Transportation Research Part F-Traffic Psychology and Behaviour最新文献_第6页

Willingness to utilize autonomous vehicles following accidents: A fresh perspective from mixed-methods research 事故发生后使用自动驾驶汽车的意愿：混合方法研究的新视角

IF 3.5 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2024-10-09 DOI: 10.1016/j.trf.2024.09.022

Yongjiang Zhou , Hanying Guo , Luping Tang , Yuxin Deng , Hongguo Shi

While autonomous vehicles (AVs) show promise, several challenges remain in their implementation. In this regard, adverse incidents can alter public perceptions and acceptance of this technology. This study used latent Dirichlet allocation (LDA), a random-parameters ordered probit model and a structural causal model to investigate public concerns regarding AV incidents and their influence on the public’s willingness to adopt AVs. Using LDA to analyse mass media data, this study identified seven latent variables related to AV incidents. To consider changes in public attitudes following incidents, attitude was introduced as a new latent variable. The impact of various variables on public willingness to use AVs was analysed using a random-parameters ordered probit model. The findings indicated that perceived trust, attitude, perceived risk, mass media, perceived value, brand effect, privacy concerns and policies and regulations are crucial factors influencing AV adoption. Subsequently, a causal structure model was developed to determine the inter-relationships between variables. The model indicated that policy interventions increased public willingness to adopt AVs by 28%, suggesting that policymakers’ interventions help create an early market for AVs. In addition, good branding and mass media campaigns influence the public’s psychological characteristics and encourage the use of AVs. These findings hold crucial implications for mitigating the negative impacts of adverse incidents, fostering public acceptance and providing valuable insight for theoretical understanding and practical implementation of AV usage.

虽然自动驾驶汽车（AVs）前景广阔，但在其实施过程中仍存在一些挑战。在这方面，负面事件会改变公众对这一技术的看法和接受程度。本研究使用潜狄利克特分配（LDA）、随机参数有序概率模型和结构因果模型来调查公众对自动驾驶汽车事件的担忧及其对公众采用自动驾驶汽车意愿的影响。本研究利用 LDA 分析大众媒体数据，确定了与自动驾驶汽车事件相关的七个潜在变量。为了考虑事件发生后公众态度的变化，态度被引入为一个新的潜变量。使用随机参数有序概率模型分析了各种变量对公众使用电动汽车意愿的影响。研究结果表明，感知信任、态度、感知风险、大众传媒、感知价值、品牌效应、隐私问题和政策法规是影响人们采用自动驾驶汽车的关键因素。随后，建立了一个因果结构模型，以确定变量之间的相互关系。模型显示，政策干预使公众采用自动驾驶汽车的意愿提高了 28%，这表明政策制定者的干预有助于为自动驾驶汽车创造早期市场。此外，良好的品牌推广和大众媒体宣传也会影响公众的心理特征，鼓励他们使用自动驾驶汽车。这些研究结果对减轻负面事件的负面影响、促进公众接受度具有重要意义，并为从理论上理解和实际使用自动驾驶汽车提供了有价值的见解。

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引用次数: 0

Beyond private-sphere pro-environmental action: Explaining shared mobility using the Theory of Planned Behavior and solidarity-oriented variables 超越私人领域的环保行动：利用计划行为理论和团结导向变量解释共享流动性

IF 3.5 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2024-10-07 DOI: 10.1016/j.trf.2024.09.014

Nadine Richter , Marcel Hunecke , Paula Blumenschein

Shared mobility behaviors can decrease the negative environmental effects of the transport sector, yet they have received limited attention. Models such as the Theory of Planned Behavior (TPB) have been widely used to explain primarily individual private-sphere pro-environmental behaviors (PEB). However, as shared mobility behaviors are not completely limited to the private sphere but require social cooperation, solidarity-focused variables that emphasize social interactions may meaningfully complement the TPB variables. In three university samples (Study 1: N=261, Study 2: N=1411; Study 3: N=544), we tested relationships between the TPB variables and shared mobility, and whether solidarity-oriented variables are relevant predictors of shared mobility beyond the TPB variables. The analyses confirmed attitude (

β

= 0.38 − 0.59, p < 0.001) and social norm (

β

= 0.17 − 0.43, p < 0.001) as predictors of shared mobility intention. Furthermore, the solidarity-oriented variables universalism (

β

= 0.09 − 0.18, p < 0.05) as well as specific collective efficacy (

β

= 0.08 − 0.10, p < 0.05) and opinion-based social identification (

β

= 0.18, p < 0.001) positively predicted shared mobility intention. Psychological variables showed no consistent connection to self-reported shared mobility behaviors in logistic regressions. We discuss the scope of solidarity-oriented variables that need social cooperation to complementarily explain PEB beyond the private sphere.

