Next Article in Journal
Modification of Segment Structure Calculation Theory and Development and Application of Integrated Software for a Shield Tunnel
Previous Article in Journal
Ship’s Digital Twin—A Review of Modelling Challenges and Applications
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Applied Sciences
Volume 12
Issue 12
10.3390/app12126040
applsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Evaluation of Urban Traffic Accidents Based on Pedestrian Landing Injury Risks

by
Liangliang Shi
1,
Ming Liu
1,
Yu Liu
1,
Qingjiang Zhao
1,
Kuo Cheng
1,
Honghao Zhang
1,2,* and
Amir M. Fathollahi-Fard
3
1
State Key Laboratory of Vehicle NVH and Safety Technology, China Automotive Engineering Research Institute Co., Ltd., Chongqing 401122, China
2
School of Mechanical Engineering, Shandong University, Jinan 250100, China
3
Department of Electrical Engineering, École de Technologie Supérieure, University of Quebec, Montreal, QC H3C 3P8, Canada
*
Author to whom correspondence should be addressed.
Appl. Sci. 2022, 12(12), 6040; https://doi.org/10.3390/app12126040
Submission received: 11 May 2022 / Revised: 8 June 2022 / Accepted: 11 June 2022 / Published: 14 June 2022
(This article belongs to the Special Issue Recent Progress in Machine Learning and Computational Intelligence in Smart Cities)
Browse Figures
Review Reports Versions Notes

Abstract

:
In comparison with vehicle-to-pedestrian collision, pedestrian-to-ground contact usually results in more unpredictable injuries (e.g., intracranial, neck, and abdominal injuries). Although there are many studies for different applications of such methods, this paper conducts an in-depth analysis of urban traffic pedestrian accidents. The effects of pedestrian rotation angle (PRA) and pedestrian facing orientation (PFO) on head and neck injury risk in a ground contact are investigated by the finite element numerical models and different probabilistic analyses. It goes without saying that this study provides a theoretical basis for the prediction and protection study of pedestrian ground contact injury risk. In our experiments, 24 pedestrian-to-ground simulations are carried out by the THUMS v4.0.2 model considering eight PRAs (0°, 45°, 90°, 135°, 180°, 225°, 270°, 315°, 360°) and three PFOs (x+, x−, y+). Each test was simulated with loading the average linear and rotational velocities that obtained from real-world pedestrian accidents at the pedestrian’s center of gravity. The results show that both PRAs and PFOs have significant impacts on head and neck injuries. Head HIC value caused by PRA 0–135° is much higher than that caused by PRA 180–315°. Neck injury risk caused by PRA 180° is the greatest one in comparison with other PRAs. The PRAs 90° and 270° usually induce a relatively lower neck injury risk. For PFO, the risk of head and neck injury was lower than PFOy+ and PFOx+ or PFOx−, which means PFOy+ was a safer landing orientation for both head and neck. The potential risk of head and neck injuries caused by the ground contact was strongly associated with the symmetry/asymmetric features of human anatomy.

