Editing Emerging Research Directions (section)

===5. Technical Challenges and Research Directions===
'''5.1. Heterogeneity and Resource Constraints'''
Vehicles use different CPUs, GPUs, and network modules. Developing uniform SDKs and runtime environments (like the VPI mentioned by Shi[5]) is crucial.

'''5.2. Real-Time OS and Scheduling'''
Due to safety requirements, OS-level guarantees are needed for tasks like braking, detection, or communication. Time-sensitive networking and real-time scheduling are active research areas.

'''5.3. Data Offloading and Bandwidth Optimization'''
Not all data can be offloaded to the cloud. Techniques like compressed AI inference, model partitioning, and log prioritization are necessary to reduce bandwidth costs.

'''5.4. Security and Privacy'''
With increased vehicle connectivity comes increased risk. Secure boot, sandboxing, trusted execution environments, and decentralized authentication are vital in VEC systems.

'''5.5. Standardization and APIs'''
There is a need for standardized vehicle-to-cloud and vehicle-to-infrastructure APIs to enable third-party service integration.

[[File: different players in automated driving.jpg|600px|thumb|center| ''Figure 8: [Different Players in Automated Driving: Seminar Presentation.]'']]