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Autonomous vehicle technology has been developing rapidly in recent years. Vehicle parametric uncertainty in the vehicle model, variable time delays in the CAN bus based sensor and actuator command interfaces, changes in vehicle sped, sensitivity to external disturbances like side wind and changes in road friction coefficient are factors that affect autonomous driving systems like they have affected ADAS and active safety systems in the past. This paper presents a robust control architecture for automated driving systems for handling the abovementioned problems. A path tracking control system is chosen as the proof-of-concept demonstration application in this paper. A disturbance observer (DOB) is embedded within the steering to path error automated driving loop to handle uncertain parameters such as vehicle mass, vehicle velocities and road friction coefficient and to reject yaw moment disturbances.

Future SAE Level 4 and Level 5 autonomous vehicles will require novel applications of localization, perception, control and artificial intelligence technology in order to offer innovative and disruptive solutions to current mobility problems. This paper concentrates on low speed autonomous shuttles that are transitioning from being tested in limited traffic, dedicated routes to being deployed as SAE Level 4 automated driving vehicles in urban environments like college campuses and outdoor shopping centers within smart cities. The Ohio State University has designated a small segment in an underserved area of campus as an initial autonomous vehicle (AV) pilot test route for the deployment of low speed autonomous shuttles. This paper presents initial results of ongoing work on developing solutions to the localization and perception challenges of this planned pilot deployment.

Posterior cruciate ligament (PCL) injuries, although rarely life threatening, affect the quality of life of the person who sustains the injury. The PCL is the primary restraint to posterior tibial translation and can be injured when the tibia moves posteriorly relative to the femur. This type of injury is common in frontal crashes where the tibia may impact the dashboard or steering column. To quantify what happens during dynamic loading of the tibial plateau, isolated cadaveric lower limbs (n = 14) were impacted at dynamic rates with a linear pneumatic ram. During the testing, a static load was applied to the quadriceps tendon to simulate active musculature. Forces as well as the stretch of the PCL were measured. The most common injuries were tibia fractures and PCL tears. The stiffness for the tests at impact velocities of 1.4 and 2.9 m/s were on average 120 N/mm and 141N/mm, respectively. A trend towards increasing femur force with increasing velocity was found.

This study was performed to showcase the possible applications of the Hardware-in-the-loop (HIL) simulation environment developed by the National Highway Traffic Safety Administration (NHTSA), to test heavy truck crash avoidance safety systems. In this study, the HIL simulation environment was used to recreate a simulation of an actual accident scenario involving a single tractor semi-trailer combination. The scenario was then simulated with and without an antilock brake system (ABS) and electronic stability control (ESC) system to investigate the crash avoidance potential afforded by the tractor equipped with the safety systems. The crash scenario was interpreted as a path-following problem, and three possible driver intended paths were developed from the accident scene data.

The EcoCAR 2 team at the Ohio State University has designed an extended-range electric vehicle capable of 44 miles all-electric range, which features a 18.9-kWh lithium-ion battery pack with range extending operation in both series and parallel modes made possible by a 1.8-L ethanol (E85) engine and a 6-speed automated manual transmission. This vehicle is designed to reduce fuel consumption, with a utility factor weighted fuel economy of 50 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This report documents the team's refinement work on the vehicle during Year 3 of the competition, including vehicle improvements, control strategy calibration and dynamic vehicle testing, culminating in a 99% buy off vehicle that meets the goals set forth by the team. This effort was made possible through support from the U.S. Department of Energy, General Motors, The Ohio State University, and numerous competition and local sponsors.

With the advent of increasing autonomous vehicles on public roads, the safety of vulnerable road users such as pedestrians, cyclists, etc. has never been more important. These especially include Blind or Visually Impaired (BVI) pedestrians who face difficulty in making confident decisions in road crossings without the help of accessible pedestrian signals (APS). This paper addresses some of the safety measures that can be taken to improve and assess the safety of BVI pedestrians in a controlled environment like a BVI school campus where autonomous vehicles are operated. The majority of research on autonomous vehicle safety does not consider the edge cases of encounters with BVI pedestrians. Based on this motivation, requirements and characteristics of Non-BVI and BVI pedestrians have been stated along with the motion models used to predict their future movements. Existing tools based on Bayesian multi-model filters were used for pedestrian tracking and motion predictions.