1. Introduction

The World Health Organization (WHO) has released the Global Status Report on Road Safety, which shows that approximately 1.35 million people die annually from road traffic accidents. More than half of all deaths are among those with the least protection: pedestrians (23%), cyclists (3%), and motorcyclists (28%) [1]. Recent trends in traffic safety research show that scientists and industry are making tremendous efforts to find solutions to improve the safety and performance of vehicle systems [2,3,4]. For decades, scholars have focused on road safety research in vehicle-to-pedestrian collisions, and a variety of vehicle safety protection devices and vehicle optimization designs have been proposed [5,6,7,8,9,10,11,12,13]. However, it should be noted that the injuries suffered by pedestrians in road traffic do not only come from vehicles, but also from the ground.
The real-world accident data analysis has shown that ground contact plays a very important role in the cause of pedestrian head injuries [14,15,16]. While there are still few studies on pedestrian-to-ground contact [17,18,19,20,21,22,23,24,25,26,27]. The main reason is that it is difficult for accident investigators to obtain the impact traces between pedestrians and the ground, compared to pedestrian-to-vehicle contact. In addition, the injury risk from ground was correlated to a lesser extent with vehicle velocity [17,21], and the ground usually results in more unpredictable injuries [28].
In recent years, some researchers have studied the kinematics of pedestrian landing and have come up with several typical types of pedestrian landing kinematics [17,19,25,29], this provided an understanding for pedestrian-to-ground contact; however, they did not deeply analyze the influence mechanism of landing kinematics on landing injuries. In 2018, Shi et al. [21] proposed the concept of the pedestrian rotation angle ranges (PRARs) to illustrate the relationship between pedestrian landing kinematics and landing injuries, which demonstrated that any landing kinematics could be classified as one of the four PRARs, and the PRARs are highly correlated with the ground contact mechanism and head injury risk. However, pedestrian landing kinematics and injury risk are not only affected by pedestrian rotation angle, but also by a variety of other factors, such as the pedestrian facing orientations and the landing sequence of body parts, which they did not analyze. Further study found that for the same pedestrian rotation angle, there were significant differences in the risk of head injury during landing for different pedestrian facing orientations [30]. However, they did not delve into the mechanism between this factor and pedestrian injury risk.
Having a look at the literature review, it was found that the biomechanical mechanisms of pedestrian injury is closely related to the symmetric/asymmetric phenomena (structures, shapes, morphologies, geometry, direction, models, aesthetics, etc.) in life sciences [31,32]. In response to this intriguing problem, this paper systematically and quantitatively investigated the effect of human anatomy features on body landing injury risk by considering two key kinematic parameters, pedestrian rotation angle (PRA) and pedestrian facing orientation (PFO). To this end, six real-world pedestrian accidents were reconstructed to derive the boundary parameters at the moment of body-to-ground impact. Then, a total of 24 pedestrian landing simulations were carried out using the THUMS v4.0.2 model with considering eight PRAs and three PFOs. The kinematic-based injury criteria such as the head injury criterion (HIC) and the maximum rotation angle of T1 relative to the head were included in the analysis to investigate head and neck injury risk. Moreover, the influence mechanism of human anatomical symmetry/asymmetry on the risk of landing injuries was deeply analyzed. The results of this study are beneficial to provide theoretical guidance for the research on pedestrian injury control strategies in the automotive industry and traffic management departments.
The rest of this paper is summarized as follows: Section 2 establishes the proposed methodology for the evaluation of urban traffic accidents. Section 3 defines our computational results. Section 4 talks about our main insights and significant results from our experiments. Finally, Section 5 provides a summary of this paper with findings, limitations, and future research recommendations.

2. Methodology

A set of pedestrian-to-ground impact simulations was implemented with the THUMS v4.0.2 model. Each simulation initiated with the pedestrian in a different PRA and PFO just above the ground. PRA is defined by Shi et al. [21], which was used in this paper to explore the effect of asymmetric anatomical features divided by the transverse plane on the risk of ground contact injuries. PFO is defined as the initial facing orientation of pedestrians in the event of vehicle-to-pedestrian collision, aiming to explore the influence of symmetrical and asymmetrical anatomical features divided by sagittal and coronal planes on ground contact injuries.

2.1. Parametric Research Proposal

Figure 1 shows the extraction and loading process of boundary parameters for the pedestrian-to-ground impact simulations. First, six real-world pedestrian traffic accidents were completely reconstructed with reference to the accident reconstruction method proposed by Shi et al. [16]. The detailed workflow of accident reconstruction is depicted in Figure 2. The key parameters related to accidents with vehicles, pedestrians, roads, and the environment are summarized in Table 1. The reconstructed pedestrian kinematics were compared with the video recordings, as shown in Figure A1 (Appendix A). The quantitative validation of reconstruction results and the linear and angular velocity components at the COG of the pedestrian’s body at the moment of 2 milliseconds before the body-to-ground contact were extracted and summarized in Table 2. The average linear velocities along the x, y, and z axes were calculated to be 2.4 m/s, −1.0 m/s and −5.6 m/s respectively, and the average angular velocity around the y-axis was 4.7 rad/s2. Second, the average linear velocity and angular velocity components were loaded into the COG of THUMS v4.0.2 for body-to-ground collisions. To explore the effect of PFO on body-to-ground contact injury, three PFOs were formed by rotating the initial orientation of a standing pedestrian around the z-axis at 90-degree intervals, coding the PFOx+, PFOx−, and PFOy+, respectively. Third, each PFO is rotated around the y-axis in 45° increments, resulting in eight different PRAs. Finally, a total of 24 pedestrian-to-ground impact configurations were defined.

