Pedestrian-vehicle Interactions Research Articles

A novel agent-based model for tsunami evacuation simulation and risk assessment

Tsunami evacuation is an effective way to save lives from the near-field tsunami. Realistic evacuation simulation can provide valuable information for accurate evacuation risk assessment and effective evacuation planning. Agent-based modeling is ideal for tsunami evacuation simulation due to its capability of capturing the emergent phenomena and modeling the individual-level interactions among agents and the agents’ interactions with the environment. However, existing models usually neglect or simplify some important factors and/or mechanisms in tsunami evacuation. For example, uncertainties in seismic damages to the transportation network are not probabilistically considered (e.g., by simply removing the damaged links (roads/bridges) from the network). Typically a relatively small population (i.e., evacuees) is considered (due to computational challenges) while neglecting population mobility. These simplifications may lead to inaccurate estimation of evacuation risk. Usually, only single traffic mode (e.g., on foot or by car) is considered, while pedestrian speed adjustment and multi-modal evacuation (e.g., on foot and by car) are not considered concurrently. Also, pedestrian–vehicle interaction is usually neglected in the multi-modal evacuation. To address the above limitations, this study proposes a novel and more realistic agent-based tsunami evacuation model for tsunami evacuation simulation and risk assessment. Uncertainties in seismic damages to all links in the transportation network as well as uncertainties in other evacuation parameters are explicitly modeled and considered. A novel and more realistic multi-modal evacuation model is proposed that explicitly considers the pedestrian–vehicle interaction, walking speed variability, and speed adjustment for both the pedestrian and car according to traffic density. In addition, several different population sizes are used to model population mobility and its impact on tsunami evacuation risk. The proposed model is applied within a simulation-based framework to assess the tsunami evacuation risk assessment for Seaside, Oregon.

Analysis of Spontaneous Order of Pedestrian–Vehicle Conflicts at Signalized Intersections

Unsafe interactions among road users are often seen on the urban networks of India. The conventional transportation planning method deals with this problem by segregating different modes to minimize intermodal conflicts. However, another school of thought recommends that spaces should be designed to ensure minimum segregation between road users by removing physical barriers and eliminating rules. Once the rules are lifted, road users become attentive to their surroundings, and therefore spontaneous order emerges. The main objective of this study is to explore the yielding behavior of road users during conflicts and analyze the spontaneous order developed at intersections. Traffic data was collected from 12 signalized intersections in India. A total of 1,785 conflicts between pedestrians and vehicles were observed during peak hours at the intersection locations. The modal dominance was examined for whether a pedestrian yields to a vehicle or vice versa. Two multiple linear regression models were developed to analyze the effect of various factors (speed and volume of pedestrians and vehicles, and size of intersection) on the number of conflicts and the proximity of conflicts. The dominance of pedestrians and vehicles was predicted with the help of the binary logit model. The model results suggested that vehicle volume, type of vehicle, noncompliance with signals by pedestrians, number of pedestrians crossing in a group, type of pedestrian–vehicle interaction, and size of intersection are some of the major factors that are significant predictors of the dominance of road users.

Capacity Model of Exclusive Right-Turn Lane at Signalized Intersection considering Pedestrian-Vehicle Interaction

In high density urban areas, pedestrians have a great influence on the capacity of intersections. This paper studies the influence of pedestrians on road capacity and proposes an exclusive right-turn lane capacity model considering pedestrian-vehicle interaction (PV-RTC). Firstly, a pedestrian-vehicle interaction (PVI) model is proposed based on the logit model and static games theory of incomplete information. Through this model, the probability of 6 kinds of pedestrian-vehicle interaction situations (vehicles yield to pedestrians, pedestrians yield to vehicles, etc.) in the crosswalk can be obtained. Then, based on the basic idea of the stop line method and the probabilities of above situations, the PV-RTC model is established, and the sensitivity analysis of the important factors (pedestrian arrival rate, yielding rate, and green time ratio) affecting the model is carried out to clarify the mechanism of the proposed model. Finally, a pedestrian-vehicle interaction model of cellular automata for the exclusive right-turn lane is established and its simulation results are compared with the results of the PV-RTC model. The results show that the relative error between the microscopic simulation model and PV-RTC model is less than 15% overall, which verifies the validity of the PV-RTC model. This study provides references for a more precise estimation method of pedestrian impact on road capacity.

