## 7 Future Development Trends and Research Prospects
### Technology Development Trends
Advanced sensor-friendly designs incorporating dedicated AV guidance infrastructure, standardized geometric configurations that minimize algorithm adaptation requirements, and redundant positioning systems for navigation reliability represent essential elements for AV-compatible non-conventional lane implementation. These modifications will enable seamless integration while preserving the operational benefits of innovative intersection designs. Dynamic spatiotemporal real-time control strategies represent the next evolutionary step for non-conventional lane systems, enabling adaptive response to unforeseen disturbances, including weather conditions, traffic incidents, and emergency scenarios. The framework integrates multi-layered sensing networks, predictive analytics, and machine learning algorithms for autonomous decision-making. Reinforcement learning agents optimize lane function switching based on real-time reward functions incorporating efficiency, safety, and environmental objectives, while deep learning models provide pattern recognition for disturbance prediction and impact assessment. Computational requirements include edge computing architectures for millisecond response times, distributed sensor networks providing comprehensive situational awareness, and robust communication protocols ensuring system reliability during disruptions. Input data streams encompass traffic sensors, weather monitoring systems, incident detection feeds, and vehicle-infrastructure communication channels, enabling real-time state estimation and predictive modeling. Implementation demands multi-objective optimization algorithms, uncertainty quantification methods, and fail-safe mechanisms ensuring graceful degradation during system limitations. (3) Network-Level Intersection Traffic Design and Control Coordination Optimization Technology  
The optimization of non-conventional lanes will extend from individual intersections to the network level of intersections. The network design method proposed by [PERSON] [81] indicates this development direction. Future research will place more emphasis on the systemic effects of non-conventional lanes in road networks, achieving unity between local optimization and global optimum through the establishment of multi-level, multi-scale optimization models. In urban traffic networks, non-conventional lanes will serve as key nodes, forming an organic whole with conventional roads and achieving balanced distribution and efficient operation of network traffic through coordinated control. Technology development trends indicate that non-conventional lanes are evolving toward more intelligent, refined, and systematic directions. The application of connected and automated vehicle technologies will fundamentally change the operational mode of non-conventional lanes, transforming them from static infrastructure to dynamic, intelligent systems. However, technological progress also brings new challenges, including increased system complexity, higher security requirements, and an urgent need for unified standards and specifications. Future efforts need to strengthen interdisciplinary research, integrating the latest achievements from fields such as traffic engineering, artificial intelligence, and communication technology to promote innovative development of non-conventional lane technology. Simultaneously, attention should be paid to the implementability and economics of technology, ensuring that advanced technologies can be truly applied in practice and generate actual benefits.