2.2. Impact Conditions

The ground surface was modeled utilizing a rigid body for representing the asphalt ground [33]. The friction coefficient between pedestrian and ground was set to 0.58 [34]. All numerical simulations were performed using the LS-DYNA MPP R9.3.0, LSTC (Livermore Software Technology Co., Livermore, CA, USA).

2.3. Injury Criteria

In this study, the potential risk of head and neck injuries caused by the ground contact was assessed using the HIC and the maximum rotation angle of T1 relative to the head, respectively. The head criteria were selected based on [16], which shown that HIC has a ‘good’ assessment capability for severe head injuries caused by ground contact. The criteria value were calculated based on the simulation results using the THUMS v4.0.2 model in the LS-DYNA code.

3. Results

3.1. Pedestrian Landing Kinematics

For the 24 simulations, pedestrian landing kinematics were completely different due to univariate differences in the PRA and PFO settings. Figure 3, Figure 4 and Figure 5 show three typical kinematic poses for each simulation in the process of body-to-ground contact. Notably, PRA mainly causes changes in the sequence of body parts and ground contact; while PFO mainly caused changes in specific positions of body parts in contact with the ground. For PRAs 0°, 45°, 90°, and 135°, the pedestrian’s upper body suffers a linear velocity component (Vz) perpendicular to the ground and an angular velocity component that rotates toward the ground. The superposition of the two velocity components increases the severity of the head-to-ground contact. Whereas for PRAs 180°, 225°, 270°, and 315°, the angular velocity component causes the head to rotate away from the ground, which can effectively reduce the severity of head-to-ground contact.
According to SE, the steps of social engineering optimizer are established according to the above process.

3.2. Head Injury Caused by Ground Impact

Figure 6 shows the distribution of HIC values for the head-to-ground contact simulations. It can be seen that the HIC caused by PRA 0–135° is significantly higher than that caused by PRA 180–315°, the result is consistent with the findings of [21]. In addition, there are significant differences in head HIC values caused by different PFOs even under the same PRA. For example, at PRAs 0°, 45°, 90°, and 135°, the HIC values caused by PFOy+ are much lower than those of the other two PFOs. While at PRA 180° and 225°, there was no significant difference in PFO-induced HIC values.

3.3. Neck Injury Caused by Ground Impact

Figure 7 shows the maximum rotation angle of T1 relative to the head. For PFOx+ and PFOx−, the rotation direction of T1 relative to the head is opposite no matter which PRA the pedestrian lands with. When the PRA is in the range of 0–180°, PFOx+ subjects the neck to buckling loads, while PFOx− subjects the neck to extension loads. Conversely, when the PRA is in the range of 225–315°, PFOx+ subjects the neck to extension loads, while PFOx− subjects the neck to buckling loads. It is important to note that the risk of neck injury is greatest in each PFO when the PRA is 180°, followed by 315° and 135°. For PFOy+, it primarily subjects the neck to lateral flexion loads. For PRA 180°, the risk of neck lateral flexion injury was greatest, followed by 135°. When the PRA is approximately 45° or 270° (i.e., the body is more parallel to the ground), the risk of neck injury from the ground contact is almost minimal regardless of which PFO the pedestrian lands.

