Travel Behaviour and Society最新文献_第4页

Choice Preferences for Urban Air Mobility: A Latent Class Discrete Choice Model with Mixed Logit Extensions 城市空中交通的选择偏好：一个混合Logit扩展的潜在类离散选择模型

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2026-01-03 DOI: 10.1016/j.tbs.2025.101229

Hong Zhang , Xiangrong Xue , Guocong Zhai , Hongtai Yang , Xiaozhao Lu , Christopher R. Cherry

The emergence of Urban Air Mobility (UAM) is expected to be a potential solution to improve travel efficiency and mitigate traffic congestion. However, choice preferences for UAM are still understudied, especially for the megacities in China. This study investigates the choice preferences for UAM through a hybrid modeling framework that integrates the Latent Class Discrete Choice Model (LCDCM) with the Mixed Logit Model (MLM). A total of 410 respondents were sampled to represent Chengdu residents in 2024. The LCDCM was first applied to identify distinct traveler segments. Then, leveraging soft-classification probabilities as weights, cluster-specific MLMs were estimated to uncover systematic heterogeneity in preferences across groups. Five user classes were identified, mainly characterized by car ownership, safety concerns, and occupation. The MLM results reveal substantial heterogeneity in sensitivity to fares, in-vehicle time, and out-of-vehicle time. Methodologically, this study provides a novel hybrid approach to capture the observed and unobserved heterogeneity of choice preferences. This study practically helps researchers, practitioners, and government agencies to understand the choice preferences of UAM and promote the deployment of UAM in megacities.

城市空中交通（UAM）的出现有望成为提高出行效率和缓解交通拥堵的潜在解决方案。然而，人们对UAM的选择偏好仍未得到充分研究，尤其是在中国的特大城市。本研究通过将潜在类离散选择模型（LCDCM）与混合Logit模型（MLM）集成在一起的混合建模框架来研究UAM的选择偏好。共有410名受访者被抽样，代表2024年的成都居民。LCDCM首先被用于识别不同的旅行者群体。然后，利用软分类概率作为权重，估计集群特定的传销，以揭示跨群体偏好的系统性异质性。该研究确定了五个用户类别，主要以汽车拥有量、安全问题和职业为特征。传销的结果揭示了实质性的异质性敏感性票价，车内时间，和车外时间。在方法上，本研究提供了一种新的混合方法来捕捉观察到的和未观察到的选择偏好的异质性。本研究有助于研究人员、从业人员和政府机构了解UAM的选择偏好，促进UAM在特大城市的部署。

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引用次数: 0

Unraveling influence of perceived service quality of drone delivery service on behavioral intentions 无人机配送服务感知服务质量对行为意向的影响

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2026-01-03 DOI: 10.1016/j.tbs.2025.101227

Xinyu Chen, Doosun Hong, Sunghoon Jang

With the development of drone technology, drone delivery services are gradually being commercialized; however, the service still faces challenges such as immature technology, insufficient publicity, and public concerns about privacy issues. This study aims to identify the key factors affecting consumers’ intention to use drone delivery services and propose improvement strategies to promote the widespread adoption of drone delivery services. Through an online survey of Seoul residents, this survey collected 491 valid questionnaires, examining various characteristics such as gender, age, and online shopping behaviors. By using hybrid generalized ordered logit model, this study analyzed the relationship between individual characteristics, perceived service quality, and usage intention. The findings reveal that eight perceived service qualities have varying degrees of influence on usage intention. Delivery time, noise and privacy are key factors for ’high intent’ consumers, while functionality, safety from infection and delivery time are top factors for ’medium intent’ consumers. In addition, males, those under 40, and those with higher levels of education show a stronger intention to use. Enterprises should enhance the visibility of drone delivery services, optimize service quality, and offer customized services tailored to different groups. Simultaneously, the government should strengthen its focus on data security and legal standards. This study provides both theoretical insights and practical recommendations for the future development of drone delivery services.

