# Evaluation of Urban Traffic Accidents Based on Pedestrian Landing Injury Risks
## 5 Conclusions, Limitations, and Future Works  
This study demonstrated that pedestrian landing kinematics and injuries are significantly influenced by the symmetrical/asymmetrical features of human anatomy. PRA mainly works by changing the sequence of contact sites between the body and the ground. PFO mainly works by changing the specific location of the contact site between the body and the ground.  
The head HIC value caused by PRA 0-135\({}^{\circ}\) was much higher than that of PRA 180-315\({}^{\circ}\). The head HIC values caused by PFOx+ and PFOx\(-\) were not significantly different, but significantly higher than that of PFOy+. That is, PFOy+ is a safer landing orientation compared with PFOx+ and PFOx\(-\).  
For the neck, both PRA and PFO shows significant effect on neck injury risk. For PRA 180\({}^{\circ}\), the pedestrian would suffer the greatest neck injury no matter which PFO they land in. For PRA 90 or 270\({}^{\circ}\) (that is, the body falls parallel to the ground), the risk of neck injury caused by ground is relatively low. In general, the risk of neck injury caused by PFOy+ is significantly lower than that caused by PFOx+ and PFOx\(-\), indicating PFOy+ is a friendly landing orientation for neck.  
The results show that PRA and PFO can be used to analyze landing injury risk. In the follow-up, it should be combined with the artificial intelligence methods [35; 36] to jointly provide theoretical support for the formulation of active and passive security protection strategies. This would help to predict the risk of urban traffic accidents and make optimal decisions in future smart cities.  
Although this study reported a significant contribution for the evaluation of urban traffic accidents, there are many limitations which can be considered for our future works. First of all, there is a limited number of reconstructed pedestrian accident cases, this results in a lack of statistical significance for the average velocity components in representing the boundaries of pedestrian landing. Therefore, in future research, we need to collect more real-world pedestrian accident data to optimize this research result. In addition, the pedestrian model currently involved in accident reconstruction lacks data validation from ground impact experiments. Therefore, this study only focuses on the distribution trend of pedestrian injury values, rather than the absolute value. Last but not least, in 2020, the COVID-19 pandemic increased the urban traffic as most of people prefer to use their cars instead of public transport [37]. In this regard, the consideration of urban traffic before and during the COVID-19 pandemic is another future research recommendation. Finally, a combination of our prediction model with novel heuristics, metaheuristics, and exact reformulations can be considered for our future work [38; 39; 40; 41].  
Methodology, L.S., M.L. and Q.Z.; Software, M.L. and Q.Z.; Validation, Y.L., K.C. and H.Z.; Formal analysis, H.Z.; Writing--review and editing, H.Z., A.M.F.-F. and Y.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the project \"China Mobile Traffic Accident Scenario (CTAS)\" of CAERI Automotive Safety Technology Center (no. CPYF202004-GA-001); the National Natural Science Foundation of China (no. 52105523); the Natural Science Foundation of Shandong (no. ZR2021 QE249) and the China Postdoctoral Science Foundation Funded Project (no. 2021M703559).  
Not applicable.