4. Discussions of Results

Combined with pedestrian landing kinematics, the biomechanical mechanisms of pedestrian injury under different ground impact conditions is deeply analyzed as follows.
  • For PRA 0°
When pedestrians land in the orientation of PFOx+, the feet contact the ground first. Due to the counterclockwise rotational momentum of the body, the pedestrian’s knees will bend forward until kneeling. Meanwhile, the upper body leaned backward and eventually the back of the head collided with the ground. In addition to serious head injuries, this landing position would also lead to the risk of waist injury due to excessive reverse stretching of the tissues and organs.
When pedestrians land in the orientation of PFOx−, the feet also contact the ground first. Different from the PFOx+ condition, the change of pedestrian kinematics is not only affected by the counterclockwise rotational momentum, but also the front-to-back asymmetry of the body anatomical structure. Restricted by the physiological bending direction of the knee joint, the impact energy (i.e., rotational momentum energy and landing potential energy) suffered by the lower limbs in this landing orientation is much larger than that in the PFOx+. This can easily lead to reverse traction injuries of the knee joint, and also subject the meniscus, tibia, and femur to greater longitudinal impact. Subsequently, the upper body rotates counterclockwise under the residual rotational energy until the head collides with the ground without any body part protection. In conclusion, this landing orientation is prone to serious head injuries, strained knee ligaments, ruptured menisci, and even fractures of the tibia and femur.
When pedestrians land in the orientation of PFOy+, the right lower limb becomes the main weight-bearing region with the load of the impact energy (i.e., rotational momentum energy and landing potential energy). It would cause the risk of right knee joint medial collateral ligament strain and tibia fracture. Eventually, the right side of the pedestrian’s upper body collides with the ground, which could cause injury to the right shoulder and chest and abdomen organs, but the posture could supply a certain buffer effect on the head-to-ground contact.
  • For PRAs 45°, 90°, 225°, and 270°
When pedestrians land at these four PRAs, the torso and lower limbs remained relatively straight during the ground contact, indicating that the impact energy was less absorbed by these two parts. As for the head, when pedestrians land in orientation of PFOx+ and PFOx−, the head collides with the ground directly; that is, the torso provided no protection on the head. However, when pedestrian lands in the orientation of PFOy+, the shoulder could protect the head to a certain extent, which is why the HIC values in orientation PFOy+ are lower than the other two orientations (see Figure 6).
  • For PRAs 135° and 180°
Although the head is the first ground impact region for these two PRAs, the HIC values show significant differences. For PRA 135°, the head has—in addition to its linear velocity component perpendicular to the ground—an angular velocity component that rotates toward the ground. Whereas for 180°, the head angular velocity component is parallel to the ground. Therefore, pedestrian landing at PRA 135° would result in a higher HIC value than PRA 180°. In addition, when pedestrians land with PRA 135° in PFOy+, the shoulder has a certain protective effect on the head, resulting in a lower HIC value than the other two orientations.
It should be noted that no matter which PFO the pedestrian lands in, the neck bending caused by these two PRAs would be very severe. Especially PRA 180°, although the HIC value of the head is low, the risk of injury is very high due to the extreme bending of the neck caused by the downward pressure of the body.
  • For PRA 315°
Figure 6 shows that PRA 315° is friendly to the head-to-ground contact injury risk. However, the kinematic performance (Figure 3, Figure 4 and Figure 5) suggest that the PRA 315° may cause serious injuries to the pedestrian’s chest, neck, and abdomen. In Figure 3, PFOx+ results in over-extension of the neck, increasing the risk of whiplash injury. In Figure 4, PFOx− results in hyper buckling of the neck, along with excessive compression of the chest and abdomen, increasing the injury risk to the internal organs. In Figure 5, PFOy+ causes the lateral hip to strike the ground, potentially resulting in pelvic injury and crush injury to abdominal organs.

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° was much higher than that of PRA 180–315°. 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°, the pedestrian would suffer the greatest neck injury no matter which PFO they land in. For PRA 90 or 270° (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].

Author Contributions

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.

Funding

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. ZR2021QE249) and the China Postdoctoral Science Foundation Funded Project (no. 2021M703559).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The study did not report any data.