共享交通行为可以减少交通部门对环境的负面影响，但它们受到的关注却很有限。计划行为理论（TPB）等模型已被广泛用于解释主要是个人的私人环境行为（PEB）。然而，由于共享移动行为并不完全局限于私人领域，而是需要社会合作，因此强调社会互动的团结变量可能会对 TPB 变量形成有意义的补充。在三个大学样本中（研究 1：261 人；研究 2：1411 人；研究 3：544 人），我们测试了 TPB 变量与共享流动之间的关系，以及团结导向变量是否是 TPB 变量之外的共享流动的相关预测因素。分析结果证实，态度（β = 0.38 - 0.59, p < 0.001）和社会规范（β = 0.17 - 0.43, p < 0.001）是共享流动意向的预测因素。此外，以团结为导向的普遍主义变量（β = 0.09 - 0.18, p <0.05）、特定的集体效能（β = 0.08 - 0.10, p <0.05）和基于观点的社会认同（β = 0.18, p <0.001）对共同流动意向有积极的预测作用。在逻辑回归中，心理变量与自我报告的共同流动行为没有一致的联系。我们讨论了以团结为导向的变量的范围，这些变量需要社会合作来补充解释私人领域以外的 PEB。

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引用次数: 0

The Predictive Role of visual attention bias in aggressive driving decisions among violation-involved drivers on attitudes of right-of-way 视觉注意力偏差在违规驾驶者做出攻击性驾驶决策时对路权态度的预测作用

IF 3.5 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2024-10-04 DOI: 10.1016/j.trf.2024.09.024

Jinfei Ma , Hao Chen , Yi Cui , Tingru Zhang

This study, based on dual-process theory, explores the aggressive driving decision-making characteristics and cognitive processing of violation-involved drivers in right-of-way infringement scenarios. It aims to identify an eye-movement indicator that can predict drivers’ prosocial behaviors. The study recruited 75 drivers aged 19–58 years, who completed a video-based aggressive driving decision-making test and the Driver Attitudes of Right-of-way Questionnaire (DARQ). The results indicate that age moderates the relationship between violation history and visual attentional bias. Younger drivers with a history of violations exhibit an attentional bias towards aggressive words, whereas older drivers do not. After controlling for age, violation-involved drivers demonstrated a higher rate of aggressive decision-making, especially in situations with very short lane-change time headway. Visual attentional bias towards aggressive words can effectively predict positive emotions in attitudes towards the right-of-way. This suggests that early eye movement indicators during the driving decision-making process represent a form of socioemotional characteristic. The more positive the driver’s right-of-way attitude, the stronger their prosocial behavior and the weaker their intuitive impulsiveness during the early cognitive processing stages of driving decision-making. This indicates that the driving decision-making eye-movement assessment paradigm is an objective and effective method for evaluating drivers’ pro-sociality.

本研究以双过程理论为基础，探讨了在侵犯路权情景下，违规驾驶者的攻击性驾驶决策特征和认知过程。其目的是找出一种能预测驾驶员亲社会行为的眼动指标。研究招募了 75 名年龄在 19-58 岁之间的驾驶员，他们完成了基于视频的侵犯性驾驶决策测试和驾驶员路权态度问卷（DARQ）。结果表明，年龄调节了违章史与视觉注意偏差之间的关系。有违章记录的年轻驾驶员会表现出对攻击性词语的注意偏向，而年龄较大的驾驶员则不会。在控制了年龄因素后，有违章记录的驾驶员做出攻击性决策的比例更高，尤其是在变道时间很短的情况下。对攻击性词语的视觉注意偏差可以有效预测对路权态度的积极情绪。这表明，驾驶决策过程中的早期眼动指标代表了一种社会情感特征。在驾驶决策的早期认知处理阶段，驾驶员的右侧通行态度越积极，其亲社会行为就越强烈，直觉冲动性就越弱。这表明驾驶决策眼动评估范式是评价驾驶员亲社会性的一种客观有效的方法。

