Research on the Dynamic Allocation of Time Resources for Self-driving Automotive Communication and Perception

With the popularization of 5G/V2X technology and the acceleration of the commercialization process of autonomous driving, vehicles need to handle communication (V2X interaction) and perception (environmental detection) tasks simultaneously, and the two share limited time and frequency resources. However, in complex traffic scenarios, the competition for time resources among communication and sensing tasks may lead to problems such as resource conflicts, low spectrum utilization, and degradation of system performance. To break through the bottleneck of resource competition, it is urgent to establish a dynamic allocation mechanism to optimize the communication-sensing collaborative efficiency on the premise of ensuring real-time performance. This paper proposes solutions from three aspects: the model design of the integrated communication and perception system, the joint resource allocation strategy, and the non-orthogonal fusion technology. Through technologies such as time resource allocation optimization algorithms, signal waveform design and interference control mechanisms, the communication and perception requirements of autonomous vehicles in different traffic scenarios were analyzed. The simulation experiment results show that the proposed scheme can dynamically adjust the resource allocation according to the scenarios: in high-density scenarios, it gives priority to meeting the time resource requirements of perception tasks, while in low-density scenarios, it optimizes the time allocation of communication tasks. This method significantly improves the performance of autonomous vehicles in different traffic environments, verifying the feasibility and effectiveness of the scheme.