Comparison of exposure in pedestrian crash analyses: A study based on zonal origin-destination survey data

In recent years, the importance of exposure for pedestrian crash analysis has received increasing attention. Unlike the case of motor vehicle crashes, the definition of exposure for pedestrian crash analysis is sometimes vague and the mechanism behind the association between exposure and pedestrian crash is often ambiguously defined. In this study, the number of roads crossed and walking distance is estimated using an integrated trip assignment method at the aggregate level. The number of walking trips are also considered and compared with the distance travelled and road crossing based exposure using joint probability models. Results show that models using the road crossing based exposure approach provides the best model fit. It is found that the number of roads crossed is the most sensitive to vehicle-pedestrian collisions, as it is more strongly correlated to potential vehicle-pedestrian interactions. The results also indicate that the sensitivity of number of road crossed could vary with road types, and road safety measures for pedestrian protection should be widely implemented on low-grade roads.

Assessment pedestrian crossing safety using vehicle-pedestrian interaction data through two different approaches: Fixed videography (FV) vs In-Motion Videography (IMV)

A significant portion of pedestrian accidents occurs in the outskirts areas due to the high vehicle speed and lack of safety facilities for pedestrians. Behavioral study on drivers and pedestrians is the key to better understand the causes of pedestrian accidents in order to develop safety models.Despite numerous studies on pedestrian safety based on various roads, outskirt areas have not been considered. Hence, the present study focuses on evaluating the safety of pedestrian crossing in urban and outskirt areas and to determine the differences of drivers and pedestrians’ behaviors between these areas through data based on fixed videography (FV) and in-motion videography (IMV). These approaches may lead to an exact analysis of the behavioral differences of road users behaviors from the perspective of pedestrians (FV data) and drivers (IMV data) in urban and outskirts roads. Accordingly, behavioral studies were conducted at urban and outskirts sites through FV as well as IMV using the behavior of 29 participants in the same roads in Babol city, Iran. The gap acceptance model using linear regression and pedestrian crossing probability model using logistic regression for both approaches showed similarity on results in both urban and outskirts roads. Furthermore, behaviors of pedestrians crossing and drivers’ yielding on urban and outskirts roads were very similar. Vehicle speed, the distance of vehicle to pedestrian at the possible collision point, size of pedestrian groups, and waiting time before crossing were the most important behavioral differences of pedestrian for choosing a gap acceptance and probability of crossing on various sites through two different approaches. The inference of the models obtained in this study will lead to a better understanding of the behavior of road users for studies on advanced driving assistance systems (ADAS).

Comparison of Methods to Evaluate the Influence of an Automated Vehicle’s Driving Behavior on Pedestrians: Wizard of Oz, Virtual Reality, and Video

Integrating automated vehicles into mixed traffic entails several challenges. Their driving behavior must be designed such that is understandable for all human road users, and that it ensures an efficient and safe traffic system. Previous studies investigated these issues, especially regarding the communication between automated vehicles and pedestrians. These studies used different methods, e.g., videos, virtual reality, or Wizard of Oz vehicles. However, the extent of transferability between these studies is still unknown. Therefore, we replicated the same study design in four different settings: two video, one virtual reality, and one Wizard of Oz setup. In the first video setup, videos from the virtual reality setup were used, while in the second setup, we filmed the Wizard of Oz vehicle. In all studies, participants stood at the roadside in a shared space. An automated vehicle approached from the left, using different driving profiles characterized by changing speed to communicate its intention to let the pedestrians cross the road. Participants were asked to recognize the intention of the automated vehicle and to press a button as soon as they realized this intention. Results revealed differences in the intention recognition time between the four study setups, as well as in the correct intention rate. The results from vehicle–pedestrian interaction studies published in recent years that used different study settings can therefore only be compared to each other to a limited extent.

