Pedestrian Vehicle Research Articles

Built Environmental Designs in Promoting Pedestrian Safety

This study examined two-level (road environments and census tracts) built environments related to the probability of severe injury for pedestrians. In total, 1407 pedestrian–vehicle crashes (years 2008–2012) were identified from 140 census tracts in the city of Austin. Two multilevel models were applied to examine pedestrian injury severity by using level-1 factors (individual characteristics, road environments, and area characteristics around the crash location) and level-2 factors (characteristics of census tracts). The results demonstrated the importance of using the multi-level model to avoid the biased results from employing the single-level model. This study showed that the likelihood of being severely injured or killed decreased when vehicles turned left, when crashes occurred at intersections, when there were traffic control devices at the crash location, and when crashes occurred during inclement weather conditions. Areas with higher sidewalk densities and higher percentage of commercial uses were negative correlates, while population density was a positive predictor. Pedestrian injury severity has been and will continue to be an important topic for the fields of public health. Future safety programs should focus on providing connected sidewalks and on populated areas.

Pedestrian Detection System for Night Vision Application to Avoid Pedestrian Vehicle Related Accidents

Pedestrian Detection System for Night Vision Application to Avoid Pedestrian Vehicle Related Accidents

Head boundary conditions in pedestrian crashes with passenger cars: six-degrees-of-freedom post-mortem human subject responses

In pedestrian–vehicle crashes, head injuries cause death and long-term disability. Thus, understanding the head kinematics is vital. Head rotation data are scarce, and the influence of individual anthropometry, upper body and arm kinematics on head kinematics is poorly understood. This paper investigates the influence of anthropometry, upper body and arm kinematics on head linear and angular kinematics, providing novel six-degrees-of-freedom data from pedestrian–vehicle-crash experiments. Five similarly positioned subjects were struck by a mid-size sedan at 40 km/h. Three-dimensional translation and three-dimensional rotation of the head, spine and shoulders were compared. Head kinematics differed considerably among the subjects. Variations in anthropometry changed pelvic sliding towards the windshield. Arm responses altered head impact velocity and head rotation. The results have implications for future experiments, evaluation of human models and the design of pedestrian safety systems. Head injury risk can be moderated by reducing head rotation before head impact, and by reducing pelvic sliding.

Fast Calculating Surrogate Models for Leg and Head Impact in Vehicle–Pedestrian Collision Simulations

Objective: In previous research, a tool chain to simulate vehicle–pedestrian accidents from ordinary driving state to in-crash has been developed. This tool chain allows for injury criteria-based, vehicle-specific (geometry, stiffness, active safety systems, etc.) assessments. Due to the complex nature of the included finite element analysis (FEA) models, calculation times are very high. This is a major drawback for using FEA models in large-scale effectiveness assessment studies. Therefore, fast calculating surrogate models to approximate the relevant injury criteria as a function of pedestrian vehicle collision constellations have to be developed.Method: The development of surrogate models for head and leg injury criteria to overcome the problem of long calculation times while preserving high detail level of results for effectiveness analysis is shown in this article. These surrogate models are then used in the tool chain as time-efficient replacements for the FEA model to approximate the injury criteria values. The method consists of the following steps: Selection of suitable training data sets out of a large number of given collision constellations, detailed FEA calculations with the training data sets as input, and training of the surrogate models with the FEA model's input and output values.Results: A separate surrogate model was created for each injury criterion, consisting of a response surface that maps the input parameters (i.e., leg impactor position and velocity) to the output value. In addition, a performance test comparing surrogate model predictions of additional collision constellations to the results of respective FEA calculations was carried out. The developed method allows for prediction of injury criteria based on impact constellation for a given vehicle. Because the surrogate models are specific to a certain vehicle, training has to be redone for a new vehicle. Still, there is a large benefit regarding calculation time when doing large-scale studies.Conclusion: The method can be used in prospective effectiveness assessment studies of new vehicle safety features and takes into account specific local features of a vehicle (geometry, stiffness, etc.) as well as external parameters (location and velocity of pedestrian impact). Furthermore, it can be easily extended to other injury criteria or accident scenarios; for example, cyclist accidents.

