Browse Topic: Pedestrian safety

Items (295)

V2P-Based Speed Guidance Method for Avoiding Vehicle–Pedestrian Collisions at Intersections

05/14/2025

Conflicts between vehicles and pedestrians at unsignalized intersections occur frequently and often result in serious consequences. In order to alleviate traffic flow congestion at unsignalized intersections caused by accidents, reduce vehicle congestion time and waiting time, and improve intersection safety as well as intersection access efficiency, a speed guidance algorithm based on pedestrian-to-vehicle (P2V) and vehicle-to-pedestrian (V2P) communication technologies is proposed. The method considers the heading angle (direction of motion) of vehicles and pedestrians and combines the post encroachment time (PET) and time to collision (TTC) to determine whether there is a risk of collision, so as to guide the speed of vehicles. Network simulator NS3 and traffic flow simulation software SUMO are used to verify the effectiveness of the speed guidance strategy proposed in this article. The experimental findings demonstrate that the speed guidance strategy introduced in this article

Sun, Yuanyuan, Wang, Kan, Liu, Weizhen, Li, Wenli

Global Vehicle Vibration Enhancement Using Circular Force Technology

2025-01-0015

05/05/2025

In addition to providing safety advantages, sound and vibration are being utilized to enhance the driver experience in Battery Electric Vehicles (BEVs). There's growing interest and investment in using both interior and exterior sounds for pedestrian safety, driver awareness, and unique brand recognition. Several automakers are also using audio to simulate virtual gear shifting of automatic and manual transmissions in BEVs. According to several automotive industry articles and market research, the audio enhancements alone, without the vibration that drivers are accustomed to when operating combustion engine vehicles, are not sufficient to meet the engagement, excitement, and emotion that driving enthusiasts expect. In this paper, we introduce the use of new automotive, high-force, compact, light-weight circular force generators for providing the vibration element that is lacking in BEVs. The technology was developed originally for vibration reduction/control in aerospace applications

Norris, Mark A., Orzechowski, Jeffrey, Sanderson, Brad, Swanson, Douglas, Vantimmeren, Andrew

Validation of Pedestrian Collision Reconstruction Using the PC-Crash Multibody Pedestrian Model

2025-01-8681

04/01/2025

This study validates the use of the pedestrian multibody model in the simulation software PC-Crash. If reasonable inputs are used, the pedestrian model will yield accurate simulations of pedestrian collisions, particularly in terms of accurately simulating the contact points between the pedestrian and the vehicle and in predicting the throw distance of the pedestrian. This study extends prior studies of the PC-Crash pedestrian multibody model by simulating additional staged collisions, by comparing the results of the model to widely utilized throw distance equations, by providing guidance on inputs for the pedestrian multibody, and by providing documentation of the characteristics of the multibody pedestrian. In addition, two new staged pedestrian collisions are discussed and simulated. This study demonstrates the following: (1) The center of gravity height of the PC-Crash pedestrian model is comparable to the center of gravity height reported for pedestrians in anthropometric data. (2

Rose, Nathan, Smith, Connor, Carter, Neal, Metanias, Andrew

Deriving Architectural Requirements for SAE J3016 ^TM Level 3 System from Functional Safety Perspective

2025-01-8009

04/01/2025

Vehicles with SAE J3016TM Level 3 systems are exposed to road infrastructure, Vulnerable Road Users (VRUs), traffic and other actors on roadways. Hence safe deployment of Level 3 systems is of paramount importance. One aspect of safe deployment of SAE Level 3 systems is the application of functional safety (ISO 26262) to their design, development, integration, and testing. This ensures freedom from unreasonable risk, in the event of a system failure and sufficient provisions to maintain Dynamic Driving Task (DDT) and to initiate Minimum Risk Maneuver (MRM), in the presence of random hardware and systematic failures. This paper explores leveraging ISO 26262 standard to develop architectural requirements for enabling SAE Level 3 systems to maintain DDT and MRM during fault conditions and outlines the importance of fail-operability for Level 3 systems, from a functional safety perspective. At a high-level, UN Regulation No. 157 – Automated Lane Keeping Systems (ALKS) is used as a baseline

Mudunuri, Venkateswara Raju, Jayakumar, Namitha

Developing a Vehicle-in-Virtual-Environment (VVE) Based Autonomous Driving Function Development and Evaluation Pipeline for Vulnerable Road User Safety

2025-01-8061

04/01/2025

Traditional methods for developing and evaluating autonomous driving functions, such as model-in-the-loop (MIL) and hardware-in-the-loop (HIL) simulations, heavily depend on the accuracy of simulated vehicle models and human factors, especially for vulnerable road user safety systems. Continuation of development during public road deployment forces other road users including vulnerable ones to involuntarily participate in the development process, leading to safety risks, inefficiencies, and a decline in public trust. To address these deficiencies, the Vehicle-in-Virtual-Environment (VVE) method was proposed as a safer, more efficient, and cost-effective solution for developing and testing connected and autonomous driving technologies by operating the real vehicle and multiple other actors like vulnerable road users in different test areas while being immersed within the same highly realistic virtual environment. This VVE approach synchronizes real-world vehicle and vulnerable road user

Chen, Haochong, Cao, Xincheng, Guvenc, Levent, Aksun Guvenc, Bilin

Empirical Analysis on Machine Vision Recognition of Green Bike Lanes for Vulnerable Road Users Safety

2025-01-8017

04/01/2025

Deliberate modifications to infrastructure can significantly enhance machine vision recognition of road sections designed for Vulnerable Road Users, such as green bike lanes. This study evaluates how green bike lanes, compared to unpainted lanes, enhance machine vision recognition and vulnerable road users safety by keeping vehicles at a safe distance and preventing encroachment into designated bike lanes. Conducted at the American Center for Mobility, this study utilizes a vehicle equipped with a front-facing camera to assess green bike lane recognition capabilities across various environmental conditions including dry daytime, dry nighttime, rain, fog, and snow. Data collection involved gathering a comprehensive dataset under diverse conditions and generating masks for lane markings to perform comparative analysis for training Advanced Driver Assistance Systems. Quality measurement and statistical analysis are used to evaluate the effectiveness of machine vision recognition using