Investigating impacts of illegal crossings on vehicle operations at unmarked midblock locations

The objective of this study is to investigate impacts of illegal crossings on vehicle operations at unmarked midblock locations. In this study, we first used a speed testing method to examine the significant difference in vehicle speeds in upstream, crossing, and downstream areas. A multinomial logit model was then proposed to identify impacts of vehicle-pedestrian interactions on vehicle behaviors based on speed, distance, and other safety measures. Last, we quantified the probability of different types of vehicle behaviors influenced by illegal crossings in marginal analysis. A case study was conducted in Nanjing, China, by utilizing trajectory data that were extracted from videos collected by an unmanned aerial vehicle. Results indicate that over half of vehicles chose to decelerate for pedestrians when the speed was less than 45 km/h. When the vehicle-pedestrian lateral distance is more than 3 m, vehicles have a higher probability of maintaining the current running status. When vehicles were involved in an interaction with pedestrians in two adjacent lanes, lane changing was significantly restricted and deceleration was the preferred way to yield in approximately 80% of the interactions. In contrast, the probability of lane changing showed an upward trend as the number of pedestrians ahead of a vehicle increased and reached almost 50% with four pedestrians.

Pedestrian–Vehicle Interaction at Unsignalized Crosswalks: A Systematic Review

A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), to generate a document that supports the development of future research, compiling the various studies focused on the analysis of the pedestrian-vehicle interaction at unsignalized crosswalks. Firstly, 381 studies were identified by applying the search protocol in the database sources; however, only nine studies were included in this review because most of the studies are not focused on this type of crosswalks or have not considered the micro-simulation perspective. For each study, an analysis of the used methodology for data collection was carried out, in addition to what type of model it was applied, including the variables that represent the PVI (Pedestrian-Vehicle Interaction). The outcomes obtained by this systematic review show that although the video camera observation technique is the most used, it is possible to complement them with other tools to add specific field information. Additionally, variables such as the adjacent yields, speed variables vehicles, pedestrian attitude, and the number of pedestrians waiting at the crossing were those most used in the cellular automata model or micro-simulation, which are the commonly developed models to simulate this interaction.

The Modelling of Pedestrian Vehicle Interaction for Post-Exiting Behaviour

During a major evacuation of high capacity buildings, such as a tower block or transportation hub, the emergency services will need to consider the safety of the people within the vicinity of the emergency. However, in general, when assessing the safety of a building for evacuation only the behaviour within the building is considered. One method of assessing this is to utilise a computer based simulation tool. This research outlines a number of developments required to simulate the impact of traffic on the evacuation process in an urban environment in relation to post-exiting behaviour. It uses a unique data set and model capabilities for representing pedestrian-vehicle interaction post-evacuation, which also considers the impact of time pressures on decision making. In addition, a number of software developments and pedestrian behaviours are identified for bridging the behavioural gaps when interfacing an emergency pedestrian model with a traffic simulation.

Combining Reachability Analysis and Importance Sampling for Accelerated Evaluation of Highway Automated Vehicles at Pedestrian Crossing

Abstract Highly automated vehicles (HAVs) must be rigorously evaluated before they are deployed on public roads. An accelerated evaluation framework was proposed in the literature to test HAVs more efficiently. However, running such a test is challenging due to the fact that some of the generated test cases may be not feasible or realistic. This paper proposes an improved accelerated evaluation framework that combines importance sampling with reachability analysis, so that the feasibility of all test cases are guaranteed, and the risk levels of cases are controlled. The performance of the proposed framework is studied using the unprotected pedestrian crossing scenario. A total od 2689 pedestrian–vehicle interaction events are extracted from open-source video data, and a truncated Gaussian mixture model (TGMM) is developed to describe the pedestrian–vehicle interaction. Simulation results show that the proposed method achieves unbiased crash rate estimation in an accelerated fashion while achieving the aforementioned benefits for test case generation (feasible and at controlled risk level).

Evaluating the effectiveness of new-designed crosswalk markings at intersections in China considering vehicle-pedestrian interaction

Crosswalk markings are a type of facility installed at the vehicle-pedestrian interaction locations and the function is to warn drivers to watch out for pedestrians crossing the street and improve safety for pedestrians. In Beijing, a type of new-designed crosswalk markings in China (NCMC) was installed. However, evaluating the effectiveness of this type of crosswalk markings was not conducted. Accordingly, the objective of this paper is to evaluate the effectiveness of this type of new-designed crosswalk markings. During the evaluation process, the vehicle-pedestrian interaction was considered; standard crosswalk markings in China (SCMC) were taken as a control group. In addition, empirical data were collected from a driving simulator, and nine evaluating indicators representing vehicle operating data, drivers’ maneuvering data and drivers’ subjective evaluation were proposed. In order to combine nine indicators, a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was used in this study to achieve the premium degrees of these two types of crosswalk markings. The evaluation result showed that, for intersections with high or low pedestrian flow, the comprehensive effectiveness and influences on drivers’ driving behaviors with presence of NCMC were better than those with presence of SCMC, no matter where vehicle-pedestrian interactions occurred. For intersections with no pedestrians, the comprehensive effectiveness and influences on drivers’ driving behaviors with presence of NCMC were worse than those with presence of SCMC, no matter where vehicle-pedestrian interaction occurred. These results may provide references for facility installing and future development of standards.