The incidence, spectrum and outcome of paediatric trauma managed by the Pietermaritzburg Metropolitan Trauma Service

The Pietermaritzburg Metropolitan Trauma Service (PMTS) has run a systematic quality improvement programme since 2006. A key component included the development and implementation of an effective surveillance system in the form of an electronic surgical registry (ESR). This study used data from the ESR to review the incidence, spectrum and outcome of paediatric trauma in Pietermaritzburg, South Africa. The ESR was reviewed, and all cases of paediatric trauma managed between 1 January 2012 and 30 July 2014 were retrieved for analysis. During the study period, 1,041 paediatric trauma patients (724 male, 69.5%) were managed by the PMTS, averaging a monthly admission of 36. The mean age was 10.9 years (standard deviation: 5.4 years). The mechanism of injury (MOI) was blunt trauma in 753 patients (72.3%) and penetrating trauma in 170 (16.3%). Pedestrian vehicle collisions accounted for 21% of cases and motor vehicle collisions for a further 11%. Intentional trauma accounted for 282 patients (27.1%) and self-inflicted trauma for 14 cases (1.3%). Ninety patients admitted to the intensive care unit and fifty-one required high dependency unit admission. There were 17 deaths, equating to an in-hospital mortality rate of 1.7%. A total of 172 children died on the scene of an incident. There were 35 road traffic related deaths, 26 suicides by hanging, 27 deaths from blunt assault and 23 deaths from penetrating assault. The overall mortality rate for paediatric trauma was 18.2%. The ESR has proved to be an effective surveillance system and has enabled the accurate quantification of the burden of paediatric trauma in Pietermaritzburg. This has improved our understanding of the mechanisms and patterns of injury, and has identified a high incidence of intentional and penetrating trauma as well as road traffic collisions. These data can be used to guide strategies to reduce the burden of paediatric trauma in our environment.

Behavioural analysis of interactions between pedestrians and vehicles in street designs with elements of shared space

This paper describes the development and implementation of qualitative behavioural criteria in order to analyse the conduct of pedestrians and vehicles when they are required to interact with each other, with particular interest to street designs with elements of shared space. The new behavioural analysis technique is developed by identifying the fundamental principles that underpin existing traffic analyses, such as traffic conflicts techniques, and adapting those to a qualitative framework that describes the mindset and rationale of road users. The technique is then applied to a case study in London, using video data from periods before and after the redevelopment of the Exhibition Road site from a conventional dual carriageway to a modern design with some elements of shared space. With the main goals being to assess the pedestrians’ confidence and the vehicles’ tolerance/patience when forced to interact with each other, behavioural trends are related to instantaneous characteristics of the vehicle flow (vehicle approach speed and traffic density). The data produced are used to develop and validate qualitative behavioural relationships for pedestrian–vehicle interactions, as well as location-specific conclusions for the Exhibition Road site.

Analysis of test tools for evaluation of contact-based sensor systems for pedestrian detection

Active systems of the passive vehicle safety, like deployable bonnets or external airbags, are installed in series vehicles since 2005 to fulfil pedestrian protection requirements. However, an appropriate test procedure for these systems was not available until 2010, when Euro NCAP published a revised version of the pedestrian test protocol (version 5.2). In this test protocol, a test method to evaluate contact-based sensor systems for pedestrian detection using so-called hardest-to-detect impactors is described. These impactors shall reproduce the lowest possible impact load induced in the vehicle front in case of a collision with a pedestrian, which is strongly dependent on the anthropometry of the pedestrian as well as the impact configuration. In this paper a holistic analysis of the accident kinematics of pedestrian–vehicle collisions and resulting loads induced in the vehicle front is conducted. The vehicle front is modelled using a generic vehicle buck, which is specifically designed for this analysis. As can be observed by the conducted simulations, the pedestrian size inducing the lowest possible impact load varies for different vehicle categories. Thus, it is not sufficient to consider only one pedestrian size. The comparison of these vehicle–pedestrian simulations with the loads being induced by three hardest-to-detect impactors shows that none of the three impactors is able to reproduce the ‘worst-case scenario’ for all analysed four vehicle categories. The results of this study, which was conducted on behalf of and funded by the German Federal Highway Research Institute (BASt), could be used for the development of a suitable, effective and objective test procedure for active systems of the passive vehicle safety with regard to pedestrian protection.