Ponnuru, Venkata Naga Rithika, Das, Sushanta, Grant, Joseph, Naber, Jeffrey, Bahramgiri, Mojtaba

Dynamic Driving Task Assessment Scores for Scenarios Navigated by an OEM ADS-Equipped Vehicle

2025-01-8672

04/01/2025

One of the major issues facing the automated driving system (ADS)-equipped vehicle (AV) industry is how to evaluate the performance of an AV as it navigates a given scenario. The development and validation of a sound, consistent, and transparent dynamic driving task (DDT) assessment (DA) methodology is a key component of the safety case framework (SCF) of the Automated Vehicle – Test and Evaluation Process (AV-TEP) Mission, a collaboration between Science Foundation Arizona and Arizona State University. The DA methodology was presented in earlier work and includes the DA metrics from the recently published SAE J3237 Recommended Practice. This work extends and implements the methodology with an AV developed by OEM May Mobility in four diverse, real-world scenarios: (1) an oncoming vehicle entering the AV’s lane, (2) vulnerable road user (VRU) crossing in front of the AV’s path, (3) a vehicle executing a three-point turn encroaches into the AV’s path, and (4) the AV exhibiting aggressive

Wishart, Jeffrey, Rahimi, Shujauddin, Swaminathan, Sunder, Zhao, Junfeng, Frantz, Matt, Singh, Satvir, Como, Steven Gerard

Compensation Algorithm Development in Platform for Pedestrian ADAS Testing

2025-01-8066

04/01/2025

Test procedures such as EuroNCAP, NHTSA’s FMVSS 127, and UNECE 152 all require specific pedestrian to vehicle overlaps. These overlap variations allow the vehicle differing amounts of time to respond to the pedestrian’s presence. In this work, a compensation algorithm was developed to be used with the STRIDE robot for Pedestrian Automatic Emergency Braking tests. The compensation algorithm uses information about the robot and vehicle speeds and positions determine whether the robot needs to move faster or slower in order to properly overlap the vehicle. In addition to presenting the algorithm, tests were performed which demonstrate the function of the compensation algorithm. These tests include repeatability, overlap testing, vehicle speed variation, and abort logic tests. For these tests of the robot involving vehicle data, a method of replaying vehicle data via UDP was used to provide the same vehicle stimulus to the robot during every trial without a robotic driver in the vehicle.

Bartholomew, Meredith, Nguyen, An, Helber, Nicholas, Heydinger, Gary

Study on the Impact of Vehicle Pitch During Braking on Pedestrian Leg Injuries

2025-01-8741

04/01/2025

With the increasing prevalence of Automatic Emergency Braking Systems (AEB) in vehicles, their performance in actual collision accidents has garnered increasing attention. In the context of AEB systems, the pitch angle of a vehicle can significantly alter the nature of collisions with pedestrians. Typically, during such collisions, the pedestrian's legs are the first to come into contact with the vehicle's front structure, leading to a noticeable change in the point of impact. Thus, to investigate the differences in leg injuries to pedestrians under various pitch angles of vehicles when AEB is activated, this study employs the Total Human Model for Safety (THUMS) pedestrian finite element model, sensors were established at the leg location based on the Advanced Pedestrian Legform Impactor (APLI), and a corresponding vehicle finite element model was used for simulation, analyzing the dynamic responses of the pedestrian finite element model at different pitch angles for sedan and Sport

Hong, Cheng, Ye, Bin, Zhan, Zhenfei, Liu, Yu, Wan, Xinming, Hao, Haizhou

Study on the Improvement of Pedestrian and Vehicle Visibility by Geometric Patterns Projection Lighting

2025-01-8663

04/01/2025

The proportion of pedestrian fatalities due to traffic accidents is higher at night than during the day. Drivers can more easily recognize pedestrians by setting their headlights to high beam, but use of high beam poses the issue of increasing glare for pedestrians. This study proposes a lighting technology that increases the noticeability of pedestrians for drivers and the noticeability of approaching vehicles for pedestrians while at the same time helping to reduce glare for pedestrians. The newly designed lighting enables geometric patterns projection lighting that makes use of projection technology. This geometric pattern projection lighting was compared with conventional low beam and high beam headlights to verify the effectiveness. Tests were conducted on a closed course with the participation of 20 drivers to evaluate the functionality of each headlight type. In these tests, subjects performed specific tasks such as evaluation of pedestrian visibility from the driver’s point of

Kawamura, Kazuyuki, Oshida, Kei

Biofidelity Evaluation of AC-HUMs Pedestrian Model Based on Generic Sedan Buck Model

2025-01-8743

04/01/2025

Objective: This study aims to evaluate the biofidelity of the Advanced Chinese Human Body Model (AC-HUMs) by utilizing a generic sedan buck model and post-mortem human surrogates (PMHS) test data. Methods: The boundary conditions of the simulation were derived from the PMHS test with the buck vehicle. The methodology involved the pose adjustment of the upper and lower extremities of AC-HUMs, executed through a pre-simulation approach. Subsequently, a 200 milliseconds whole body pedestrian crash simulation was conducted using the buck vehicle and the AC-HUMs pedestrian model. The trajectories of AC-HUMs during the period from initial position to head impact were recorded, including the Head CG, T1, T8 and pelvis. Based on the knee joint, the corridors of trajectories from the PMHS test were scaled to match the Chinese 50th percentile male to evaluate the biofidelity of AC-HUMs's kinematic response. Furthermore, the biomechanical responses were compared with the PMHS tests, including

Qian, Jiaqi, Wang, Qiang, Liu, Yu, Wu, Xiaofan, Huida, Zhang, Bai, Zhonghao

Research on the Boundary of Pedestrian Leg Impactor Test in Low-Speed Passive and Active Conditions

2025-01-8735

04/01/2025

With the widespread application of the Automatic Emergency Braking System (AEB) in vehicles, its impact on pedestrian safety has received increasing attention. However, after the intervention of AEB, the kinematic characteristics of pedestrian leg collisions and their corresponding biological injury responses also change. At the same time, in order to accurately evaluate the pedestrian protection performance of vehicles, the current assessment regulations generally use advanced pedestrian protection leg impactors (aPLI) and rigid leg impactors (TRL) to simulate the movement and injury conditions of pedestrian legs. Based on this, in order to explore the collision boundary conditions and changes in injury between vehicles and APLI and TRL leg impactors under the action of AEB, this paper first analyzes the current passive and active assessment conditions. Secondly, the simulation software LS-DYNA is used to build a finite element model of APLI and TRL impactor-vehicle collisions to