Pedestrian Crossing Warrants for Urban Midblock Crossings under Mixed-Traffic Environment

AbstractIn recent times, amplified pedestrian-vehicle interaction, especially at urban midblock crossings, have ensued in higher risks and fatalities during pedestrian crossings. This situation fur...

PEDESTRIAN SAFETY EVALUATION OF SIGNALIZED INTERSECTIONS USING SURROGATE SAFETY MEASURES

The large proportions of pedestrian fatalities led researchers to make the improvements of pedestrian safety at intersections. Thus, this paper proposes a methodology to evaluate crosswalk safety at signalized intersections using Surrogate Safety Measures (SSM) under mixed traffic conditions. The required pedestrian, traffic, and geometric data were extracted based on the videographic survey conducted at signalized intersections in Mumbai (India). Post Encroachment Time (PET) for each pedestrian were segregated into three categories for estimating pedestrian–vehicle interactions and Cumulative Frequency Distribution (CDF) was plotted to calculate the threshold values for each interaction severity level. The Cumulative Logistic Regression (CLR) model was developed to predict the pedestrian mean PET values in the cross-walk at signalized intersections. The proposed model was validated with a new signalized intersection and the results were shown that the proposed PET ranges and model appropriate for Indian mixed traffic conditions. To assess the suitability of model framework, model transferability was carried out with data collected at signalized intersection in Kolkata (India). Finally, this study can be helpful to rank the severity level of pedestrian safety in the crosswalk and improve the existing facilities at signalized intersections.

Surrogate safety indicator for unsignalised pedestrian crossings

ProblemAlthough the road safety situation in Poland is generally improving, the number of accidents at pedestrian crossings has not decreased in the last four years. This paper presents the results of the MOBIS research project, the aim of which was to develop surrogate safety indicators, based on detection of pedestrian-vehicle conflicts using video analysis. MethodPedestrian and vehicle traffic was filmed at two unsignalised pedestrian zebra crossings in Warsaw and Wrocław for over 40 days. Motion trajectories of vehicles and pedestrians were determined based on video processing. Several variables describing pedestrian-vehicle interactions were calculated, such as speed, post-encroachment time, distance between the participants, decelerations, etc. Classification of encounters was based on interactions of pedestrians and vehicles i.e. drivers yielding to pedestrians, vehicles passing just in front of, or behind pedestrians. Results and discussionCriteria for identification of dangerous encounters were selected with the assumption that it should be possible to automate the assessment process. The selected variables were: pedestrian-vehicle passing distance and the vehicle speed at that moment. Other criteria were used in cases of abrupt braking – deceleration exceeding 4 m/s2 and vehicle speed. A Dangerous Encounter Index is proposed as a surrogate safety indicator for pedestrian crossings. It relates the occurrence of dangerous events to exposure, defined as the number of pedestrian-vehicle encounters. Practical applicationsThe proposed index shows that crossing two lanes involves more risk than crossing one lane, given similar traffic flow. Some improvement of safety at both types of crossing was observed after active signage involving blinking lights had been introduced. The proposed method is a step towards automation of safety assessment.

A Social Force Based Pedestrian Motion Model Considering Multi-Pedestrian Interaction with a Vehicle

Pedestrian motion modeling in mixed traffic scenarios is crucial to the development of autonomous systems in transportation related applications. This work investigated how pedestrian motion is affected by surrounding pedestrians and vehicles, i.e., vehicle-pedestrian interaction. A social force based pedestrian motion model was proposed, in which the effect of surrounding pedestrians was improved and the effect of vehicles was newly designed. Variable constraints dependent on vehicle influence as well as nearby pedestrian density were imposed on the velocity and acceleration of the pedestrian motion. This work focuses on fundamental patterns of multi-pedestrian interaction with a low speed vehicle (front, back, and lateral interaction in open space). In other words, the application of the model is not restricted to specific scenarios such as crosswalks. Parameters of the proposed model were calibrated by the genetic algorithm (GA) based on trajectory data of the same vehicle-pedestrian interaction patterns from controlled experiments. The proposed model is able to simulate complex self-designed vehicle-pedestrian interaction scenarios. The effectiveness of the proposed model was validated by comparing the simulated trajectories with ground truth trajectories under the same initial conditions, and by evaluating the pedestrian behavior of avoiding vehicle in the simulation of self-designed scenarios.