Comparison of Two Simulation Approaches to Safety Assessment: Cellular Automata and SSAM

AbstractA study is conducted to compare two simulation methods for estimating conflicts between road users. An improved cellular automata (CA) model is proposed to estimate the occurrences and severity of traffic conflicts (both vehicle–vehicle and vehicle–pedestrian) at signalized intersections. The proposed CA model is compared with a calibrated method of a surrogate safety assessment model (SSAM) based on Vissim. Simulated conflicts from both methods are compared with observed vehicle conflicts from automated vehicle tracking for both occurrences and severity. Simulation results show that the CA approach is able to replicate realistic conflicts. However, SSAM tends to overestimate occurrences and underestimate the severity of rear-end and lane-change conflicts. SSAM has also been found to overestimate the severity of crossing conflicts. Furthermore, the proposed CA model is able to estimate conflicts between vehicles and pedestrians.

Factor Association with Multiple Correspondence Analysis in Vehicle–Pedestrian Crashes

In the United States, about 14% of total crash fatalities are pedestrian related. In 2012, 4,743 pedestrians were killed, and 76,000 pedestrians were injured in vehicle–pedestrian crashes in the United States. Vehicle– pedestrian crashes have become a key concern in Louisiana as a result of the high percentage of fatalities there in recent years. In 2012, pedestrians accounted for 17% of total crash fatalities in the state. This study used multiple correspondence analysis (MCA), an exploratory data analysis method used to detect and represent underlying structures in a categorical data set, to analyze 8 years (2004 to 2011) of vehicle–pedestrian crashes in Louisiana. Pedestrian crash data are best represented as transactions of multiple categorical variables, so the use of MCA was a unique choice to determine the relationship of the variables and their significance. The findings indicated several nontrivial focus groups (e.g., drivers with high-occupancy vehicles, female drivers in bad weather conditions, and drivers distracted by mobile phone use). The associated geometric factors were hillcrest roadways, dip or hump aligned roadways, roadways with multiple lanes, and roadways with no lighting at night. Male drivers were seen to be relatively susceptible to severe and moderate injury crashes. Fatal pedestrian crashes were correlated to two-lane roadways with no lighting at night. The MCA method helped measure significant contributing factors and degrees of association between the factors through the analysis of the systematic patterns of variation with categorical data sets of pedestrian crashes. The findings from this study will help transportation professionals improve countermeasure selection strategies.

Violation Behavior Analysis of Pedestrian and Non-Motorized Vehicle

Behavior-based analysis of the relationship between pedestrian and non-motorized vehicle’s violation was established through empirical study and survival analysis. The nonparametric method which belongs to survival analysis a statistical method combining the result of the event and the time of result complied with the SPSS the data statistical analysis software was used to set up hazard rate function and waiting time survival function and then the regularities of the pedestrians and non-motorized vehicles’ irregularities are obtained. The study is helpful to evaluate the crowd on the influence of the irregularities and provide the basis for urban planning.

Micro-Simulation Model for Assessing the Risk of Vehicle–Pedestrian Road Accidents

Data on traffic accidents clearly point to road black spots, where the accident rate is always high. However, road safety research is still far from understanding why these particular places on a road are risky. The reason is the lack of sufficient knowledge on how pedestrians and drivers interact when facing a potentially dangerous traffic situation, and the lack of an integrated framework that relates the data on human behavior to real-world traffic situations. We attempt to tackle this problem by developing SAFEPED, a multi-agent microscopic three-dimensional (3D) simulation of vehicle and pedestrian dynamics at a black spot. SAFEPED is a test platform for evaluating experimentally estimated drivers’ and pedestrians’ behavioral rules, and estimating accident risks in different traffic situations. It aims to analyze the design of existing and future black spots and to assess alternative architectural and environmental solutions in order to identify maximally efficient safety countermeasures.