Ye, Bin, Hong, Cheng, Wan, Xinming, Liu, Yu, Cheng, James, Long, Yongchen, Hao, Haizhou

Lattice Based Localized Energy Absorber for Improved Vulnerable Road User Performance for a Vehicle

2025-01-8723

04/01/2025

A passenger vehicle hood is designed to meet Vulnerable Road User (VRU) regulatory requirements and consumer metric targets. Generally, hood inner design and its reinforcements, along with deformable space available under the hood are the main enablers to meet the Head Impact performance targets. However, cross functional balancing requirements, such as hood stiffness and packaging space constraints, can lead to higher Head Injury Criteria (HIC15) scores, particularly when secondary impacts are present. In such cases, a localized energy absorber is utilized to absorb the impact energy to reduce HIC within the target value. The current localized energy absorber solutions include the usage of flexible metal brackets, plastic absorbers etc. which have limited energy absorbing capacity and tuning capability. This paper focuses on usage of a novel 3D printed energy absorbers, based on various kinds of lattice structures. These absorbers are either sandwiched between the inner and the outer

Kinila, Vivekananda, Agarwal, Varun, V S, Rajamanickam, Tripathy, Biswajit, Gupta, Vishal

Analysis of OEM Collision Avoidance Data Outputs during VRU Testing

2025-01-8053

04/01/2025

Using OEM tools to analyze data available from on-vehicle collision avoidance systems can shed light on the data scope that is available to analyze failures in these systems. In this work, an Advanced Driver Assistance System (ADAS)-equipped vehicle was tested to determine the performance in several collision imminent scenarios. Vehicle Event Data Recorder (EDR) data was pulled and compared to data collected from independent instrumentation to determine the vehicle system accuracy in detecting targets, investigate timings, and understand the scope of data available to an agency investigating a failure. Images and data files are presented as an example of scope of output. Tests included several variable overlap tests, along with several tests specifically chosen due to compare performance across the operating design domain.

Bartholomew, Meredith, Heydinger, Gary

Efficient Sidewalk Route Planning on Aerial Images with Cost-Based A* and Mini-Max Objective Function

2025-01-8032

04/01/2025

With the growing diversification of modern urban transportation options, such as delivery robots, patrol robots, service robots, E-bikes, and E-scooters, sidewalks have gained newfound importance as critical features of High-Definition (HD) Maps. Since these emerging modes of transportation are designed to operate on sidewalks to ensure public safety, there is an urgent need for efficient and optimal sidewalk routing plans for autonomous driving systems. This paper proposed a sidewalk route planning method using a cost-based A* algorithm and a mini-max-based objective function for optimal routes. The proposed cost-based A* route planning algorithm can generate different routes based on the costs of different terrains (sidewalks and crosswalks), and the objective function can produce an efficient route for different routing scenarios or preferences while considering both travelling distance and safety levels. This paper’s work is meant to fill the gap in efficient route planning for

Bao, Zhibin, Lang, Haoxiang, Lin, Xianke

Longitudinal Analysis of Forward Blind Zone Changes in Popular Vehicle Models (1997–2023)

09-13-01-0005

03/26/2025

Background. In 2022, vulnerable road user (VRU) deaths in the United States increased to their highest level in more than 40 years. At the same time, increasing vehicle size and taller front ends may contribute to larger forward blind zones, but little is known about the role that visual occlusion may play in this trend. Goal. Researchers measured the blind zones of six top-selling light-duty vehicle models (one pickup truck, three SUVs, and two passenger cars) across multiple redesign cycles (1997–2023) to determine whether the blind zones were getting larger. Method. To quantify the blind zones, the markerless method developed by the Insurance Institute for Highway Safety was used to calculate the occluded and visible areas at ground level in the forward 180° arc around the driver at ranges of 10 m and 20 m. Results. In the 10-m forward radius nearest the vehicle, outward visibility declined in all six vehicle models measured across time. The SUV models showed up to a 58% reduction

Epstein, Alexander K., Brodeur, Alyssa, Drake, Juwon, Englin, Eric, Fisher, Donald L., Zoepf, Stephen, Mueller, Becky C., Bragg, Haden

Research on Automatic Emergency Braking Pedestrian System Considering Road Adhesion Coefficient

10-09-03-0022

03/08/2025

To further optimize the automatic emergency braking for pedestrian (AEB-P) control algorithm, this study proposes an AEB-P hierarchical control strategy considering road adhesion coefficient. First, the extended Kalman filter is used to estimate the road adhesion coefficient, and the recursive least square method is used to predict the pedestrian trajectory. Then, a safety distance model considering the influence factor of road adhesion coefficient is proposed to adapt to different road conditions. Finally, the desired deceleration is converted into the desired pressure and desired current to the requirements of the electric power-assisted braking system. The strategy is verified through the hardware-in-the-loop (HIL) platform; the simulation results show that the control algorithm proposed in this article can effectively avoid collision in typical scenarios, the safe distance of parking is between 0.61 m and 2.34 m, and the stop speed is in the range of 1.85 km/h–27.64 km/h.