Impact of right-turn channelization on pedestrian safety at signalized intersections

Channelized right turns or slip lanes have been widely implemented as an effective countermeasure of reducing traffic delay and number of conflicts between vehicles at signalized intersections. However, only a few studies have investigated the impact of channelized right turns (in left-band driving countries) on pedestrian safety. Channelized right turns may increase the risks for pedestrians since they bring pedestrian-vehicle interactions in a fully non-signalized environment. Furthermore, the increased turning radius at channelized lanes can lead to higher vehicle speeds. This paper investigates the impact of channelized right turns on pedestrian safety based on surrogate safety and behavior measures. Video data were collected from twelve signalized intersections in the city of Zunyi, China, involving three main types of right-turn designs: 1) non-channelized right-only lanes, 2) non-channelized right-through lanes, and 3) channelized right-turn lanes. Different measures are used, including interaction and behavior measures based on a recent-proposed Distance-Velocity model, the PET measurement, speed measurements, and observations of failures in interactions (pedestrian retreats and evasive maneuvers from pedestrians or vehicles). Results indicate that the design of channelized right-turn lane increases pedestrian risks at signalized intersections from different dimensions of safety. The impact of the nighttime condition on pedestrian safety was also compared. Pedestrians are safer at nighttime at non-channelized locations, while the impact of nighttime conditions on pedestrian safety at channelized intersections was not ascertained. Consequently, cities should be cautious to install channelized intersections as a safety countermeasure. Treatments are needed to improve pedestrian safety if channelized right turns are implemented.

Pedestrian Moving Patterns during Potential Conflicts with 110 On-Road Driving Vehicles

As the most commonly seen vulnerable road users, protection and interaction with pedestrians are key functionalities in vehicle active safety and self-driving research areas. Development and evaluation of such systems require deeper understanding of pedestrian behaviors, especially motion patterns, in different driving environments. Traditionally, most of the pedestrian movement studies rely on fixed roadside cameras in specific road locations with higher pedestrian density, like intersections and junctions. Although these studies can provide information to describe pedestrian walking behavior and vehicle-pedestrian interactions in micro and macro levels, there are two main limitations. Firstly, pedestrian movement data are rarely collected from the vehicle’s point of view, which makes some critical variables difficult to be collected related to pedestrian initial appearance situation. Secondly, insufficient data are acquired to cover low- pedestrian-density road environments like mid-block, rural areas, and small un-controlled intersections. In this study, we focus on three important pedestrian movement variables including appearance distances, initial time-to-collision, and crossing speed under different driving and road scenarios. Based on a large-scale naturalistic driving study, crossing pedestrians were randomly captured in the scene videos from 110 passenger cars when potential ego-vehicle-to-pedestrian conflicts appeared during a one-year period. Motion data of these pedestrians were then analyzed to calculate the targeted behavior measurements, with the empirical results reported.

Evaluating pedestrian vehicle interaction dynamics at un-signalized intersections: A proactive approach for safety analysis

The present research demonstrates the use of advanced trajectory based data to analyze road user interactions at an un-signalized intersection under heterogeneous traffic complexities. This study demonstrates an improvement over the conventional grid-based analysis to estimate surrogate safety measures (SSM). An advanced pattern-based approach to categorize pedestrian-vehicle interactions based on the road user behavior is proposed in the study. A concept of a two-interaction pattern has been applied, which deals with the responsive and non -responsive behavior of the road users, respectively. The behavior-based patterns were categorized based on the SSM like Speed, Time to Collision, and Gap Time profiles of the pedestrian and vehicle interacting on an un-signalized intersection. On conducting a variable importance test, i.e., k-fold test, it was comprehended that, for pattern-1, Time to collision (TTC), and for pattern-2 both TTC and Post Encroachment Time (PET) were showing required importance. Further, Import Vector Machine (IVM) approach was used to classify the severity levels based on selected indicators computed from 1486 events, occurring at three Un-Signalized intersections in India. The proposed severity levels will help to test and evaluate various infrastructure and control improvements for making urban intersections safe for road users. It was observed from the severity levels of both the patterns that, events involving non-evasive behavior can also result in critical interaction. Overall, the research provides an advanced framework for evaluating and improving the safety of the uncontrolled intersections.