Design of a Warning System for Pedestrians and Non-Motorized Vehicles

This article aims at to invent a warning system which can be used to improve the widely spread phenomenon of pedestrians and non-motorized vehicles’ traffic violation in our country. We collected data by making researches at the cross between the North and South terminal coach station of Jinan. Analysis of psychological knowledge causes pedestrian and non-motorized vehicle traffic violation are expounded in detail.

An Optimization Model for Guiding Pedestrian–Vehicle Mixed Flows During an Emergency Evacuation

In most metropolitan areas, an emergency evacuation may require a potentially large number of pedestrians to walk some distance to access their passenger cars or resort to transit systems. In this process, the massive number of pedestrians may place a tremendous burden on vehicles in the roadway network, especially at critical intersections. Thus, the effective road enforcement of the vehicle and pedestrian flows and the proper coordination between these two flows at critical intersections during a multimodal evacuation process is a critical issue in evacuation planning. This article presents an integrated linear model for the design of optimized flow plans for massive mixed pedestrian–vehicle flows within an evacuation zone. The optimized flow can also be used to generate signal timing plans at critical intersections. In addition, the linear nature of the model can circumvent the computational burden to apply in large-scale networks. An illustrating example of the evacuation around the M&T Bank Stadium in downtown Baltimore, MD, is presented and used to demonstrate the model's capability to address the complex interactions between vehicle and pedestrian flows within an evacuation zone. Results of simulation experiments verify the applicability of our model to a real-world scenario and further indicate that accounting for such conflicting movements will yield more reliable estimation of an evacuation's required clearance time.

Explaining Pedestrian Safety Experience at Urban and Suburban Street Crossings Considering Observed Conflicts and Pedestrian Counts

This article presents an investigation of pedestrian conflicts and crash count models to learn which exposure measures and roadway or roadside characteristics significantly influence pedestrian safety at road crossings. Negative binomial and ordered proportional odds technique were used to estimate pedestrian conflict count and severity models. Pedestrian counts and conflicts data were collected at 100 locations throughout Connecticut. Pedestrian crash data were collected from the Connecticut Crash Data Repository. The results show that minor and serious conflicts are marginally significant in predicting total pedestrian crashes together with crossing distance and building setback. This suggests that these conflicts may be a good surrogate for crashes in analyzing pedestrian safety. Greater crossing distance and small building setbacks are found to be associated with larger numbers of pedestrian–vehicle crashes. This latter effect is not expected, because we expect vehicle speeds to be lower in areas where the building setback is small. This factor may account for the greater pedestrian activity and more complex interactions in such areas. Further research aimed at identifying a minimum length of time for accurate estimation of pedestrian volume and conflicts to relate to crashes is the subject of continuing investigation by the authors.

A mixed-flow simulation model for congested intersections with high pedestrian–vehicle traffic flows

In design of plans for major metropolitan areas, it should be recognized that a potentially large percentage of the population is walking instead of driving. The massive number of pedestrians may cause tremendous burden to vehicles in the roadway network, and thus should be adequately accommodated. However, limited research has been done to qualitatively evaluate the effectiveness of different control plans at such mixed-flow intersections. Hence, the development of a simulation tool, capable of replicating the realistic road conditions for both the pedestrian and vehicle flows, is an imperative task. Such a simulation tool should be able to account for conflicts between pedestrians, between vehicles, and between pedestrians and vehicles. In this study, we attempt to address this vital subject with the mixed-cellular automata (MCA) method. Our proposed simulation model has integrated the strengths of the CA method with some probabilistic functions, offering a realistic mechanism to reflect the competing and conflict interactions between vehicle and pedestrian flows. To ensure the proposed model’s applicability, this study has used field data to demonstrate the parameter calibration process and examples of some applications. Our extensive experimental results clearly indicate that the simulation model could realistically capture the behaviors and characteristics of mixed flows, offering an effective tool for potential real-world applications.