Wang, Zijun, Wang, Liang, Ma, Liang, Sun, Yong, Li, Chenghao, Yang, Xinglong

Tunnel Traffic Anomaly Detection via Multi-Modal LLMs

2025-01-7129

02/21/2025

Tunnels play a crucial role in urban transportation, yet they frequently encounter various incidents during operation. Manual video inspections and sensor-based systems are inefficient and limited in accurately detecting and addressing these issues. The emergence of artificial intelligence has led to the development of object detection models such as YOLO, which have shown promise in real-time anomaly detection. However, these single-modality models achieve suboptimal results when dealing with complex events. Multi-modal large language models (LLMs) offer a potential solution, with their ability to process and understand information from different modalities. This paper develops a novel tunnel traffic anomaly detection method that combines single-modal models and multi-modal LLMs. The proposed system first employs YOLO for an initial detection round and then utilizes a specially designed LLM with an effective prompt and a data filtering strategy tailored for traffic tunnel scenarios

Liu, Hongyu, Zhou, Ruohan, Bai, Jiayang, Li, Yuanqi

Verification of Vulnerable Road User Pre-Crash Scenarios in Vision-Based Safety Applications

12-08-01-0004

01/10/2025

Verifying training datasets in vision-based vehicle safety applications is crucial to understanding the potential limitations of detection capabilities that may result in a higher safety risk. Vision-based pedestrian safety applications with crash avoidance technologies rely on prompt detection to avoid a crash. This research aims to develop a verification process for vulnerable road user safety applications with vision-based detection functionalities. It consists of reviewing the application’s safety requirements, identifying the target objects of detection in the operational design domain and pre-crash scenarios, and evaluating the safety risks qualitatively by examining the training dataset based on the results of pre-crash scenarios classification. As a demonstration, the process is implemented using open-source pedestrian tracking software, and the pre-crash scenarios are classified based on the trajectories of pedestrians in an example training dataset used in a pedestrian

Hsu, Chung-Jen

Lightweight Neural Network Model and Algorithm for Pedestrian Detection

12-08-03-0027

12/18/2024

Traditional pedestrian detection methods have poor robustness. Deep learning-based methods have shown high performance in recent years but rely on substantial computational resources. Developing a lightweight, deep learning-based pedestrian detection algorithm is essential for applying deep learning-based algorithms in resource-limited scenarios, such as driverless and advanced driver assistance systems. In this article, an improved model based on YOLOv3 called “YOLOPD” (You Only Look Once—Pedestrian Detection), is proposed. It is obtained by constructing a self-attentive module, introducing a CIOU (Complete Intersection over Union) loss function and a depth separated convolutional layer. Experimental results show that on the INRIA (National Institute for Research in Computer Science and Automation), Caltech, and CityPerson pedestrian dataset, the MR (miss rate) of the model YOLOPD is better than that of the original YOLOv3 model, and the number of parameters is reduced by about 1/3

Li, Shanglin, Wang, Qi Feng, Li, Ren Fa, Xiao, Juan

Skeletal Surrogate Metastructural Anisotropy Mimicry and the Influence of Fabrication Material

09-12-02-0009

11/12/2024

Human body models have been used for decades to inform efforts in promoting automobile occupant and pedestrian safety. However, many of these models fail to capture the intricacies of individual variability. Cadaveric subjects typically exceed representative age ranges and hence mechanics. Animal subjects typically require specific setups that stray from that which is representative of human crash scenarios. Computational models can only consider so many practical real-world variables. Artificial surrogates, dummies being popular among them, are very popular for reusability and robust data collection. However, even the biomechanically accurate skeletal surrogates available commercially are limited in that they do not consider human variability and skeletal microstructure local variability. The objective of the work herein is to assess computational methods of metastructural variability mimicry by fabrication material. We implement mimicry approaches focusing on bulk isotropic

Hezrony, Benjamin S., C. F. Lopes, Pedro, Brown, Philip J.

Enhancing Availability of Autonomous Shuttle Services: A Conceptual Approach toward Challenges and Opportunities

12-08-03-0023

10/09/2024

Autonomous vehicle technologies have become increasingly popular over the last few years. One of their most important application is autonomous shuttle buses that could radically change public transport systems. In order to enhance the availability of shuttle service, this article outlines a series of interconnected challenges and innovative solutions to optimize the operation of autonomous shuttles based on the experience within the Shuttle Modellregion Oberfranken (SMO) project. The shuttle shall be able to work in every weather condition, including the robustness of the perception algorithm. Besides, the shuttle shall react to environmental changes, interact with other traffic participants, and ensure comfortable travel for passengers and awareness of VRUs. These challenging situations shall be solved alone or with a teleoperator’s help. Our analysis considers the basic sense–plan–act architecture for autonomous driving. Critical components like object detection, pedestrian tracking

Dehghani, Ali, Salaar, Hamza, Srinivasan, Shanmuga Priya, Zhou, Lixian, Arbeiter, Georg, Lindner, Alisa, Patino-Studencki, Lucila

Micromobility and the Next Infrastructure Wave

EPR2024022

10/04/2024

US transportation infrastructure is dominated by the automobile form factor. Alternative modalities of movement, such as bikes, golf carts, and other micromobility options, have existed but are decidedly at a lower tier of importance. Even pedestrian access ways are not overly emphasized in the US transportation system. This lack of prioritization matches the reality that the vast majority of people and commerce moves through the motor vehicle infrastructure, with micromobility sitting in the periphery. Additionally, given the current lack of commercial applications, there are limited direct fee-based funding mechanisms connected to micromobility form factors. Micromobility and the Next Infrastructure Wave discusses how recent technological innovations in electrification, e-commerce, and autonomy are enabling a new class of micromobility devices which offer palpable value to consumers and enable significant commercial applications. Unlike the past, these micromobility devices now have

Razdan, Rahul

Comprehensive Study on Challenges to Introduce Autonomous Emergency Braking (AEBS) Feature in Indian Perspective

2024-01-3050

09/08/2024

India is a diverse country in terms of road conditions, road maintenance, traffic conditions, traffic density, quality of traffic which implies presence of agricultural tractors, bullock carts, autos, motor bikes, oncoming traffic in same lane, vulnerable road users (VRU) walking in the same lanes as vehicles, VRU’s crossing roads without using zebra crossings etc. as additional traffic quality deterrents in comparison to developed countries. The braking capacity of such vivid road users may not be at par with global standards due to their maintenance, loading beyond specifications, driver behavior which includes the tendency to maintain a close gap between the preceding vehicle etc. which may lead to incidents specifically of rear collisions due to the front vehicle going through an emergency braking event. The following paper provides a comprehensive study of the special considerations or intricacies in implementation of Autonomous Emergency Braking (AEBS) feature into Indian traffic

Kartheek, Nedunuri, Khare, Rashmita, Sathyamurthy, Sainathan, Manickam, Praveenkumar, Kuchipudi, Venkata Sai Pavan