随着无人机技术的发展，无人机送货服务正在逐步商业化；然而，这项服务仍然面临着技术不成熟、宣传不足以及公众对隐私问题的担忧等挑战。本研究旨在找出影响消费者使用无人机送货服务意愿的关键因素，并提出改进策略，以促进无人机送货服务的广泛采用。此次调查以首尔市民为对象，对性别、年龄、网上购物行为等进行了问卷调查，共收集了491份有效问卷。采用混合广义有序logit模型，分析了个体特征、感知服务质量与使用意愿之间的关系。研究结果显示，八项感知服务品质对使用意愿有不同程度的影响。配送时间、噪音和隐私是“高意向”消费者的关键因素，而功能、防感染安全性和配送时间是“中等意向”消费者的主要因素。此外，男性、40岁以下和受教育程度较高的人使用手机的意愿更强。企业应提高无人机配送服务的可见性，优化服务质量，针对不同人群提供定制化服务。同时，政府应加强对数据安全和法律标准的关注。本研究为无人机快递服务的未来发展提供了理论见解和实践建议。

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引用次数: 0

Flood hazard assessment and emergency evacuation under rainstorm disasters: A case study of Luhe District in Nanjing 暴雨灾害下洪涝灾害危险性评价与应急疏散——以南京市鹿河区为例

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2026-01-03 DOI: 10.1016/j.tbs.2025.101231

Shuchao Cao , Luhan Ma , Ying Zhou , Xiangxia Ren , Yiping Zeng , Xiaoxia Yang , Peng Wang

In recent years, urban floods caused by heavy rains occur frequently, leading to heavy casualties and economic losses worldwide. Transportation network serves as the backbone of urban lifeline engineering, which is crucial for ensuring residents’ safety and emergency evacuation in flood disasters. Therefore, to investigate the flood hazard for pedestrians and vehicles during the rainstorm, an urban rain-flood coupling model is firstly established and validated to accurately simulate the flood inundation process by fusing multiple types of high-precision data. Four rainfall patterns with return periods of 5 years, 10 years, 50 years and 100 years are designed based on the Chicago rainfall method. The critical instability conditions for heterogeneous pedestrians and vehicles are obtained. Finally, a quantitative assessment framework for flood hazard on urban roads is proposed based on flood simulation results and instability risk analysis. The results indicate that the flood hazard level for pedestrians and vehicles increases with the increment of rainfall intensity and duration. Compared to pedestrians, the adverse impact of floods on vehicles is greater since the length of dangerous roads for vehicles increases by 4.5 times. Compared with adults and SUVs, children and cars are more vulnerable to floods, with the length of dangerous roads increasing by 6 times and 90 % respectively. In emergency circumstances, based on the flood hazard distribution and evacuation distances, feasible evacuation routes and evacuation modes in different residential areas are planned to ensure the safety of citizens. The study is helpful to improve emergency responses and traffic management under urban flood disasters.

近年来，暴雨引发的城市洪水频繁发生，在世界范围内造成了重大人员伤亡和经济损失。交通网络是城市生命线工程的骨干，在洪涝灾害中对保障居民安全和应急疏散至关重要。因此，为了研究暴雨期间行人和车辆的洪水危害，首先建立并验证了城市雨洪耦合模型，通过融合多类型高精度数据准确模拟洪水淹没过程。基于芝加哥降雨法，设计了4种重现周期为5年、10年、50年和100年的降水模式。得到了非均质行人和车辆的临界不稳定条件。最后，基于洪水模拟结果和失稳风险分析，提出了城市道路洪水灾害定量评价框架。结果表明：随着降雨强度和持续时间的增加，行人和车辆的洪水危险程度增加；与行人相比，洪水对车辆的不利影响更大，因为车辆的危险道路长度增加了4.5倍。与成年人和suv相比，儿童和汽车更容易受到洪水的影响，危险道路的长度分别增加了6倍和90%。在紧急情况下，根据洪水灾害分布和疏散距离，规划不同居民区可行的疏散路线和疏散方式，确保市民的安全。研究结果有助于提高城市洪涝灾害下的应急响应和交通管理水平。

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引用次数: 0

Licensing delay versus reduced car orientation in Germany: A cohort perspective using panel data 许可延迟与德国汽车定位减少：使用面板数据的队列视角

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2026-01-02 DOI: 10.1016/j.tbs.2025.101225