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引用次数: 0

Road-crossing behavior and safety of pedestrians facing autonomous vehicles with an acceleration indicator eHMI in VR traffic flow 在 VR 交通流中使用加速度指示器 eHMI 面对自动驾驶汽车时行人的过路行为和安全问题

IF 3.5 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2024-10-04 DOI: 10.1016/j.trf.2024.09.023

Yuanming Song , Xing Chen , Jingyu Zhang , Jingyi Tian , Liwen Zhang , Guojie Ma , Xiangling Zhuang

To support pedestrian road-crossing behavior in the presence of autonomous vehicles (AVs), we propose a novel external Human-Machine Interface (eHMI) that enhances the vehicle’s inherent motion cues, which pedestrians already use in traditional traffic. Based on the Beta Movement, the eHMI design consists of light bands with multiple arrows moving forward or backward to indicate the vehicle’s accelerating or decelerating motion state. We measured pedestrians’ behavior and perceived safety when faced with AVs equipped with this acceleration indicator eHMI in a virtual reality (VR) street scene, where pedestrians had road-crossing tasks and vehicles did not always yield. We found that pedestrians exhibited crossing behavior according to the motion state of the oncoming vehicle. They almost always crossed if the vehicle yielded but considered the gap size to cross when it did not. With the acceleration indicator eHMI, they crossed more frequently if the vehicle yielded, yet less frequently if it did not. Although risky crossings could not be fully prevented, pedestrians crossed faster and maintained larger safety margins when the non-yielding vehicle used this eHMI. Additionally, pedestrians started to cross earlier when the eHMI indicated the vehicle’s decelerating state. Regarding pedestrians’ perceived safety, the eHMI did not increase perceived safety for decelerating vehicles but effectively decreased the perceived safety for accelerating vehicles. These results demonstrate the potential of enhancing vehicles’ inherent motion cues with eHMIs, but also imply that making vehicles’ motion state more apparent might not simply increase pedestrians’ perceived safety. Overall, a trade-off seems to exist that it is pedestrians’ sense of unsafety that leads to their safe road-crossing behavior. Suggestions for future research and VR experiments were also discussed.

为了支持行人在自动驾驶汽车（AV）面前的过马路行为，我们提出了一种新颖的外部人机接口（eHMI），它可以增强车辆固有的运动提示，而行人在传统交通中已经使用了这种提示。基于 "贝塔运动"（Beta Movement），eHMI 的设计由带有多个向前或向后移动箭头的光带组成，用于指示车辆的加速或减速运动状态。我们在虚拟现实（VR）街道场景中测量了行人在面对配备这种加速指示器 eHMI 的自动驾驶汽车时的行为和安全感知。我们发现，行人会根据迎面而来的车辆的运动状态表现出过马路的行为。如果车辆让行，他们几乎总是会横穿马路，但如果车辆不让行，他们则会考虑空隙大小来横穿马路。在使用加速度指示器 eHMI 的情况下，如果车辆让行，行人会更频繁地横穿马路，但如果车辆不让行，行人横穿马路的频率就会降低。虽然无法完全避免危险的横穿马路行为，但当不礼让的车辆使用这种电子人机界面时，行人横穿马路的速度更快，并保持了更大的安全余量。此外，当电子人机界面显示车辆处于减速状态时，行人会更早开始过马路。在行人的安全感方面，eHMI 没有提高减速车辆的安全感，却有效降低了加速车辆的安全感。这些结果表明，电子人机界面有可能增强车辆固有的运动提示，但同时也意味着，让车辆的运动状态更加明显可能不会简单地提高行人的安全感。总体而言，行人的不安全感似乎是导致其安全过马路行为的一个权衡因素。会议还讨论了对未来研究和 VR 实验的建议。

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引用次数: 0

Human-Machine interfaces and vehicle Automation: A review of the literature and recommendations for system Design, Feedback, and alerts 人机界面和车辆自动化：文献综述及系统设计、反馈和警报建议

IF 3.5 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2024-10-01 DOI: 10.1016/j.trf.2024.08.014