Effect of A-Pillar Blind Spots on a Driver’s Pedestrian Visibility during Vehicle Turns at an Intersection

2024-22-0002

09/05/2024

This study aims to elucidate the impact of A-pillar blind spots on drivers’ visibility of pedestrians during left and right turns at an intersection. An experiment was conducted using a sedan and a truck, with a professional test driver participating. The driver was instructed to maintain sole focus on a designated pedestrian model from the moment it was first sighted during each drive. The experimental results revealed how the blind spots caused by A-pillars occur and clarified the relationship between the pedestrian visible trajectory distance and specific vehicle windows. The results indicated that the shortest trajectory distance over which a pedestrian remained visible in the sedan was 17.6 m for a far-side pedestrian model during a right turn, where visibility was exclusively through the windshield. For the truck, this distance was 20.9 m for a near-side pedestrian model during a left turn, with visibility through the windshield of 9.5 m (45.5% of 20.9 m) and through the

Matsui, Yasuhiro, Oikawa, Shoko

Toward Trustworthy Automated Driving through Qualitative Scene Understanding and Explanations

12-08-01-0003

07/12/2024

Understanding driving scenes and communicating automated vehicle decisions are key requirements for trustworthy automated driving. In this article, we introduce the qualitative explainable graph (QXG), which is a unified symbolic and qualitative representation for scene understanding in urban mobility. The QXG enables interpreting an automated vehicle’s environment using sensor data and machine learning models. It utilizes spatiotemporal graphs and qualitative constraints to extract scene semantics from raw sensor inputs, such as LiDAR and camera data, offering an interpretable scene model. A QXG can be incrementally constructed in real-time, making it a versatile tool for in-vehicle explanations across various sensor types. Our research showcases the potential of QXG, particularly in the context of automated driving, where it can rationalize decisions by linking the graph with observed actions. These explanations can serve diverse purposes, from informing passengers and alerting

Belmecheri, Nassim, Gotlieb, Arnaud, Lazaar, Nadjib, Spieker, Helge

Harmonizing Safety Regulations and Perception: A Simulation Methodology for AVAS System Design

2024-01-2915

06/12/2024

The development of an effective Acoustic Vehicle Alerting System (AVAS) is not solely about adhering to safety regulations; it also involves crafting an auditory experience that aligns with the expectations of vulnerable road users. To achieve this, a deep understanding of the acoustic transfer function is essential, as it defines the relationship between the sound emitter (the speaker inside the vehicle) and the receiver (the vulnerable road user). Maintaining the constancy of this acoustic transfer function is paramount, as it ensures that the sound emitted by the vehicle aligns with the intended safety cues and brand identity that is defined by the car manufacturer. In this research paper, three distinct methodologies for calculating the acoustic transfer function are presented: the classical Boundary Element method, the H-Matrix BEM accelerated method, and the Ray Tracing method. Furthermore, the paper encompasses an assessment of the correlation between these methods and their

Calloni, Massimiliano, Hadjit, Rabah, Salvekar, Pinak, Musser, Chad

Lighting and Visual Information for Vulnerable Road User (VRU) Safety: An Introductory Review

VRUSC-002-202405/03/2024

Injuries and fatalities among pedestrians, cyclists, scooterists, highway road workers, and safety and emergency personnel—often referred to as vulnerable road users (VRUs)—continue to rise at alarming rates worldwide. Emphasizing the urgent need for enhanced safety measures, this study, commissioned by the Vulnerable Road User Safety Consortium™ (VRUSC) and conducted by the Light and Health Research Center at the Icahn School of Medicine at Mount Sinai, evaluates the potential effectiveness of lighting and visual information systems in improving VRU safety. The white paper presents a synthesis of published research on lighting and markings from the perspective of both human drivers and machine vision systems. It identifies potential preliminary guidelines for the intensity, color, temporal, and spatial characteristics of lighting and visual information that can help prevent crashes involving VRUs. The study also highlights knowledge gaps that require further research, including the

Vulnerable Road Users Safety Consortium

Vehicle-in-Virtual-Environment Method for ADAS and Connected and Automated Driving Function Development, Demonstration and Evaluation

2024-01-1967

04/09/2024

The current approach for new Advanced Driver Assistance System (ADAS) and Connected and Automated Driving (CAD) function development involves a significant amount of public road testing which is inefficient due to the number miles that need to be driven for rare and extreme events to take place, thereby being very costly also, and unsafe as the rest of the road users become involuntary test subjects. A new development, evaluation and demonstration method for safe, efficient, and repeatable development, demonstration and evaluation of ADAS and CAD functions called Vehicle-in-Virtual –Environment (VVE) was recently introduced as a solution to this problem. The vehicle is operated in a large, empty, and flat area during VVE while its localization and perception sensor data is fed from the virtual environment with other traffic and rare and extreme events being generated as needed. The virtual environment can be easily configured and modified to construct different testing scenarios on

Cao, Xincheng, Chen, Haochong, Gelbal, Sukru Yaren, Aksun Guvenc, Bilin, Guvenc, Levent

Research on Design of Electric Vehicle Sound Synthesis Based on Frequency Shift Algorithm

2024-01-2335

04/09/2024

The active sound generation systems (ASGS) for electric vehicles (EVs) play an important role in improving sound perception and transmission in the car, and can meet the needs of different user groups for driving and riding experiences. The active sound synthesis algorithm is the core part of ASGS. This paper uses an efficient variable-range fast linear interpolation method to design a frequency-shifted and pitch-modified sound synthesis algorithm. By obtaining the operating parameters of EVs, such as vehicle speed, motor speed, pedal opening, etc., the original sound signal is interpolated to varying degrees to change the frequency of the sound signal, and then the amplitude of the sound signal is determined according to different driving states. This simulates an effect similar to the sound of a traditional car engine. Then, a dynamic superposition strategy is proposed based on the Hann window function. Through windowing and superposition processing of each sound signal segment