Roundabout is a unique approach of managing traffic at intersections because it relies on driver’s instincts of safety. Roundabouts are considered safer than other ways of intersection traffic management due to low speed limits, smoother merging, and reduced fatal accidents. Despite their benefits and increasing usage, there is lack of clear understanding of the roundabouts, particularly due to scarcity of data and simulation models and the complexity of the structure. Real-time and offline traffic data recorded at a roundabout provides a basis for 1) identification of the safety issues, 2) understanding unexpected and risky driver behavior, 3) proposing potential mobility solutions, and 4) developing simulation models. The processed data may be used in controlling metered roundabouts, communicating with connected and automated vehicles (CAVs) etc. In this paper an approach to obtain useful traffic information from video feed data at a roundabout is presented.

Automated driving systems (ADS) are one of the key modern technologies that are changing the way we perceive mobility and transportation. In addition to providing significant access to mobility, they can also be useful in decreasing the number of road accidents. For these benefits to be realized, candidate ADS need to be proven as safe, robust, and reliable; both by design and in the performance of navigating their operational design domain (ODD). This paper proposes a multi-pronged approach to evaluate the safety performance of a hypothetical candidate system. Safety performance is assessed through using a set of test cases/scenarios that provide substantial coverage of those potentially encountered in an ODD. This systematic process is used to create a library of scenarios, specific to a defined domain. Beginning with a system-specific ODD definition, a set of core competencies are identified.

This study is focused on exploring the possibilities of using camera and route planner images for autonomous driving in an end-to-mid learning fashion. The overall idea is to clone the humans’ driving behavior, in particular, their use of vision for ‘driving’ and map for ‘navigating’. The notion is that we humans use our vision to ‘drive’ and sometimes, we also use a map such as Google/Apple maps to find direction in order to ‘navigate’. We replicated this notion by using end-to-mid imitation learning. In particular, we imitated human driving behavior by using camera and route planner images for predicting the desired waypoints and by using a dedicated control to follow those predicted waypoints. Besides, this work also places emphasis on using minimal and cheaper sensors such as camera and basic map for autonomous driving rather than expensive sensors such Lidar or HD Maps as we humans do not use such sophisticated sensors for driving.

Markings or observable anomalies on vehicle seat belt restraint systems can be classified into two categories: (1) Those caused by collision forces, or “loading marks” and (2) those created by noncollision situations, or “normal usage marks” [1]. A survey was conducted of both crash tested and non-crash tested vehicles in order to collect data on both categories of markings. This paper examines and analyzes the markings caused by both collision and noncollision load scenarios in order to illustrate and evaluate their unique differences as well as provide a general pattern of severity relative to different loading conditions.

In the field of accident reconstruction, there has been a significant amount of effort devoted to the calculation and derivation of vehicle crush energy and vehicle stiffness. Crush energy is usually calculated with a crush profile and crush stiffness. But, oftentimes, crush profiles and/or crush stiffnesses are not available and accident constructionists face the situation of insufficient information. In some such cases, the force balance method can be used to reduce the uncertainty. The method follows from Newton's Third Law, i.e., the impact force exerted on one vehicle is balanced by the force exerted on the other vehicle. With the help of this method, crush profile or crush stiffness can be derived. As a result, the crush energy can then be calculated with improved accuracy. This ultimately increases the accuracy of the overall accident reconstruction. In this paper, examples will be given to illustrate the use of such a methodology.