Meng Wang , Shashank Mehrotra , Nicholas Wong , Jah’inaya Parker , Shannon C. Roberts , Woon Kim , Alicia Romo , William J. Horrey

The effectiveness of the human–machine interface (HMI) in a driving automation system is based, in part, on how it issues alerts and requests to the driver—it must quickly and sufficiently orient the driver to the driving task. While much research on the design of HMIs exists, unique associations and meaningful relationships must be considered collectively to offer guidance for vehicle automation. The purpose of the current study was to: (a) review and synthesize existing research and guidance on HMI design as it related to requests to intervene (RTI) for driving automation systems and (b) propose a clear and comprehensive set of recommendations that could inform future system development and implementation. A thorough literature search and selection process was followed the PRISMA guidelines and resulted in the review of 93 articles. The review’s outcome indicates multimodal alerts are prominent, useful, and effective. Many of the HMIs reported in the literature were similar in that they abided by well-established HMI-design guidelines. A small subset of HMIs established evidence for distinct and innovative design principles. Taken together, this study proposed 10 recommendations for HMI design in driving automation systems, ranging from the utility of auditory versus visual alerts to the timing, sensitivity, and location of alerts.

驾驶自动化系统中人机界面（HMI）的有效性部分取决于它如何向驾驶员发出警报和请求--它必须快速、充分地引导驾驶员完成驾驶任务。虽然对人机界面的设计有很多研究，但必须综合考虑独特的关联和有意义的关系，才能为车辆自动化提供指导。本研究的目的是：(a) 回顾和综合与驾驶自动化系统的干预请求 (RTI) 相关的人机界面设计方面的现有研究和指导；(b) 提出一套清晰而全面的建议，为未来的系统开发和实施提供参考。按照 PRISMA 指南进行了全面的文献检索和筛选，共审查了 93 篇文章。综述结果表明，多模式警报非常突出、有用且有效。文献中报道的许多人机界面都大同小异，都遵守了完善的人机界面设计准则。一小部分人机界面则证明了其独特而创新的设计原则。综上所述，本研究为驾驶自动化系统中的人机界面设计提出了 10 项建议，从听觉警报与视觉警报的实用性到警报的时间、灵敏度和位置，不一而足。

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引用次数: 0

In the driver's mind: Modeling the dynamics of human overtaking decisions in interactions with oncoming automated vehicles 驾驶员的想法：模拟人类在与迎面而来的自动驾驶车辆互动时做出超车决定的动态过程

IF 3.5 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2024-10-01 DOI: 10.1016/j.trf.2024.09.020

Samir H.A. Mohammad , Haneen Farah , Arkady Zgonnikov

Understanding human behavior in overtaking scenarios is crucial for enhancing road safety in mixed traffic with automated vehicles (AVs). Computational models of behavior play a pivotal role in advancing this understanding, as they can provide insight into human behavior generalizing beyond empirical studies. However, existing studies and models of human overtaking behavior have mostly focused on scenarios with simplistic, constant-speed dynamics of oncoming vehicles, disregarding the potential of AVs to proactively influence the decision-making process of the human drivers via implicit communication. Furthermore, despite numerous studies in other scenarios, so far it remained unknown whether overtaking decisions of human drivers are affected by whether they are interacting with an AV or a human-driven vehicle (HDV). To address these gaps, we conducted a “reverse Wizard-of-Oz” driving simulator experiment with 30 participants who repeatedly interacted with oncoming AVs and HDVs, measuring the drivers' gap acceptance decisions and response times. The oncoming vehicles featured time-varying dynamics designed to influence the overtaking decisions of the participants by briefly decelerating and then recovering to their initial speed. We found no evidence of differences in participants' overtaking behavior when interacting with oncoming AVs compared to HDVs. Furthermore, we did not find any evidence of brief decelerations of the oncoming vehicle affecting the decisions or response times of the participants. Cognitive modeling of the obtained data revealed that a generalized drift-diffusion model with dynamic drift rate and velocity-dependent decision bias best explained the gap acceptance outcomes and response times observed in the experiment. Overall, our findings highlight that cognitive models of the kind considered here can provide a generalizable description of human overtaking decisions and their timing. Such models can thus help further advance the ongoing development of safer interactions between human drivers and AVs during overtaking maneuvers.