Yu, Shangbo, Xie, Liping, Lu, Chihua, Qian, Yushu, Liu, Zhien, Songze, Du

Sensor-Fused Low Light Pedestrian Detection System with Transfer Learning

2024-01-2043

04/09/2024

Objection detection using a camera sensor is essential for developing Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) vehicles. Due to the recent advancement in deep Convolution Neural Networks (CNNs), object detection based on CNNs has achieved state-of-the-art performance during daytime. However, using an RGB camera alone in object detection under poor lighting conditions, such as sun flare, snow, and foggy nights, causes the system's performance to drop and increases the likelihood of a crash. In addition, the object detection system based on an RGB camera performs poorly during nighttime because the camera sensors are susceptible to lighting conditions. This paper explores different pedestrian detection systems at low-lighting conditions and proposes a sensor-fused pedestrian detection system under low-lighting conditions, including nighttime. The proposed system fuses RGB and infrared (IR) thermal camera information. IR thermal cameras are used as they are

Thota, Bharath kumar, Somashekar, Karthik, Park, Jungme

Development of Predictive Model for Flexible Pedestrian Legform Impactor Injury

2024-01-2511

04/09/2024

Road accidents are a major concern worldwide and vulnerable road users make up more than half of the victims of road accident deaths. In order to combat this issue, several countries worldwide have mandated pedestrian safety test regulations viz., AIS100 & UN-R127. One of the requirements of the regulations is when Flexible Pedestrian Legform Impactor (Flex-PLI) is impacted onto the frontal structure of the vehicle at a speed of 40kmph, the Bending moment (BM) of tibia bone of Flex-PLI shall not exceed the regulatory limit of 340Nm. In this paper, we have built a statistical model for predicting the BM of tibia in Flex-PLI using regression analysis. 13 vehicles have been selected from all applicable vehicle categories viz., Sedan, hatchback, Coupe & SUV/MUV for this undertaking. An exhaustive analysis of the vehicle frontal structures and Flex-PLI test videos have been done to identify & measure the design parameters to be used as predictor variables. The vehicles have then been

Barbhuiya, Junaid Hassan, Jain, Subhav

Evaluating Vehicle Response Through Non-Traditional Pedestrian Automatic Emergency Braking Scenarios

2024-01-1975

04/09/2024

Pedestrian Automatic Emergency Braking (P-AEB) is a technology designed to avoid or reduce the severity of vehicle to pedestrian collisions. This technology is currently assessed and evaluated via EuroNCAP and similar procedures in which a pedestrian test target is crossing the road, walking alongside the road, or stationary in the forward vehicle travel path. While these assessment methods serve the purpose of providing cross-comparison of technology performance in a standardized set of scenarios, there are many scenarios which could occur which are not considered or studied. By identifying and performing non-EuroNCAP, non-standardized scenarios using similar methodology, the robustness of P-AEB systems can be analyzed. These scenarios help identify areas of further development and consideration for future testing programs. Three scenarios were considered as a part of this work: straight line approach, curved path approach, and parking lot testing. Exemplar tests were performed for

Bartholomew, Meredith, Helber, Nicholas, Heydinger, Gary, Zagorski, Scott

Evaluation of the Full-Frontal Crash Regulation for the M1 Category of Vehicles from an Indian Perspective

2024-01-2750

04/09/2024

Background: The Indian automobile industry, including the auto component industry, is a significant part of the country’s economy and has experienced growth over the years. India is now the world’s 3rd largest passenger car market and the world’s second-largest two-wheeler market. Along with the boon, the bane of road accident fatalities is also a reality that needs urgent attention, as per a study titled ‘Estimation of Socio-Economic Loss due to Road Traffic Accidents in India’, the socio-economic loss due to road accidents is estimated to be around 0.55% to 1.35% of India’s GDP [27] Ministry of road transport and highways (MoRTH) accident data shows that the total number of fatalities on the road are the highest (in number terms) in the world. Though passenger car occupant fatalities have decreased over the years, the fatalities of vulnerable road users are showing an increasing trend. India has committed to reduce road fatalities by 50% by 2030. In this context, the automotive

Mehta, Pooja, Prasad, Avinash, Srivastava, Aakash, Arora, Pankaj, Howlader, Ashim

Active Collision Avoidance System for E-Scooters in Pedestrian Environment

2024-01-2555

04/09/2024

In the dense fabric of urban areas, electric scooters have rapidly become a preferred mode of transportation. As they cater to modern mobility demands, they present significant safety challenges, especially when interacting with pedestrians. In general, e-scooters are suggested to be ridden in bike lanes/sidewalks or share the road with cars at the maximum speed of about 15-20 mph, which is more flexible and much faster than pedestrians and bicyclists. Accurate prediction of pedestrian movement, coupled with assistant motion control of scooters, is essential in minimizing collision risks and seamlessly integrating scooters in areas dense with pedestrians. Addressing these safety concerns, our research introduces a novel e-Scooter collision avoidance system (eCAS) with a method for predicting pedestrian trajectories, employing an advanced Long short-term memory (LSTM) network integrated with a state refinement module. This method predicts future trajectories by considering not just past

Yan, Xuke, Shen, Dan

Evaluating Safety Metrics for Vulnerable Road Users at Urban Traffic Intersections Using High-Density Infrastructure LiDAR System

2024-01-2641

04/09/2024

Ensuring the safety of vulnerable road users (VRUs) such as pedestrians, users of micro-mobility vehicles, and cyclists is imperative for the commercialization of automated vehicles (AVs) in urban traffic scenarios. City traffic intersections are of particular concern due to the precarious situations VRUs often encounter when navigating these locations, primarily because of the unpredictable nature of urban traffic. Earlier work from the Institute of Automated Vehicles (IAM) has developed and evaluated Driving Assessment (DA) metrics for analyzing car following scenarios. In this work, we extend those evaluations to an urban traffic intersection testbed located in downtown Tempe, Arizona. A multimodal infrastructure sensor setup, comprising a high-density, 128-channel LiDAR and a 720p RGB camera, was employed to collect data during the dusk period, with the objective of capturing data during the transition from daylight to night. In this study, we present and empirically assess the

Rath, Prabin Kumar, Harrison, Blake, Lu, Duo, Yang, Yezhou, Wishart, Jeffrey, Yu, Hongbin

Representative Cyclist Collision Injury Risk Distributions for a Dense-Urban US ODD Using Naturalistic Dash Camera Data

2024-01-2645

04/09/2024

Automated driving systems (ADS) are designed toward safely navigating the roadway environment, which also includes consideration of potential conflict with other road users. Of particular concern is understanding the cumulative risk associated with vulnerable road users (VRUs) conflicts and collisions. VRUs represent a population of road users that have limited protection compared to vehicle occupants. These severity distributions are particularly useful in evaluating ADS real-world performance with respect to the existing fleet of vehicles. The objective of this study was to present event severity distributions associated with vehicle-cyclist collisions within an urban naturalistic driving environment by leveraging data from third-party vehicles instrumented with forward-facing cameras and a sensor suite (accelerometer sampling at 20 Hz and GPS [variable sampling frequency]). From over 66 million miles of driving, 30 collision events were identified. A global optimization routine was

Campolettano, Eamon T., Scanlon, John M., Kusano, Kristofer D.