Power-law in pedestrian crossing flow under the interference of vehicles at an un-signalized midblock crosswalk

Mixed traffic without signal control is complicated. This paper proposes a pedestrian–vehicle cellular automata (CA) model to study the characteristics of the mixed traffic. The model includes two sub models. One is the pedestrian model, in which the heterogeneity is taken into consideration. The other is the vehicle model, in which a safely running mode and a normally running mode are introduced. Simulation results show that (1) the traffic flow experiences four phases, that is, free flow, pedestrians-free flow, vehicles-free flow and jams, (2) pedestrians cross the crosswalk in groups and the sizes of the groups obey power law distribution, and (3) the heterogeneity of pedestrians acts an important role in the system. If the pedestrians are simultaneously homogeneous, the mixed traffic flow shows a “polarization” and these power-laws disappear under high arrival rates of vehicles and pedestrians.

Can visibility difference between driver and pedestrian lead to crash?

Pedestrians are the most vulnerable road users. Some studies have verified that the visibility difference between pedestrians and drivers can lead to pedestrian–vehicle crashes at night when pedestrians cross the road. This paper considered the influences of the ratio of driver and pedestrian visibility, the vehicle original speed, the pavement friction coefficient and the vehicle mass on crashes when the pedestrians go through the road during night, and analysed the vehicle movement process and the collision speed and crash severity under different conditions. Besides, the special conditions considering driver characteristics, roadway features and vehicle features were analysed, respectively. From the results, it is observed that the collision speed and crash severity is higher when the ratio of driver and pedestrian visibility is smaller, the original speed is higher and pavement friction coefficient is higher. Moreover, from the results, the least distance between vehicles is also obtained. This study will make some contribution to the traffic safety improvement.

Decreasing Adhesions and Avoiding Further Surgery in a Pediatric Patient Involved in a Severe Pedestrian versus Motor Vehicle Accident

In this case study, we report the use of manual physical therapy in a pediatric patient experiencing complications from a life-threatening motor vehicle accident that necessitated 19 surgeries over the course of 12 months. Post-surgical adhesions decreased the patient’s quality of life. He developed multiple medical conditions including recurrent partial bowel obstructions and an ascending testicle. In an effort to avoid further surgery for bowel obstruction and the ascending testicle, the patient was effectively treated with a manual physical therapy regimen focused on decreasing adhesions. The therapy allowed return to an improved quality of life, significant decrease in subjective reports of pain and dysfunction, and apparent decreases in adhesive processes without further surgery, which are important goals for all patients, but especially for pediatric patients.

A dynamic evacuation model for pedestrian–vehicle mixed-flow networks

In urban emergency evacuation, a potentially large number of evacuees may depend either on transit or other modes, or need to walk a long distance, to access their passenger cars. In the process of approaching the designated pick-up points or parking areas for evacuation, the massive number of pedestrians may cause tremendous burden to vehicles in the roadway network. Responsible agencies often need to contend with congestion incurred by massive vehicles emanating from parking garages, evacuation buses generated from bus stops, and the conflicts between evacuees and vehicles at intersections. Hence, an effective plan for such evacuation needs to concurrently address both the multi-modal traffic route assignment and the optimization of network signal controls for mixed traffic flows. This paper presents an integrated model to produce the optimal distribution of vehicle and pedestrian flows, and the responsive network signal plan for massive mixed pedestrian–vehicle flows within the evacuation zone. The proposed model features its effectiveness in accounting for multiple types of evacuation vehicles, the interdependent relations between pedestrian and vehicle flows via some conversion locations, and the inevitable conflicts between intersection turning vehicle and pedestrian flows. An illustrating example concerning an evacuation around the M&T stadium area has been presented, and the results indicate the promising properties of our proposed model, especially on reflecting the complex interactions between vehicle and pedestrian flows and the favorable use of high-occupancy vehicles for evacuation operations.

Benefit Estimation of Automatic Braking System Based on Real-World Pedestrian Accidents

The aim of the current study was to assess effectiveness of automatic braking system quantitatively using real pedestrian accident data selected from IVAC database. Based on the IVAC pedestrian accident scenarios, vehicle and pedestrian trajectories, and other information, the relative position of vehicles and pedestrians were estimated one second (0.5 second) prior to the actual crash. According to the pedestrian fatal (AIS3+) risk and compared with the real pedestrian casualty risk, the benefit of the automatic braking system was calculated. About 86.8% (82.3%) reduction in pedestrian fatal (AIS3+) injury at a field of view of 60°.