了解超车场景中的人类行为对于提高自动驾驶汽车（AV）混合交通中的道路安全至关重要。行为计算模型在促进这种理解方面发挥着关键作用，因为它们可以提供超越经验研究的人类行为概括洞察力。然而，现有的关于人类超车行为的研究和模型大多集中在迎面而来的车辆具有简单、恒速动态的场景中，忽略了自动驾驶汽车通过隐式通信主动影响人类驾驶员决策过程的潜力。此外，尽管对其他场景进行了大量研究，但迄今为止，人类驾驶员的超车决策是否会受到与自动驾驶汽车或人类驾驶汽车（HDV）交互的影响，仍然是个未知数。为了填补这些空白，我们进行了一项 "反向 Wizard-of-Oz "驾驶模拟实验，让 30 名参与者反复与迎面而来的自动驾驶汽车（AV）和人类驾驶汽车（HDV）互动，测量驾驶员的间隙接受决策和响应时间。迎面而来的车辆具有时变动态特性，旨在通过短暂减速然后恢复到初始速度来影响参与者的超车决策。我们没有发现任何证据表明，在与迎面驶来的自动驾驶汽车进行互动时，参与者的超车行为与普通车辆有所不同。此外，我们也没有发现任何证据表明迎面而来的车辆短暂减速会影响参与者的决策或反应时间。对获得的数据进行认知建模后发现，具有动态漂移率和速度相关决策偏差的广义漂移-扩散模型最能解释实验中观察到的间隙接受结果和反应时间。总之，我们的研究结果突出表明，本文所考虑的这种认知模型可以对人类的超车决策及其时间进行通用描述。因此，此类模型有助于进一步推动人类驾驶员与自动驾驶汽车在超车过程中进行更安全互动的持续发展。

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引用次数: 0

Sensor fusion to connect gaze fixation with dynamic driving context for driver attention management 融合传感器，将凝视固定与动态驾驶环境联系起来，实现驾驶员注意力管理

IF 3.5 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2024-10-01 DOI: 10.1016/j.trf.2024.07.025

Shiyan Yang, Kyle M. Wilson, Brook Shiferaw, Trey Roady, Jonny Kuo, Michael G. Lenné

Objective

The paper aims to integrate interior and exterior sensing signals to explore gaze-context connections for more context-aware driver attention management.

Background

Driving context is important for crash risk assessment, but little is known about how it modulates attention requirements for developing driver monitoring systems.

Method

Twenty-four participants drove a Tesla Model S equipped with Autopilot on the highway, during which driver gaze, headway, speed, and driving mode were sampled from the driver monitoring system, Mobileye, and CAN Bus. These signals were processed and synchronized over each single gaze fixation and incorporated into a Bayesian generalized linear model to assess the effects of dynamic contextual factors on the duration of individual gaze fixation.

Results

During car following, gaze fixations on eccentric locations in the road scene were shorter. Changes in headway led to longer fixations on the lead vehicle. Moreover, higher vehicle speed and larger acceleration/deceleration, regardless of being in the manual or assisted driving mode, led to longer fixations on the road center. In addition, driving mode itself had a small effect on fixation duration.

Conclusion

Sensor fusion, along with computation models, explains the connections between driver attention and dynamic context in real-world driving.

Application: The gaze-context connections provide insight into developing more context-sensitive gaze metrics to support adaptive driver attention management.

背景驾驶环境对于碰撞风险评估非常重要，但对于驾驶环境如何调节开发驾驶员监控系统所需的注意力却知之甚少。方法24名参与者驾驶一辆配备自动驾驶功能的特斯拉Model S行驶在高速公路上，在此期间，驾驶员监控系统、Mobileye和CAN总线对驾驶员的视线、车头、车速和驾驶模式进行了采样。这些信号经过处理后同步到每个单个凝视固定点，并纳入贝叶斯广义线性模型，以评估动态环境因素对单个凝视固定点持续时间的影响。车头距离的变化导致对前车的凝视时间延长。此外，不管是手动驾驶模式还是辅助驾驶模式，车速越高、加减速越大，对道路中心的注视固定时间就越长。此外，驾驶模式本身对凝视持续时间的影响较小。结论传感器融合与计算模型一起解释了真实世界驾驶中驾驶员注意力与动态环境之间的联系：应用：凝视与上下文之间的联系为开发对上下文更敏感的凝视指标提供了启示，从而支持自适应驾驶员注意力管理。