Integrating Machine Learning in Pedestrian Forensics: A Comprehensive Tool for Analysing Pedestrian Collisions

2024-01-2468

04/09/2024

Analysis of pedestrian-to-vehicle collisions can be complex due to the nature of the interaction and the physics involved. The scarcity of evidence like video evidence (from CCTV or dashcams), data from the vehicle's ECU, witness accounts, and physical evidence such as tyre marks, complicates the analysis of these incidents. In cases with limited evidence, current forensic methods often rely on prolonged inquiry processes or computationally intensive simulations. Without adequate data, accurately estimating pedestrian kinematics and addressing hit-and-run scenarios becomes challenging. This research provides an alternative approach to enhancing pedestrian forensic analysis based on machine learning (ML) algorithms trained on over 3000 multi-body computer simulations with a diverse set of vehicle profiles and pedestrian anthropometries. Leveraging information such as vehicle profile, damage, and pedestrian attributes like height and weight, the ML algorithm estimates essential

Shrinivas, Vadhiraj, Bastien, Christophe, Davies, Huw, Daneshkhah, Alireza, Hardwicke, Joseph, Neal-Sturgess, Clive, Lamaj, Albi

Assessing the Impact of Rubberized Asphalt on Reducing Hip Fracture Risk in Elderly Populations Using Human Body Models

09-12-01-0007

04/08/2024

Compared to other age groups, older adults are at more significant risk of hip fracture when they fall. In addition to the higher risk of falls for the elderly, fear of falls can reduce this population’s outdoor activity. Various preventive solutions have been proposed to reduce the risk of hip fractures ranging from wearable hip protectors to indoor flooring systems. A previously developed rubberized asphalt mixture demonstrated the potential to reduce the risk of head injury. In the current study, the capability of the rubberized asphalt sample was evaluated for the risk of hip fracture for an average elderly male and an average elderly female. A previously developed human body model was positioned in a fall configuration that would give the highest impact forces toward regular asphalt. Three different rubber contents with 14, 28, 33 weight percent (% wt.) were implemented as the ground alongside one regular non-rubberized (0%) asphalt mixture, one baseline, and one extra-compliant

Sahandifar, Pooya, Wallqvist, Viveca, Kleiven, Svein

Towards a New Approach for Reducing the Safety Validation Effort of Driving Functions Using Prediction Divergence

SAE-PP-0038403/09/2024

An essential component in the approval of advanced driver assistance systems (ADAS) and automated driving systems (ADS) is the quantification of residual risk, which demonstrates that hazardous behavior (HB) occurs less frequently than specified by a corresponding acceptance criterion. In the case of HB with high potential impact severity, only very low accepted frequencies of occurrence are tolerated. To avoid uncertainties due to abstractions and simplifications in simulations, the proof of the residual risk in systems such as advanced emergency braking systems (AEBS) is often partially or entirely implemented as system-level field test. However, the low rates and high confidence required, common for residual risk demonstrations, result in a significant disadvantage of these field tests: the long driving distance required. In this publication, the prediction divergence principle (PDP) is presented as an approach that has the potential to reduce the testing effort in the future

Betschinske, Daniel, Schrimpf, Malte, Lippert, Moritz, Peters, Steven

Modelling and Evaluation of Pedestrian Active Safety System Based on Accidents in India

2024-26-0013

01/16/2024

Many Vulnerable Road Users (VRUs) experience injuries and fatalities every year, making road safety a challenge in the World. According to the Ministry of Road Transport and Highway (MoRTH) during the year 2021, a total number of 4,12,432 road accidents have been reported in India, claiming 1,53,972 lives and causing injuries to 3,84,448 persons. In terms of road-user categories, the total fatality of the Pedestrian road-users was 18.9 per cent of persons killed in road accidents. One of the ways to handle the situation is to protect pedestrians utilizing active safety measures in the vehicle. In addition, active safety research heavily relies on perceptions of pre-crash scenarios. The objective of the study is to examine passenger car-to-pedestrian scenarios and model active safety system in a car to prevent or mitigate collisions. Road Accident Sampling System – India (RASSI) database is used for this research, which provided a comprehensive set of accident data describing the

Doshi, Urvilkumar HItendrabhai, Agrawal, Saurav, Muthanandam, Muthukumar, Yarramsetti, Karthik, Penumaka, Avinash, Kalakala, Vijaya Prakash

A Simulation Methodology to Design the AVAS System to Meet Safety Regulations and Create the Expected Perception for the Vulnerable Road User

2024-26-0230

01/16/2024

Designing an effective AVAS system, not only to meet safety regulations, but also to create the expected perception for the vulnerable road user, relies on knowledge of the acoustic transfer function between the sound actuator and the receiver. It is preferable that the acoustic transfer function be as constant as possible to allow transferring the sound designed by the car OEM to ensure the safety of vulnerable road users while conveying the proper brand image. In this paper three different methodologies for the acoustic transfer function calculations are presented and compared in terms of accuracy and calculation time: classic Boundary Element method, H-Matrix BEM accelerated method and Ray tracing method. An example of binaural listening experience at different certification positions in the modeled simulated space is also presented.

