0

Comparable effectiveness of risk awareness and perception training (RAPT) in young drivers with diverse socioeconomic status: A driving simulator study 风险意识和感知训练（RAPT）在不同社会经济地位的年轻司机中的可比有效性：一项驾驶模拟器研究

IF 4.4 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2025-10-08 DOI: 10.1016/j.trf.2025.103397

Jeffrey Glassman, Yusuke Yamani

Previous driving simulator and on road studies have shown that young drivers are poorer at anticipating road hazards than more experienced drivers. Risk Awareness and Perception Training (RAPT) is a training program shown to improve hazard anticipation skills among young drivers. A recent study suggested that RAPT may reduce crashes more effectively among drivers from low-socioeconomic status (SES) backgrounds than those from high-SES backgrounds, implying differential effects of RAPT on accelerating hazard anticipation skills. The present driving simulator experiment directly examined whether RAPT improves latent hazard anticipation differently in young drivers with various SES backgrounds in the United States. Fifty-two participants were randomly assigned to either an active or passive RAPT training group. The active RAPT group completed the full RAPT program that provided knowledge-based instruction on hazard anticipation, rehearsal of hazard anticipation skills, and feedback on errors. The passive RAPT group completed placebo training that included only the knowledge-based content without active practice or feedback. Participants drove eight driving scenarios in a high-fidelity driving simulator immediately before and after the completion of their assigned training. Results showed credible improvements in hazard anticipation performance for the active but not the passive group, suggesting that the active training method was crucial for learning. Low-SES drivers only showed improvements on hazard anticipation performance only after completing the active-training, whereas high-SES drivers improved following either program. These findings suggest that RAPT is generally effective across SES groups, but active training may be particularly important for enhancing hazard anticipation in low-SES young drivers.

以前的驾驶模拟器和道路研究表明，年轻司机在预测道路危险方面比经验丰富的司机差。风险意识和感知训练（RAPT）是一项旨在提高年轻司机风险预测技能的培训项目。最近的一项研究表明，低社会经济地位（SES）背景的驾驶员比高社会经济地位背景的驾驶员更有效地减少碰撞，这意味着RAPT在加速危险预测技能方面的不同效果。本驾驶模拟器实验直接考察了RAPT在美国不同社会经济背景的年轻驾驶员中对潜在危险预测的提高是否存在差异。52名参与者被随机分配到主动或被动RAPT训练组。积极的RAPT组完成了完整的RAPT项目，提供了基于知识的危险预测指导，演练了危险预测技能，并对错误进行了反馈。被动RAPT组完成安慰剂训练，只包括知识型内容，没有主动练习或反馈。参与者在完成指定训练之前和之后，在高保真驾驶模拟器中驾驶了八种驾驶场景。结果显示，主动组的危险预期表现有明显改善，而被动组则没有，这表明主动训练方法对学习至关重要。低社会经济地位的司机只有在完成主动训练后才表现出对危险预测的改善，而高社会经济地位的司机在两种训练后都有所改善。这些研究结果表明，RAPT在社会经济地位群体中通常是有效的，但积极的训练对于提高低社会经济地位的年轻司机的危险预期可能特别重要。

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引用次数: 0