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引用次数: 0

Trust calibration through perceptual and predictive information of the external context in autonomous vehicle 通过自动驾驶汽车外部环境的感知和预测信息进行信任校准

IF 3.5 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2024-09-28 DOI: 10.1016/j.trf.2024.09.019

Qi Gao, Lehan Chen, Yanwei Shi, Yuxuan Luo, Mowei Shen, Zaifeng Gao

Maintaining an appropriate level of trust is critical for driving safety in autonomous vehicles. While enhancing the driver’s situation awareness (SA) of system information in autonomous driving is known to significantly promote trust calibration, it remains unclear whether enhancing the driver’s SA of the external context during driving contributes to this calibration. This study addresses this gap by improving SA of the external context during Level 3 (L3) driving automation across various driving environments. Driving contexts were manipulated using distinct road conditions containing low, medium, or high contextual risks. To enhance driver’s SA of the driving context, we redesigned the in-vehicle central control panel to display real-time perceptual and predictive information about the external driving context. We hypothesized that SA of driving contexts would facilitate trust calibration rather than merely enhancing trust, allowing trust to adjust to appropriate levels under different driving conditions. Experiment 1 examined the impact of perceptual information about the road, traffic infrastructure, and surrounding vehicles on drivers’ trust. We found that driver’s trust decreased with increased contextual risk only when the reconfigured panel was used, while the number of accidents was not affected. Experiment 2 investigated the effect of predictive information about the external context on drivers’ trust by marking safe and dangerous zones around driver’s vehicle with green and red areas, respectively. We revealed that the predictive information calibrated the trust according to road conditions and increased overall trust levels, while the number of accidents was not affected. Together, these findings suggest that enhancing perception and prediction of external contexts helps drivers align their trust with contextual risk levels in L3 driving automation without compromising driving safety.

保持适当的信任度对于自动驾驶汽车的驾驶安全至关重要。众所周知，在自动驾驶中增强驾驶员对系统信息的态势感知（SA）可显著促进信任校准，但在驾驶过程中增强驾驶员对外部环境的态势感知是否有助于这种校准仍不清楚。本研究通过在各种驾驶环境中提高三级（L3）自动驾驶期间对外部环境的感知能力来填补这一空白。驾驶环境是通过包含低、中、高环境风险的不同道路条件来操控的。为了提高驾驶员对驾驶环境的感知能力，我们重新设计了车载中央控制面板，以显示有关外部驾驶环境的实时感知和预测信息。我们假设，驾驶环境的可感知性将促进信任校准，而不仅仅是增强信任，从而使信任在不同的驾驶条件下调整到适当的水平。实验 1 考察了有关道路、交通基础设施和周围车辆的感知信息对驾驶员信任度的影响。我们发现，只有在使用重新配置的面板时，驾驶员的信任度才会随着环境风险的增加而降低，而事故数量则不受影响。实验 2 调查了外部环境的预测信息对驾驶员信任度的影响，方法是将驾驶员车辆周围的安全区和危险区分别标记为绿色和红色。我们发现，预测信息根据路况调整了信任度，并提高了整体信任度，而事故数量却不受影响。这些研究结果表明，加强对外部环境的感知和预测有助于驾驶员根据 L3 自动驾驶中的环境风险水平调整其信任度，而不会影响驾驶安全。

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引用次数: 0

A multi-road user evaluation of the acceptance of connected and automated vehicles through the lenses of safety and justice 从安全和公正的角度对联网和自动驾驶汽车的接受程度进行多路用户评估

IF 3.5 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2024-09-27 DOI: 10.1016/j.trf.2024.09.011

Laura Martínez-Buelvas , Andry Rakotonirainy , Deanna Grant-Smith , Oscar Oviedo-Trespalacios