Calloni, Massimiliano, Hadjit, Rabah, Salvekar, Pinak, Musser, Chadwyck

Comprehensive Assessment of Driver Monitoring System for Commercial Vehicle Applications Using Innovative Lab Testing Approach

2024-26-0027

01/16/2024

The commercial vehicle sector (especially trucks) has major role in economic growth of a nation. With improving infrastructure, increasing number of commercial vehicles and growing amount of Vulnerable Road Users (VRUs) on roads, accidents are also increasing. As per RASSI (Road Accident Sampling System India) FY2016-21 database, commercial vehicles are involved in 43% of total accidents on Indian roads. One of the major causes of these accidents is Driver Drowsiness and Inattention (DDI) (approx. 10% contribution in total accidents). This paper describes novel driver-in-loop performance assessment methodology for comprehensive verification of Driver Monitoring System (DMS) for commercial vehicle application. Novelty lies in specification of test subjects, driving styles and variety of road traffic scenarios for verification of DMS system. Test setup is made modular to cater to different platform environments (Heavy, Intermediate, Light) with minor modifications. The test setup

Sudarshan, BV, Jarhad, Manoj, Dey, Susanta Kumar, Joshi, Kedar Shrikant, Gadekar, Ganesh

Research on Vulnerable Road User Detection Algorithm based on Improved Deep Learning

2023-01-7050

12/20/2023

This paper proposes a detection algorithm based on deep learning for Vulnerable Road Users such as pedestrians and cyclists, which is improved on the basis of YOLOv5 network model. (1) Aiming at the problems of low resolution and insufficient information for small targets, a multi-scale feature fusion method is adopted to integrate shallow features with deep features. In this way, the effective information of small target is enriched, and the accuracy of target detection is improved. (2) In view of the interference of image noise, background and other factors, the channel attention method is introduced to strengthen key features and suppress the interference of noise, which can improve the model's attention to small targets and enable the network to better identify blocked targets; (3) Aiming at the problem that the computing speed of the model is difficult to achieve real-time performance, a deep separable convolution optimization method is proposed to reduce the amount of computation

Yi, Zhenxing, Zhan, Zhenfei, Zhou, Guilin, Lv, Fengyao, Mao, Qing, Sun, Bowen

Initial Research Summation Overview: Vehicle-VRU Safety Landscape

VRUSC-001-202312/18/2023

This white paper is an examination of the increasing rate of injuries and deaths worldwide of a class of road users, often referred to as “vulnerable road users” (VRUs), with a focus on pedestrians, cyclists, scooterists, highway road workers, safety, and emergency personnel. The potential to leverage pragmatic, evidence-based technology countermeasures to reduce these collisions, and the severity of those that do occur, is also examined.

Vulnerable Road Users Safety Consortium

Pedestrian Intention Prediction and Style Recognition in Bird’s-Eye View

12-07-01-0008

11/16/2023

In this article, pedestrian crossing intention and pedestrian crossing style are studied by means of statistical theory and artificial neural network. Feature parameters such as the average speed of pedestrians, pedestrian attention to vehicles, and vehicle arrival speed are extracted before and during the time pedestrians cross the street from a bird’s-eye view. Based on these parameters, an artificial neural network is used to predict the pedestrian crossing intention. K-means statistical method was used to cluster the pedestrian crossing styles, and the results showed that clustering the crossing styles into three categories, conservative, cautious, and adventurous, has a better classification effect, and the crossing behaviors of different types of pedestrians were analyzed. A random forest-based model is used to identify pedestrian crossing styles, the prediction accuracy reaches 91.83% and the recognition accuracy reaches 93.3%. The research content of this article can provide

Li, Wenli, Wang, Mengxin, Gong, Xiaohao, Tang, Yuanhang

Letter from the Special Issue Editors

09-11-02-0009

09/20/2023

Letter from the Special Issue Editors

Mueller, Becky, Bautsch, Brian, Mansfield, Julie

Cooperative Driving Automation (CDA) Feature: Perception Status Sharing for Occluded Pedestrian Collision Avoidance

J3251_202308 (Current)

08/22/2023

This SAE Information Report develops a concept of operations (ConOps) to evaluate a cooperative driving automation (CDA) Feature for occluded pedestrian collision avoidance using perception status sharing. It provides a test procedure to evaluate this CDA Feature, which is suitable for proof-of-concept testing in both virtual and test track settings.

Cooperative Driving Automation(CDA) Committee

Ligaments Laxity and Elongation at Injury in Flexed knees during Lateral Impact Conditions

2022-22-0003

06/27/2023

The knee is one of the regions of interest for pedestrian safety assessment. Past testing to study knee ligament injuries for pedestrian impact only included knees in full extension and mostly focused on global responses. As the knee flexion angle and the initial ligament laxity may affect the elongation at which ligaments fail, the objectives of this study were (1) to design an experimental protocol to assess the laxity of knee ligaments before measuring their elongation at failure, (2) to apply it in paired knee tests at two flexion angles (10 and 45 degrees). The laxity tests combined strain gauges to measure bone strains near insertions that would result from ligament forces and a custom machine to exercise the knee in all directions. Failure was assessed using a four-point bending setup with additional degrees of freedom on the axial rotation and displacement of the femur. A template was designed to ensure that the two setups used the exact same starting position. The protocol was

Benadi, Sahar, Trosseille, Xavier, Petit, Philippe, Uriot, Jérôme, Lafon, Yoann, Beillas, Philippe

Effect of Tissue Erosion Modeling Techniques on Pedestrian Impact Kinematics

2022-22-0007

06/27/2023

The pedestrian is one of the most vulnerable road users and has experienced increased numbers of injuries and deaths caused by car-to-pedestrian collisions over the last decade. To curb this trend, finite element models of pedestrians have been developed to investigate pedestrian protection in vehicle impact simulations. While useful, modeling practices vary across research groups, especially when applying knee/ankle ligament and bone failure. To help better standardize modeling practices this study explored the effect of knee ligament and bone element elimination on pedestrian impact outcomes. A male 50th percentile model was impacted by three European generic vehicles at 30, 40, and 50 km/h. The pedestrian model was set to three element elimination settings: the “Off-model” didn’t allow any element erosion, the “Lig-model” allowed lower-extremity ligament erosion, and the “All-model” allowed lower-extremity ligament and bone erosion. Failure toggling had a significant effect on

Grindle, Daniel, Untaroiu, Costin

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