Acknowledgments

The authors would like to thank Na Du (southern campus of the second hospital of Shandong University) for the validation assistance.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

See Figure A1.
Applsci 12 06040 g0a1a 550Applsci 12 06040 g0a1b 550
Figure A1. Comparison of reconstructed kinematics with video screenshots. The pedestrian’s body is blurred in the screenshot, but the body can be clearly judged in the video.
Figure A1. Comparison of reconstructed kinematics with video screenshots. The pedestrian’s body is blurred in the screenshot, but the body can be clearly judged in the video.
Applsci 12 06040 g0a1aApplsci 12 06040 g0a1b

References

  1. WHO. Global Status Report on Road Safety 2018; World Health Organization: Geneva, Switzerland, 2018. [Google Scholar]
  2. Fan, Y.; Zou, X.; Wang, G.; Mu, D. Robust Adaptive Path Following Control Strategy for Underactuated Unmanned Surface Vehicles with Model Deviation and Actuator Saturation. Appl. Sci. 2022, 12, 2696. [Google Scholar] [CrossRef]
  3. Farroni, F.; Genovese, A.; Sakhnevych, A. Performance and Safety Enhancement Strategies in Vehicle Dynamics and Ground Contact. Appl. Sci. 2022, 12, 2034. [Google Scholar] [CrossRef]
  4. Oszczypała, M.; Ziółkowski, J.; Małachowski, J. Reliability Analysis of Military Vehicles Based on Censored Failures Data. Appl. Sci. 2022, 12, 2622. [Google Scholar] [CrossRef]
  5. Schuster, P.J.; Staines, B. Determination of bumper styling and engineering parameters to reduce pedestrian leg injuries. SAE Trans. 1998, 107, 830–840. [Google Scholar]
  6. McCarthy, M.; Simmons, I. Active pedestrian protection. In Proceedings of the 19th International Technical Conference on the Enhanced Safety of Vehicles, Washington, DC, USA, 6–9 June 2005. [Google Scholar]
  7. Wang, F.; Yin, J.; Hu, L.; Wang, M.; Liu, X.; Miller, K.; Wittek, A. Should Anthropometric Differences Between the Commonly Used Pedestrian Computational Biomechanics Models and Chinese Population Be Taken into Account When Predicting Pedestrian Head Kinematics and Injury in Vehicle Collisions in China? Accid. Anal. Prev. 2022, 173, 106718. [Google Scholar] [CrossRef]
  8. Wang, F.; Wu, J.; Hu, L.; Yu, C.; Wang, B.; Huang, X.; Miller, K.; Wittek, A. Evaluation of The Head Protection Effectiveness of Cyclist Helmets Using Full-Scale Computational Biomechanics Modelling of Cycling Accidents. J. Safety Res. 2022, 80, 109–134. [Google Scholar] [CrossRef]
  9. Inomata, Y.; Iwai, N.; Maeda, Y.; Kobayashi, S.; Okuyama, H.; Takahashi, N. Development of the pop-up engine hood for pedestrian head protection. In Proceedings of the 21st International Technical Conference on the Enhanced Safety of Vehicles (ESV 2009), Stuttgart, Germany, 15–18 June 2009. [Google Scholar]
  10. Huang, S.; Yang, J. Optimization of a Reversible Hood for Protecting a Pedestrian’s Head during Car Collisions. Accid. Anal. Prev. 2010, 42, 1136–1143. [Google Scholar] [CrossRef]
  11. Li, G.; Yang, J.; Simms, C. Safer Passenger Car Front Shapes for Pedestrians: A Computational Approach to Reduce Overall Pedestrian Injury Risk in Realistic Impact Scenarios. Accid. Anal. Prev. 2017, 100, 97–110. [Google Scholar] [CrossRef]
  12. Wang, B.; Wang, F.; Otte, D.; Han, Y.; Peng, Q. Effects of Passenger Car Front Profile and Human Factors on Pedestrian Lower Extremity Injury Risk Using German In-Depth Accident Data. Int. J. Crashworthiness 2019, 24, 163–170. [Google Scholar] [CrossRef]
