## 4 Suitability Evaluation and Effect Analysis of Non-Conventional Lanes
### Traffic Safety Evaluation  
Traffic safety is a factor that must be emphasized in the design of non-conventional lanes, with safety issues primarily focused on driver adaptability, traffic conflicts, and violation behaviors.  
[PERSON] et al. [10] analyzed data from 22,830 left-turning vehicles at 7 EFL intersections in China, finding that 9793 vehicles (42.9% of total left-turning vehicles) used the mixed-usage area. [PERSON] et al. [17] evaluated the safety of outside left-turn lanes based on conflict extremum models using Bayesian hierarchical analysis. [PERSON] et al. [67] constructed a real-time dynamic reversible lane safety control model, with SSAM analysis showing that the scheme can maintain a vehicle traffic conflict rate below 5%. Comprehensive safety risk analysis reveals that non-conventional lanes face distinct challenge patterns requiring systematic countermeasure frameworks. CLL systems exhibit four primary safety concerns: red-light violations at pre-signals (1.83% higher than conventional intersections), head-on collision risks in mixed-usage areas, vehicle entrapment scenarios, and rear-end collision potential due to speed differentials (18.75% reduction in mixed-usage areas). Wrong-way driving violations reach 11.07% during peak hours, reflecting driver adaptation challenges to counterintuitive traffic patterns. Outside left-turn lanes present weaving movement conflicts and sight distance limitations, though hierarchical Bayesian conflict extreme value models demonstrate 21.8% safety improvement potential when properly designed. Advanced safety assessment methodologies, particularly hierarchical Bayesian frameworks, address non-stationarity and heterogeneity in conflict data, enabling robust risk quantification and optimal parameter identification. Effective countermeasure strategies integrate engineering solutions (enhanced signage, geometric optimization, dynamic message systems), enforcement mechanisms (automated monitoring, violation detection),and education programs (driver training, public awareness campaigns). The hierarchical Bayesian approach represents a methodological breakthrough in capturing extreme conflict values with high data utilization efficiency, enabling proactive safety management through predictive risk assessment rather than reactive accident analysis. These advanced modeling frameworks support evidence-based design decisions that balance operational efficiency with acceptable safety performance, providing the analytical foundation for confident non-conventional lane implementation.  
Traffic safety evaluation research shows that while non-conventional lanes bring new safety challenges as they change traditional traffic organization methods, risks can be controlled within acceptable ranges through reasonable design and effective management. Existing research primarily relies on traffic conflict techniques and accident statistical analysis, with insufficient consideration of driver behavior and psychological factors. Future research should strengthen studies on driver behavioral characteristics in non-conventional lane environments and establish safety evaluation methods that consider human factor engineering. Simultaneously, there is a need to develop real-time safety warnings and active safety control systems, utilizing intelligent technologies to enhance the safety level of non-conventional lanes. Furthermore, safety design guidelines and standards for non-conventional lanes should be established to provide guidance for engineering practice.