Autonomous Vehicles (AV) and Advanced Driver Assistant Systems (ADAS) prioritize safety over comfort. The intertwining factors of safety and comfort emerge as pivotal elements in ensuring the effectiveness of Autonomous Driving (AD). Users often experience discomfort when AV or ADAS drive the vehicle on their behalf. Providing a personalized human-like AD experience, tailored to match users' unique driving styles while adhering to safety prerequisites, presents a significant opportunity to boost the acceptance of AVs. This paper proposes a novel approach, Neural Driving Style Transfer (NDST), inspired by Neural Style Transfer (NST), to address this issue. NDST integrates a Personalized Block (PB) into the conventional Baseline Driving Model (BDM), allowing for the transfer of a user's unique driving style while adhering to safety parameters. The PB serves as a self-configuring system, learning and adapting to an individual's driving behavior without requiring modifications to the BDM. This approach enables the personalization of AV models, aligning the driving style more closely with user preferences while ensuring baseline safety critical actuation. Two contrasting driving styles (Style A and Style B) were used to validate the proposed NDST methodology, demonstrating its efficacy in transferring personal driving styles to the AV system. Our work highlights the potential of NDST to enhance user comfort in AVs by providing a personalized and familiar driving experience. The findings affirm the feasibility of integrating NDST into existing AV frameworks to bridge the gap between safety and individualized driving styles, promoting wider acceptance and improved user experiences.

翻译：自动驾驶汽车（AV）与高级驾驶辅助系统（ADAS）通常将安全性置于舒适性之上。安全性与舒适性之间的交织因素已成为确保自动驾驶（AD）有效性的关键要素。当AV或ADAS代替用户驾驶车辆时，用户常会感到不适。在满足安全前提的条件下，提供一种符合用户独特驾驶风格的个性化、类人化的自动驾驶体验，是提升AV接受度的重要机遇。本文受神经风格迁移（NST）启发，提出了一种新颖的神经驾驶风格迁移（NDST）方法以解决此问题。NDST将个性化模块（PB）集成到传统的基线驾驶模型（BDM）中，在遵循安全参数的前提下，实现用户独特驾驶风格的迁移。PB作为一个自配置系统，能够学习并适应个体的驾驶行为，而无需修改BDM。该方法实现了AV模型的个性化，使驾驶风格更贴近用户偏好，同时确保基线安全的关键执行。研究采用两种对比鲜明的驾驶风格（风格A与风格B）验证了所提出的NDST方法，证明了其将个人驾驶风格迁移至AV系统的有效性。我们的工作凸显了NDST通过提供个性化且熟悉的驾驶体验来提升AV用户舒适度的潜力。研究结果证实了将NDST整合到现有AV框架中的可行性，以弥合安全性与个性化驾驶风格之间的差距，从而促进更广泛的接受度和更佳的用户体验。