  13. Liu, Y.; Wan, X.; Xu, W.; Shi, L.; Bai, Z.; Wang, F. A Novel Approach to Investigate Effects of Front-End Structures on Injury Response of e-Bike Riders: Combining Monte Carlo Sampling, Automatic Operation, and Data Mining. Accid. Anal. Prev. 2022, 168, 106599. [Google Scholar] [CrossRef]
  14. Otte, D.; Pohlemann, T. Analysis and load assessment of secondary impact to adult pedestrians after car collisions on roads. In Proceedings of the IRCOBI Conference, Isle of Man, UK, 10–12 October 2001. [Google Scholar]
  15. Badea-Romero, A.; Lenard, J. Source of Head Injury for Pedestrians and Pedal Cyclists: Striking Vehicle or Road? Accid. Anal. Prev. 2013, 50, 1140–1150. [Google Scholar] [CrossRef] [Green Version]
  16. Shi, L.; Han, Y.; Huang, H.; Davidsson, J.; Thomson, R. Evaluation of Injury Thresholds for Predicting Severe Head Injuries in Vulnerable Road Users Resulting from Ground Impact via Detailed Accident Reconstructions. Biomech. Modeling Mechanobiol. 2020, 19, 1845–1863. [Google Scholar] [CrossRef]
  17. Kendall, R.; Meissner, M.; Crandall, J. The Causes of Head Injury in Vehicle-Pedestrian Impacts: Comparing the Relative Danger of Vehicle and Road Surface; SAE Technical Paper 1; SAE: Warrendale, PA, USA, 2006. [Google Scholar]
  18. Simms, C.K.; Ormond, T.; Wood, D.P. The influence of vehicle shape on pedestrian ground contact mechanisms. In Proceedings of the IRCOBI Conference, Krakow, Poland, 14–16 September 2011. [Google Scholar]
  19. Crocetta, G.; Piantini, S.; Pierini, M.; Simms, C. The Influence of Vehicle Front-End Design on Pedestrian Ground Impact. Accid. Anal. Prev. 2015, 79, 56–69. [Google Scholar] [CrossRef]
  20. Guillaume, A.; Hermitte, T.; Hervé, V.; Fricheteau, R. Car or ground: Which causes more pedestrian injuries? In Proceedings of the 24th International Technical Conference on the Enhanced Safety of Vehicles (ESV) , Gothenburg, Sweden, 8–11 June 2015. [Google Scholar]
  21. Shi, L.; Han, Y.; Huang, H.; Li, Q.; Wang, B.; Mizuno, K. Analysis of Pedestrian-to-Ground Impact Injury Risk in Vehicle-to-Pedestrian Collisions Based on Rotation Angles. J. Saf. Res. 2018, 64, 37–47. [Google Scholar] [CrossRef]
  22. Shi, L.; Han, Y.; Huang, H.; He, W.; Wang, F.; Wang, B. Effects of Vehicle Front-End Safety Countermeasures on Pedestrian Head Injury Risk during Ground Impact. Proc. Inst. Mech. Eng. Part D J. Automob. Eng. 2019, 233, 3588–3599. [Google Scholar] [CrossRef]
  23. Shang, S.; Otte, D.; Li, G.; Simms, C. Detailed Assessment of Pedestrian Ground Contact Injuries Observed from In-Depth Accident Data. Accid. Anal. Prev. 2018, 110, 9–17. [Google Scholar] [CrossRef]
  24. Shang, S.; Masson, C.; Llari, M.; Py, M.; Ferrand, Q.; Arnoux, P.-J.; Simms, C. The Predictive Capacity of the MADYMO Ellipsoid Pedestrian Model for Pedestrian Ground Contact Kinematics and Injury Evaluation. Accid. Anal. Prev. 2021, 149, 105803. [Google Scholar] [CrossRef]
  25. Han, Y.; Li, Q.; Wang, F.; Wang, B.; Mizuno, K.; Zhou, Q. Analysis of Pedestrian Kinematics and Ground Impact in Traffic Accidents Using Video Records. Int. J. Crashworthiness 2019, 24, 211–220. [Google Scholar] [CrossRef]
  26. Zou, T.; Shang, S.; Simms, C. Potential Benefits of Controlled Vehicle Braking to Reduce Pedestrian Ground Contact Injuries. Accid. Anal. Prev. 2019, 129, 94–107. [Google Scholar] [CrossRef]