Nicole Reinfeld, Tobias Hagen

In Germany, the share of driver’s license holders aged 17 to 20 has decreased from 57.4 % in 2012 to 44.1 % in 2025. Since licensing shares serve as an indicator of future travel behavior, it is important to evaluate whether young cohorts in Germany delay or forgo licensing. This paper contributes to the debate on licensing delay versus reduced car orientation by applying discrete-time survival models to the German Mobility Panel (1994–2022) to estimate the determinants of driver’s license acquisition and to disentangle age, period, and cohort (APC) effects. The results showed that age, household composition, education, employment, car ownership, and spatial factors were significant determinants of obtaining a driver’s license. The strongest effect resulted from reaching the legal minimum age for obtaining a driver’s license. Higher costs for driving school, license fees, and car acquisition reduced the probability of obtaining a license. Members of Gen Y and Gen Z had a statistically significantly lower annual licensing probability compared to Baby Boomers at a given age. Cohort differences in out-of-sample predicted probabilities with respect to the timing of obtaining a driver’s license were only significant at age 18. The difference was no longer significant after controlling for further covariates, indicating that differences can be explained by life-course events such as graduating from school. A weaker decline in predicted licensing probabilities across age groups among Gen Y and Gen Z indicates a delayed licensing for a part of the younger generations compared to Gen X.

在德国，17岁至20岁的驾照持有者比例从2012年的57.4%下降到2025年的44.1%。由于许可证份额是未来旅行行为的一个指标，因此评估德国的年轻群体是否推迟或放弃许可证是很重要的。本文通过将离散时间生存模型应用于德国移动面板（1994-2022）来估计驾驶执照获取的决定因素，并解算年龄、时期和队列（APC）效应，从而有助于关于许可延迟与减少汽车定向的辩论。结果表明，年龄、家庭构成、教育程度、就业、汽车保有量和空间因素是获得驾照的重要决定因素。影响最大的是达到获得驾驶执照的法定最低年龄。更高的驾驶学校费用、执照费和购车费用降低了获得执照的可能性。与婴儿潮一代相比，Y世代和Z世代的成员在特定年龄的年度许可概率显著降低。样本外预测概率在获得驾驶执照时间方面的队列差异仅在18岁时显著。在控制了进一步的协变量后，这种差异不再显著，这表明这种差异可以用人生历程中的事件来解释，比如从学校毕业。在Y世代和Z世代中，各年龄组的预测许可概率下降幅度较弱，这表明与X世代相比，部分年轻一代的许可延迟。

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引用次数: 0

Propagating synthetic populations with dynamic Bayesian networks: a framework for long-horizon demographic forecasting 用动态贝叶斯网络传播合成种群：长期人口预测的框架

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2025-12-31 DOI: 10.1016/j.tbs.2025.101226

Mohammad Mehdi Oshanreh , Nazmul Arefin Khan , Don MacKenzie

This study presents a dynamic demographic microsimulator using dynamic Bayesian networks to forecast long–term changes in household and individual life events. Leveraging longitudinal Panel Study of Income Dynamics (PSID) data, two networks for individuals and households were modeled to simulate transitions in employment, income, education, marriage, childbirth, leaving the parental home, home ownership, mortality, and household formation or dissolution. Across 1,000 simulation runs spanning 24 years, household–level outcomes remain highly accurate and individual–level predictions reasonable. Although accuracy naturally declines with projection horizon, performance remains promising at both levels. This study addresses a key limitation of existing population synthesis models, which typically generate only a single static snapshot of the population. By introducing a framework that propagates cross-sectional outputs into the future, the microsimulator enables the tracking of demographic evolution over time, enhances realism in population-based simulations, and supplies credible inputs to agent-based travel demand models.

本研究提出一个动态人口微模拟器，使用动态贝叶斯网络来预测家庭和个人生活事件的长期变化。利用收入动态纵向面板研究（PSID）数据，对个人和家庭的两个网络进行建模，以模拟就业、收入、教育、婚姻、生育、离开父母家、房屋所有权、死亡率和家庭组建或解散等方面的转变。在跨越24年的1000次模拟运行中，家庭层面的结果仍然高度准确，个人层面的预测仍然合理。尽管准确率自然会随着投影水平的下降而下降，但在这两个水平上的表现仍然很有希望。这项研究解决了现有人口综合模型的一个关键限制，这些模型通常只生成一个人口的静态快照。通过引入一个将横断面输出传播到未来的框架，微模拟器能够跟踪人口随时间的演变，增强基于人口的模拟的真实性，并为基于代理的旅行需求模型提供可靠的输入。

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引用次数: 0

Driving adoption: Discrete choice modeling of consumer valuation for wireless electric vehicles charging in Aotearoa, New Zealand 驱动采用：新西兰Aotearoa地区无线电动汽车充电消费者评估的离散选择模型

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2025-12-30 DOI: 10.1016/j.tbs.2025.101220

Mira Simunic , Mingyue Selena Sheng , Le Wen , Ramesh Chandra Majhi , Prakash Ranjitkar , Bo Du , Minh Kieu , Basil Sharp , Douglas Wilson

This research delves into consumer behavior in the economic domain, particularly focusing on adopting innovative technologies. It assesses the perceived economic and environmental advantages of dynamic wireless power transfer technology, known as dynamic wireless charging. This technology allows electric vehicles to be charged while in motion, which could significantly influence their adoption rates in Aotearoa, New Zealand. The study employs discrete choice modeling to gain insights into consumer valuation of dynamic charging technologies. Various sophisticated logit models were utilized to analyze the data gathered from surveys on consumer preferences rigorously. These models, such as multinomial logit, heteroscedastic logit, and mixed logit, allow for a nuanced understanding of consumer choices by accommodating varying levels of randomness and heterogeneity in decision-making processes. Furthermore, the research investigates the willingness to pay among users, which indirectly measures how much consumers value the ability to charge their vehicles dynamically. The key finding from the study is that the convenience of being able to charge while driving is a significant factor that enhances the adoption of electric vehicles. This indicates that as dynamic wireless charging technology becomes more widespread and accessible, it could be crucial in accelerating the transition towards electric mobility, particularly in contexts where environmental sustainability and technological innovation are prioritized.

这项研究深入研究了经济领域的消费者行为，特别关注创新技术的采用。它评估了被称为动态无线充电的动态无线电力传输技术的经济和环境优势。这项技术允许电动汽车在行驶中充电，这可能会显著影响它们在新西兰奥特罗阿的采用率。本研究采用离散选择模型来深入了解消费者对动态充电技术的评价。利用各种复杂的logit模型对消费者偏好调查收集的数据进行了严格的分析。这些模型，如多项logit、异方差logit和混合logit，通过适应决策过程中不同程度的随机性和异质性，允许对消费者选择进行细致入微的理解。此外，该研究还调查了用户的付费意愿，间接衡量了消费者对汽车动态充电能力的重视程度。这项研究的主要发现是，驾驶时充电的便利性是提高电动汽车普及率的一个重要因素。这表明，随着动态无线充电技术的普及和普及，它可能对加速向电动汽车的过渡至关重要，特别是在环境可持续性和技术创新优先的背景下。

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引用次数: 0

Who waits longer to pick you up? behavioral and spatial inequities in ride-hailing pickup time based on real-world platform data 谁等得更久才来接你？基于真实平台数据的网约车接送时间的行为和空间不平等

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2025-12-29 DOI: 10.1016/j.tbs.2025.101224

Jiayan Zhang , Jiao Jiao , Xiang Wang , Inhi Kim , Tianqi Gu

Pickup time at the post-matching stage is a critical but often overlooked dimension of service equity in ride-hailing systems. While existing studies often rely on modeled or inferred estimates of wait time based on distance, traffic conditions, or simulation outcomes, few have access to actual pickup time records linked to real-name ride-hailing transactions. This study draws on a rare, real-world dataset comprising platform-recorded pickup durations and real-name verified driver profiles from Suzhou, China. Using a Geographically Weighted Random Forest (GWRF) model with SHAP interpretation, we examine how pickup responsiveness varies across driver characteristics (gender, age, residency), geography (central vs. peripheral zones), and time (weekday vs. holiday). Our findings show that young, local male drivers tend to achieve faster pickups due to broader geographic coverage and incentive sensitivity, while older, non-local female drivers face slower pickups, especially under uncertain or high-risk conditions. Moreover, spatial and temporal patterns reveal that conventional assumptions—such as the edge disadvantage or vehicle density effects—do not hold uniformly across groups. These findings suggest that pickup time is a socially embedded outcome rather than a purely algorithmic one. Building on this perspective, we propose behavior-aware dispatch strategies, targeted driver support programs, and regulatory design implications aimed at enhancing equity, inclusion, and responsiveness in ride-hailing governance.