Assessment of pedestrian-vehicle interaction on urban roads: a critical review

Walking is being promoted as either a main mode of transportation or as a part of multimodal mobility. However, a rapid growth and development in urban areas has resulted in a drastic increase in human population as well as vehicular population in most of the metropolitans across the globe. Due to this, there is an unavoidable increase in conflicts between vehicular traffic and pedestrians often sharing the same road space. At an undesignated crossing, pedestrians wait for suitable inter-vehicular gap to cross the road. However, in order to reduce the waiting delay, pedestrians often take risk by accepting smaller gaps while crossing the road. It increases the probability of their collision with approaching vehicles. Apart from the frequency of crashes, the crash severity is also vastly governed by traffic flow characteristics. In this regard, it is a common belief that the reduction in speed of approaching vehicles can significantly bring down the severity of pedestrian crashes. On the other hand, vehicular movements also get obstructed due to the pedestrian activities carried out on the carriageway. During pedestrian crossing maneuvers, pedestrians often force the approaching vehicle(s) either to slow down or to change the lane which leads to reduction in the average speed of traffic stream. However, in case of pedestrians walking along the road, vehicles tend to shy away towards the center of carriageway to ensure the safe movements of pedestrians. Hence, pedestrians irrespective of crossing or walking along the road, eventually results in the reduction in speed as well as capacity of the road and sometimes prove to be a promising threat to safety of the road users. Therefore, in order to delve into the phenomena of pedestrian-vehicle interaction, one should need to study the mutual influences of pedestrian and vehicular movements on each other. In this background, this paper puts forward a detailed literature review on the assessment of pedestrian-vehicle interaction on urban roads. Findings of the paper are specific and infer the behaviors of both pedestrians and vehicles while sharing the same road space.

Situational characteristics of fatal pedestrian accidents involving vehicles traveling at low speeds in Japan

Objective: This study aimed to investigate the situational characteristics of fatal pedestrian accidents involving vehicles traveling at low speeds in Japan. We focused on vehicles with 4 or more wheels. Such characteristics included daytime or nighttime conditions, road type, vehicle behaviors preceding the accident, and vehicle impact locations.Methods: Pedestrian fatality data on vehicle–pedestrian accidents were obtained from the Institute for Traffic Accident Research and Data Analysis of Japan (ITARDA) from 2005 to 2014. Nine vehicle classifications were considered: Trucks with gross vehicle weight (GVW) ≥7.5 tons and <7.5 tons, buses, box vans, minivans, sport utility vehicles (SUVs), sedans, light passenger cars (LPCs), and light cargo vans (LCVs). We compared the situational daytime or nighttime conditions, road type, vehicle behaviors preceding the accident, and vehicle impact locations for accident-involved vehicles traveling at low and higher speeds across all vehicle types.Results: The results indicate that pedestrian fatalities involving vehicles traveling at low speeds occurred more often under daytime conditions across all vehicle types. At signalized intersections, the relative proportions of pedestrian fatalities were significantly higher when vehicles were traveling at low speed, except when the accidents involved box vans or SUVs. Similarly, when vehicles turned right, the relative proportions of pedestrian fatalities were significantly higher when vehicles traveling at low speed were involved across all vehicle types. In terms of the frontal right vehicle impact location, the relative proportions of pedestrian fatalities were significantly higher when trucks with GVW ≥7.5 tons or <7.5 tons, sedans, or LCVs traveling at low speed were involved.Conclusions: The situational characteristics of fatal pedestrian accidents involving vehicles traveling at low speeds identified in this study can guide targeted development of new traffic safety regulations or technologies specific to vehicle–pedestrian interactions at low vehicle travel speeds (i.e., driver alert devices or automated emergency braking systems). Ultimately, these developments can improve pedestrian safety by reducing the frequency or severity of vehicle–pedestrian accidents for vehicles turning right at intersections and/or reducing the number of resultant pedestrian fatalities.