  27. Zou, T.; Liu, Q.; Zha, A.; Simms, C.; Chen, T. New Observations from Real-World Vehicle-Pedestrian Collisions in Reducing Ground Related Injury by Controlling Vehicle Braking. Int. J. Crashworthiness 2022, 27, 614–631. [Google Scholar] [CrossRef]
  28. Simms, C.K.; Wood, D.P. Effects of Pre-Impact Pedestrian Position and Motion on Kinematics and Injuries from Vehicle and Ground Contact. Int. J. Crashworthiness 2006, 11, 345–355. [Google Scholar] [CrossRef]
  29. Shang, S.; Masson, C.; Teeling, D.; Py, M.; Ferrand, Q.; Arnoux, P.-J.; Simms, C. Kinematics and Dynamics of Pedestrian Head Ground Contact: A Cadaver Study. Saf. Sci. 2020, 127, 104684. [Google Scholar] [CrossRef]
  30. Shi, L.; Han, Y.; Wang, B.; Huang, H. Effect of Vehicle Front-end Structure on Pedestrian-ground Impact Injury Risk. In Proceedings of the 14th International Forum of Automotive Traffic Safety, Changsha, China, 1 December 2017. [Google Scholar]
  31. Barczyk-Pawelec, K.; Bańkosz, Z.; Derlich, M. Body postures and asymmetries in frontal and transverse planes in the trunk area in table tennis players. Biol. Sport 2012, 29, 127–132. [Google Scholar] [CrossRef] [Green Version]
  32. Wieczorek, B.; Kukla, M.; Warguła, Ł. The Symmetric Nature of the Position Distribution of the Human Body Center of Gravity during Propelling Manual Wheelchairs with Innovative Propulsion Systems. Symmetry 2021, 13, 154. [Google Scholar] [CrossRef]
  33. Huang, Y.; Zhou, Q.; Koelper, C.; Li, Q.; Nie, B. Are Riders of Electric Two-Wheelers Safer than Bicyclists in Collisions with Motor Vehicles? Accid. Anal. Prev. 2020, 134, 105336. [Google Scholar] [CrossRef]
  34. Wood, D.; Simms, C. Coefficient of friction in pedestrian throw. Impact J. ITAI 2000, 9, 12–14. [Google Scholar]
  35. Hassanat, A. Furthest-Pair-Based Decision Trees: Experimental Results on Big Data Classification. Information 2018, 9, 284. [Google Scholar] [CrossRef] [Green Version]
  36. Tarawneh, A.S.; Chetverikov, D.; Hasanat, A.B.; Rahman, M.S. Deep Face Image Retrieval: A Comparative Study with Dictionary Learning. In Proceedings of the IEEE 10th International Conference on Information and Communication Systems, Irbid, Jordan, 11–13 June 2019. [Google Scholar]
  37. Moosavi, J.; Fathollahi-Fard, A.M.; Dulebenets, M.A. Supply chain disruption during the COVID-19 pandemic: Recognizing potential disruption management strategies. Int. J. Disaster Risk Reduct. 2022, 75, 102983. [Google Scholar] [CrossRef]
  38. Zamanikherad, M.; Montazeri, A.; Gheibi, M.; Fathollahi-Fard, A.M.; Behzadian, K. An efficient design of primary sedimentation tanks using a combination of the response surface, metaheuristic, and scenario building methods. Int. J. Environ. Sci. Technol. 2022. [Google Scholar] [CrossRef]
  39. Soleimani, H.; Chhetri, P.; Fathollahi-Fard, A.M.; Mirzapour Al-e-Hashem SM, J.; Shahparvari, S. Sustainable closed-loop supply chain with energy efficiency: Lagrangian relaxation, reformulations and heuristics. Ann. Oper. Res. 2022. [Google Scholar] [CrossRef]
  40. Seydanlou, P.; Jolai, F.; Tavakkoli-Moghaddam, R.; Fathollahi-Fard, A.M. A multi-objective optimization framework for a sustainable closed-loop supply chain network in the olive industry: Hybrid meta-heuristic algorithms. Expert Syst. Appl. 2022, 203, 117566. [Google Scholar] [CrossRef]
