## 7 Future Development Trends and Research Prospects  
### Technology Development Trends  
(1) Innovative Application Technologies of Non-conventional Lanes in Connected and Automated Vehicle Environment  
The deep integration of connected and automated vehicle technology with non-conventional lanes will become an important development direction. Research by [PERSON] et al. [51] and [PERSON] et al. [57] has already demonstrated the profound impact of autonomous driving and connected vehicle technologies on traffic flow characteristics. In a connected and automated vehicle environment, non-conventional lanes will transition from passive adaptation to active guidance. Through vehicle-infrastructure cooperation technology, precise prediction and control of vehicle trajectories can be achieved, making the function switching of non-conventional lanes smoother and more efficient. The real-time dynamic control implemented by [PERSON] et al. [25] and [PERSON] et al. [67] in intelligent vehicle-road cooperative environments provides technical validation for this development direction. In the future, based on 5G communication, edge computing, and other technologies, non-conventional lanes will construct intelligent systems integrating perception, decision-making, and control, achieving rapid response and precise control. (2) Demand-Responsive Dynamic Lane Function Setting Technology  
The transition from static design to dynamic response is an inevitable trend in the development of non-conventional lanes. Current research [26; 27; 67; 80] has already made significant progress in dynamic control, but it remains limited to preset scenarios and fixed patterns. Future non-conventional lanes will possess stronger environmental perception capabilities and adaptive abilities, capable of dynamically adjusting lane functions and control strategies according to factors such as real-time traffic conditions, weather conditions, and emergent events. This technological progression builds upon the three-phase development evolution, where each phase contributed essential foundations for current advancement. The transition from manual reversible lane operations to intelligent adaptive systems represents a fundamental shift in spatiotemporal resource management philosophy. CAV technologies and dynamic lane allocation methods advance this evolution further, enabling real-time demand-triggered activation supported by predictive algorithms and multi-objective optimization frameworks that simultaneously balance efficiency, safety, and environmental considerations. Future development will continue this trajectory toward fully autonomous traffic management systems. The integration of autonomous vehicles with non-conventional lane geometries presents both synergistic opportunities and compatibility challenges requiring systematic infrastructure redesign. AV path planning algorithms achieve enhanced performance through trajectory precision that enables aggressive utilization of contraflow sections and variable lane configurations, while vehicle-infrastructure communication facilitates synchronized movements that eliminate human hesitation factors. However, geometric incompatibility arises from path planning complexity, where current algorithms optimized for conventional layouts struggle with non-conventional geometric irregularities, sensor limitations in complex transition zones, and infrastructure predictability requirements that demand consistent geometric parameters. Infrastructure redesign strategies must focus on geometric standardization with consistent turning radii and transition lengths, enhanced marking systems using machine-readable lane demarcation, and communication integration enabling real-time geometric parameter transmission to approaching vehicles.