As technological development towards connected and automated vehicles (CAVs) continues to rise, addressing the challenges associated with their integration is crucial, especially regarding public acceptance. This study explores the acceptability of CAVs, focusing on their potential role in enhancing safety and justice within the transport system. Semi-structured interviews were conducted with a diverse participant group, including 18 car drivers (aged 20–79, M = 48.3, SD = 18.77) and 12 pedestrians (aged 18–61, M = 36.0, SD = 12.94). Thematic analysis was employed to identify and contextualise factors influencing CAV acceptability, encompassing usefulness, ease of use, effectiveness, affordability, and social acceptability. Results emphasised safety as a top priority for both drivers and pedestrians. Trust and system reliability were also common concerns, varying with participants’ roles and transport experiences. Both drivers and pedestrians identified cost and economic benefits as significant barriers to CAV acceptance. Moreover, shared apprehensions about justice in adopting CAVs acknowledged the imperfections inherent in technological advancements. Participants supported CAVs but raised concerns about potential harm to vulnerable road users. Both car drivers and pedestrians expressed concerns that introducing CAVs could exacerbate existing injustices these road users face. This study offers valuable insights into how individual differences influence CAV acceptability, contributing to understanding their preparedness to adopt advanced automotive technologies.

随着互联和自动驾驶汽车（CAVs）技术的不断发展，解决与其集成相关的挑战至关重要，尤其是在公众接受度方面。本研究探讨了 CAV 的可接受性，重点关注其在提高交通系统安全性和公正性方面的潜在作用。研究人员对不同的参与者进行了半结构式访谈，其中包括 18 名汽车驾驶员（年龄在 20-79 岁之间，平均年龄为 48.3 岁，平均差异为 18.77 岁）和 12 名行人（年龄在 18-61 岁之间，平均年龄为 36.0 岁，平均差异为 12.94 岁）。研究人员采用主题分析法来确定影响 CAV 可接受性的因素并将其具体化，这些因素包括实用性、易用性、有效性、可负担性和社会接受度。研究结果强调，安全是驾驶员和行人最优先考虑的问题。信任和系统可靠性也是人们普遍关注的问题，这些问题因参与者的角色和交通经验而异。司机和行人都认为成本和经济效益是阻碍接受 CAV 的重要因素。此外，对采用 CAV 的公正性的共同担忧也承认了技术进步固有的不完善性。与会者支持 CAV，但对其可能对易受伤害的道路使用者造成的伤害表示担忧。汽车司机和行人都表示担心，引入 CAV 可能会加剧这些道路使用者所面临的现有不公正现象。这项研究为了解个体差异如何影响 CAV 的可接受性提供了宝贵的见解，有助于了解他们采用先进汽车技术的准备情况。

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引用次数: 0

Park smart or face the music: Understanding users’ orderly parking behavior of dockless shared bikes from the perspective of deterrence theory 聪明停车，否则遭殃：从威慑理论的角度理解用户有序停放无桩共享单车的行为

IF 3.5 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour

Pub Date : 2024-09-26 DOI: 10.1016/j.trf.2024.09.017

Zhenya Tang , Jianliang Hao , Xizi Wang

The rapid growth of dockless bike-sharing has revolutionized urban transportation. However, the disorderly parking of dockless shared bikes has emerged as a critical challenge, significantly hindering the benefits of this system by causing obstructions, safety hazards, and public nuisance. This study aims to investigate users’ orderly parking behavior of dockless shared bikes through the lens of deterrence theory. Our findings reveal that punishment severity, punishment certainty, personal norm, and descriptive norm have significant positive effects on users’ attitudes towards orderly parking, which in turn positively influences their orderly parking behavior. This study contributes to the literature by extending the application of deterrence theory to the context of dockless bike-sharing and providing empirical evidence on the role of deterrence factors in shaping users’ orderly parking behavior. Our findings offer valuable insights for bike-sharing operators and policymakers to develop effective strategies.

无桩共享单车的快速发展彻底改变了城市交通。然而，无桩共享单车的无序停放已成为一个严峻的挑战，它造成了障碍、安全隐患和公害，严重阻碍了该系统效益的发挥。本研究旨在通过威慑理论的视角，研究用户对无桩共享单车的有序停放行为。我们的研究结果表明，惩罚的严重程度、惩罚的确定性、个人规范和描述性规范对用户的有序停放态度有显著的积极影响，而用户的有序停放态度又反过来对用户的有序停放行为产生积极影响。本研究将威慑理论应用于无桩共享单车，并提供了威慑因素在影响用户有序停放行为方面作用的实证证据，从而为相关文献做出了贡献。我们的研究结果为共享单车运营商和政策制定者制定有效策略提供了有价值的见解。

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引用次数: 0