在网约车系统中，匹配后阶段的接车时间是服务公平的一个关键因素，但往往被忽视。虽然现有的研究通常依赖于基于距离、交通状况或模拟结果的模型或推断的等待时间估计，但很少有人能够获得与实名叫车交易相关的实际取车时间记录。本研究利用了一个罕见的、真实的数据集，其中包括来自中国苏州的平台记录的取车时间和实名验证的司机资料。使用具有SHAP解释的地理加权随机森林（GWRF）模型，我们研究了不同驾驶员特征（性别、年龄、居住地）、地理位置（中心与外围区域）和时间（工作日与假日）的取车响应性差异。我们的研究结果表明，由于地理覆盖范围更广和激励敏感性，年轻的本地男性司机往往能够更快地接车，而年长的非本地女性司机则面临更慢的接车速度，尤其是在不确定或高风险的情况下。此外，空间和时间模式表明，传统的假设——如边缘劣势或车辆密度效应——在不同的群体中并不一致。这些发现表明，接送时间是一个社会嵌入的结果，而不是纯粹的算法。基于这一观点，我们提出了行为感知调度策略、有针对性的司机支持计划和监管设计启示，旨在提高网约车治理中的公平性、包容性和响应性。

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引用次数: 0

The influencing factors and nonlinear effects on residents’ green space usage behavior patterns: An interpretable machine learning modelling approach 居民绿地使用行为模式的影响因素及非线性效应：可解释的机器学习建模方法

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2025-12-27 DOI: 10.1016/j.tbs.2025.101223

Wenyue Yang, Yani Chen

Based on survey data collected in Guangzhou in 2021, this study employs Latent Profile Analysis (LPA) to categorize residents’ green space usage behavior patterns. Subsequently, interpretable XGBoost-SHAP machine learning modeling is employed to analyze the factors and nonlinear effects influencing these patterns. The results indicate that residents’ green space usage behavior patterns can be classified into three categories: “short distance-short duration-high frequency”, “moderate distance-medium duration-regular frequency”, and “long distance-long duration-low frequency”. Residents’ individual socio-demographic attributes, perceived accessibility to green spaces, perceived characteristics of green spaces, neighborhood greenness, and the accessibility to nearby green spaces exert different influencing effects on the three types of green space usage behavior patterns. Among these factors, perceived accessibility to green spaces is the most significant factor. Residents with high perceived accessibility prefer the “short distance-short duration-high frequency” pattern, while those with low perceived accessibility prefer the “long distance-long duration-low frequency” pattern. Among the perceived characteristics of green spaces, high safety and plant diversity drive the “short distance-short duration-high frequency” pattern, while moderate aesthetics and animal diversity encourage the “moderate distance-medium duration-regular frequency” pattern. Low safety and plant diversity, along with high animal diversity, drive the “long distance-long duration-low frequency” pattern. Moreover, neighborhood greenness and the accessibility to nearby green spaces exhibit distinct nonlinear effects on residents’ green space usage behavior patterns.

本研究基于广州市2021年的调查数据，采用潜在剖面分析法（Latent Profile Analysis， LPA）对居民绿地使用行为模式进行分类。随后，采用可解释的XGBoost-SHAP机器学习模型分析影响这些模式的因素和非线性效应。结果表明：居民绿地利用行为模式可划分为“短距离-短持续时间-高频率”、“中等距离-中等持续时间-正常频率”和“远距离-长持续时间-低频率”三类。居民个人社会人口属性、感知绿地可达性、感知绿地特征、邻里绿地度和邻近绿地可达性对三类绿地使用行为模式的影响作用不同。在这些因素中，绿色空间的可达性是最重要的因素。可达性高的居民偏好“距离短-持续时间短-频率高”的模式，可达性低的居民偏好“距离长-持续时间长-频率低”的模式。在绿地感知特征中，高安全性和植物多样性推动了“短距离-短持续时间-高频率”的模式，而适度的美学和动物多样性则促进了“中等距离-中等持续时间-规律频率”的模式。低安全性和植物多样性，以及高动物多样性，驱动了“长距离-长持续时间-低频率”的模式。社区绿化度和邻近绿地可达性对居民绿地使用行为模式具有明显的非线性影响。

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引用次数: 0

Adapting to new mobility conditions: Evidence from a Japanese survey on the substitution of in-person mobility with online services for daily necessities 适应新的出行条件：来自日本的一项调查的证据，关于用在线服务替代日常必需品的面对面出行

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2025-12-27 DOI: 10.1016/j.tbs.2025.101221