  41. Pasha, J.; Nwodu, A.L.; Fathollahi-Fard, A.M.; Tian, G.; Li, Z.; Wang, H.; Dulebenets, M.A. Exact and metaheuristic algorithms for the vehicle routing problem with a factory-in-a-box in multi-objective settings. Adv. Eng. Inform. 2022, 52, 101623. [Google Scholar] [CrossRef]
Applsci 12 06040 g001 550
Figure 1. Methodology implemented for the parametric study.
Figure 1. Methodology implemented for the parametric study.
Applsci 12 06040 g001
Applsci 12 06040 g002 550
Figure 2. Workflow implemented for the pedestrian accident reconstruction.
Figure 2. Workflow implemented for the pedestrian accident reconstruction.
Applsci 12 06040 g002
Applsci 12 06040 g003 550
Figure 3. Typical landing kinematics in PFOx+.
Figure 3. Typical landing kinematics in PFOx+.
Applsci 12 06040 g003
Applsci 12 06040 g004 550
Figure 4. Typical landing kinematics in PFOx−.
Figure 4. Typical landing kinematics in PFOx−.
Applsci 12 06040 g004
Applsci 12 06040 g005 550
Figure 5. Typical landing kinematics in PFOy+.
Figure 5. Typical landing kinematics in PFOy+.
Applsci 12 06040 g005
Applsci 12 06040 g006 550
Figure 6. HIC values caused during head-to-ground contact.
Figure 6. HIC values caused during head-to-ground contact.
Applsci 12 06040 g006
Applsci 12 06040 g007 550
Figure 7. Maximum rotation angle of T1 relative to the head.
Figure 7. Maximum rotation angle of T1 relative to the head.
Applsci 12 06040 g007
Table
Table 1. Key parameters related to these accidents.
Table 1. Key parameters related to these accidents.
Case IDVehicle InfoPedestrian InfoRoad and Environment Info
TypeVelocity (km/h)Brake before CollisionGenderAgeHeight (cm)StateLocationObstaclePavementHumidity
1Sedan67NoMale36179RunningMotor laneNoneAsphaltWet
2Sedan90NoFemale51162RunningMotor laneNoneAsphaltWet
3Sedan63YesFemale37164RunningMotor laneNoneAsphaltDry
4Sedan29NoFemale73142WalkingMotor laneNoneAsphaltDry
5E-bike31YesFemale63157WalkingNon-motor laneNoneAsphaltDry
6MPV29NoFemale79158WalkingCrosswalkNoneAsphaltDry
Table
Table 2. Validation and extraction of reconstruction results.
Table 2. Validation and extraction of reconstruction results.
Case IDFinal Position Error %: Reconstructed vs. ActualLinear and Angular Velocity Components (2 ms before Body-to-Ground Contact)
PedestrianVehicleVx (m/s)Vy (m/s)Vz (m/s)ωy (rad/s)
13.1%2.4%2.8−0.4−5.84.6
23.6%2.7%4.70.1−6.95.8
32.4%1.7%3.90.2−6.15.2
40.9%0.6%1.3−3.8−5.56.5
51.2%1.1%0.9−0.8−5.23.8
60.6%1.3%0.6−1.4−4.32.4
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Shi, L.; Liu, M.; Liu, Y.; Zhao, Q.; Cheng, K.; Zhang, H.; Fathollahi-Fard, A.M. Evaluation of Urban Traffic Accidents Based on Pedestrian Landing Injury Risks. Appl. Sci. 2022, 12, 6040. https://doi.org/10.3390/app12126040

AMA Style

Shi L, Liu M, Liu Y, Zhao Q, Cheng K, Zhang H, Fathollahi-Fard AM. Evaluation of Urban Traffic Accidents Based on Pedestrian Landing Injury Risks. Applied Sciences. 2022; 12(12):6040. https://doi.org/10.3390/app12126040

Chicago/Turabian Style

Shi, Liangliang, Ming Liu, Yu Liu, Qingjiang Zhao, Kuo Cheng, Honghao Zhang, and Amir M. Fathollahi-Fard. 2022. "Evaluation of Urban Traffic Accidents Based on Pedestrian Landing Injury Risks" Applied Sciences 12, no. 12: 6040. https://doi.org/10.3390/app12126040

APA Style

Shi, L., Liu, M., Liu, Y., Zhao, Q., Cheng, K., Zhang, H., & Fathollahi-Fard, A. M. (2022). Evaluation of Urban Traffic Accidents Based on Pedestrian Landing Injury Risks. Applied Sciences, 12(12), 6040. https://doi.org/10.3390/app12126040

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop