Vehicular fog computing (VFC) enhances Intelligent Traffic System (ITS) by computing the real-time traffic information for accident alerts, path navigation and etc. It utilizes parked and moving vehicles as a fog node to perform computation rather than the core cloud. VFC consumes less bandwidth, decreased response time, and congestion of core cloud due to sort distance. VFC performs resource allocation to select the appropriate vehicle for computation according to the available computational resource. It performs data retrieval operations to transfer traffic data from vehicle to vehicular fog because direct communication is limited by the transmission range of the vehicle. VFC faces various issues during resource allocation and data retrieval operation such as vehicle's high mobility, dynamic topology and etc. This causes uneven resource distribution due to inefficient resource allocation and late data delivery due to unfeasible data retrieval. The security and privacy leakage of traffic data threaten due to sharing in vehicular fog. To overcome these issues, we provide in-depth exploration at each phase of the VFC operation. Hence, we present a new classification of VFC operation, which classifies the challenges every phase such as resource allocation in task division, scheduling, and load balancing; result-retrieval in phase, node selector, node selection and path recovery; secure data sharing in authentication, encipherment, auditing, and data privacy. This state-of-the-art gives a better understanding of open research issues and future direction to efficiently handle the computation at VFC.

车辆雾计算（VFC）通过计算事故警报、路径导航等的实时交通信息来增强智能交通系统（ITS）。它利用停放和移动的车辆作为雾节点而不是核心云来执行计算。VFC 消耗更少的带宽，减少响应时间，并且由于排序距离而导致核心云拥塞。VFC 执行资源分配，根据可用的计算资源选择合适的车辆进行计算。它执行数据检索操作以将交通数据从车辆传输到车辆雾，因为直接通信受到车辆传输范围的限制。VFC在资源分配和数据检索操作中面临各种问题，例如车辆的高机动性、动态拓扑等。这会由于资源分配效率低下而导致资源分配不均，并且由于数据检索不可行而导致数据交付延迟。车雾共享威胁交通数据的安全和隐私泄露。为了克服这些问题，我们在 VFC 操作的每个阶段进行了深入探索。因此，我们提出了一种新的 VFC 操作分类，将任务划分中的资源分配、调度和负载均衡等各个阶段的挑战进行分类；阶段中的结果检索、节点选择器、节点选择和路径恢复；在身份验证、加密、审计和数据隐私方面的安全数据共享。这种最先进的技术可以更好地理解开放的研究问题和未来的方向，以有效地处理 VFC 的计算。