Tomoyuki Yakura , An Minh Ngoc , Yasuhiro Shiomi

The rapid advancement of information and communication technology (ICT) and the COVID-19 pandemic have significantly reshaped mobility patterns worldwide. As a result, many activities have been replaced from in-person activity to online services. However, relatively little attention has been given to understanding people’s willingness to forgo in-person mobility or replace it with online alternatives, particularly in the case of older adults, who often face challenges in using ICT-based services. This study fills this gap by offering insights into how the potential transportation services market would be if people are offered online services for their daily necessities. A stated choice survey of 645 individuals was conducted in Shiga prefecture, Japan, primarily through an online survey of registered panel members, with additional door-to-door distribution and postal returns in areas with lower panel availability. Then, a mixed logit model was estimated to address the research questions. Results indicate older adults are generally willing and able to substitute car travel with public transport, rather than forgo travel altogether when driving is no longer an option. In addition, individuals are willing to substitute in-person mobility with online alternatives under specific conditions. Substitution is more prevalent among those who are tech-savvy, socially supported, or have access to cars. However, in-person mobilities appear to be less replaceable for older adults, likely due to the sensory nature of shopping and the relational quality of social interaction, which online formats fail to replicate. Overall, this study offers policymakers and business domains insights into better understanding the dominant effect of online services in sustaining daily activities and enabling behavioral adaptation, thus facilitating the development of the digital transformation in various aspects of life services.

信息通信技术（ICT）的快速发展和2019冠状病毒病（COVID-19）大流行极大地改变了全球的流动模式。因此，许多活动已经从面对面的活动取代为在线服务。然而，相对而言，很少有人关注人们是否愿意放弃亲自出行或以在线替代方式取而代之，尤其是老年人，他们在使用基于信息通信技术的服务时经常面临挑战。这项研究填补了这一空白，它揭示了如果为人们提供日常必需品的在线服务，潜在的交通服务市场将如何发展。在日本滋贺县对645名个人进行了一项明确的选择调查，主要是通过对注册小组成员的在线调查进行的，在小组可用性较低的地区，还会进行额外的上门分发和邮政退货。然后，估计了一个混合logit模型来解决研究问题。调查结果显示，老年人通常愿意并且能够用公共交通工具代替汽车出行，而不是在开车不再是一种选择时完全放弃出行。此外，在特定条件下，个人愿意用在线替代面对面的移动。替代在那些精通技术、得到社会支持或拥有汽车的人中更为普遍。然而，对于老年人来说，面对面的活动似乎是不可替代的，这可能是由于购物的感官性质和社交互动的关系质量，而在线模式无法复制。总体而言，本研究为政策制定者和商业领域提供了更好的见解，以更好地理解在线服务在维持日常活动和实现行为适应方面的主导作用，从而促进生活服务各方面数字化转型的发展。

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引用次数: 0

Effects of load state and light conditions on driver takeover performance in a car-two-wheeler risk-state conflict environment 汽车-两轮车风险状态冲突环境下负载状态和光照条件对驾驶员接管行为的影响

IF 5.7 2区工程技术 Q1 TRANSPORTATION

Travel Behaviour and Society

Pub Date : 2025-12-27 DOI: 10.1016/j.tbs.2025.101222

Lin Hu , Jian Zhang , Jing Huang , Xinghua Wang , Jing Zhao , Pak Kin Wong

With the development of automated driving technology, the safety of driver takeover in risky traffic environments has become a key issue. However, in actual driving, the driver’s internal cognitive state and external environmental factors often interact with each other to jointly affect the takeover performance. To this end, this paper explores the effects of driver load state and light conditions on takeover performance for different car-two-vehicle conflict scenarios at signalized intersections on urban roads. The results show that the nighttime environment amplifies the negative impact of load states on takeover performance. The interaction between load state and light conditions had the greatest effect on the left-straight conflict scenario, and drivers in the left-straight conflict scenario had worse takeover performance and higher collision risk compared to the straight-straight and right-straight conflict scenarios. This study provides an important reference for improving the driver’s takeover performance in the risky traffic environment, which is of great significance for the development and improvement of transportation policies and helps to improve the overall transportation safety.

随着自动驾驶技术的发展，驾驶员在危险交通环境下的接管安全已成为一个关键问题。但在实际驾驶中，驾驶员的内部认知状态和外部环境因素往往相互作用，共同影响接管绩效。为此，本文研究了城市道路信号交叉口不同车-两车冲突场景下驾驶员负载状态和光照条件对接管性能的影响。结果表明，夜间环境放大了负载状态对接管性能的负面影响。负载状态和光照条件的交互作用对左直冲突情景影响最大，左直冲突情景驾驶员的接管行为比直直和右直冲突情景更差，碰撞风险更高。本研究为提高风险交通环境下驾驶员接管行为提供了重要参考，对交通政策的制定和完善具有重要意义，有助于提高整体交通安全水平。

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引用次数: 0