The Elderly Female Dummy (EFD) is an omni-directional ATD developed to represent a vulnerable population. The EFD it is able to be 3D printed and quickly altered to meet design requirements. A recent side impact sled test series suggested that small, elderly females may be at risk of thoracic injuries in side impact crashes due to combined loading from the belt pre-tensioner and side airbag. The EFD was altered to add four IR-TRACCs to the thoracic region to allow both x-axis and y-axis displacement to be evaluated in a similar test. While the IR-TRACCs did record the displacement due to combined loading, the rate of displacement and timing of the peak displacements did not match external chestband outputs. The next step for the EFD is to revise the locations of IRTRACCs in the thorax and begin component testing in lateral and frontal directions to improve thoracic biofidelity.

The goal of this study is to evaluate both the internal and external biofidelity of existing rear impact anthropomorphic test devices (BioRID II, RID3D, Hybrid III 50th) in two moderate-speed rear impact sled test conditions (8.5g, 17 km/h; 10.5g, 24 km/h) by quantitatively comparing the ATD responses to biomechanical response targets developed from PMHS testing in a corresponding study. The ATDs and PMHS were tested in an experimental seat system that is capable of simulating the dynamic seat back rotation response of production seats. The experimental seat contains a total of fourteen load cells installed such that external loads from the ATDs and PMHS can be measured to evaluate external biofidelity. The PMHS were instrumented to correspond to the instrumentation contained in the ATDs so that direct comparison between ATDs and PMHS could be made to evaluate internal biofidelity.

Anthropomorphic test devices (ATDs) should accurately depict head kinematics in crash tests, and thoracic spine properties have been demonstrated to affect those kinematics. To investigate the relationships between thoracic spine system dynamics and upper thoracic kinematics in crash-level scenarios, three adult post-mortem human subjects (PMHS) were tested in both Isolated Segment Manipulation (ISM) and sled configurations. In frontal sled tests, the T6-T8 vertebrae of the PMHS were coupled through a novel fixation technique to a rigid seat to directly measure thoracic spine loading. Mid-thoracic spine and belt loads along with head, spine, and pectoral girdle (PG) displacements were measured in 12 sled tests conducted with the three PMHS (3-pt lap-shoulder belted/unbelted at velocities from 3.8 - 7.0 m/s applied directly through T6-T8).

The objectives of this study were to obtain biomechanical responses of post mortem human subjects (PMHS) by subjecting them to two moderate-speed rear impact sled test conditions (8.5g, 17 km/h; 10.5g, 24 km/h) while positioned in an experimental seat system, and to create biomechanical targets for internal and external biofidelity evaluation of rear impact ATDs. The experimental seat was designed to measure external loads on the head restraint (4 load cells), seat back (6 load cells), and seat pan (4 load cells) such that subject dynamic interaction with the seat could be evaluated. This seat system was capable of simulating the dynamic characteristics of modern vehicle seat backs by considering the moment-rotation properties of a typical passenger vehicle, thus providing a more realistic test environment than using a rigid seat with a non-rotating seat back as done in previous studies.

Past studies have found that a pressure based injury risk function was the best predictor of liver injuries due to blunt impacts. In an effort to expand upon these findings, this study investigated the biomechanical responses of the abdomen of post mortem human surrogates (PMHS) to high-speed seatbelt loading and developed external response targets in conjunction with proposing an abdominal injury criterion. A total of seven unembalmed PMHS, with an average mass and stature of 71 kg and 174 cm respectively were subjected to belt loading using a seatbelt pull mechanism, with the PMHS seated upright in a free-back configuration. A pneumatic piston pulled a seatbelt into the abdomen at the level of the umbilicus with a nominal peak penetration speed of 4.0 m/s. Pressure transducers were placed in the re-pressurized abdominal vasculature, including the inferior vena cava (IVC) and abdominal aorta, to measure internal pressure variation during the event.

High-speed biplane x-ray was used to research the kinematics of the small intestine in response to seatbelt loading. Six driver-side 3-point seatbelt simulations were conducted with the lap belt routed superior to the pelvis of six unembalmed human cadavers. Testing was conducted with each cadaver perfused, ventilated, and positioned in a fixed-back configuration with the spine angled 30° from the vertical axis. Four tests were conducted with the cadavers in an inverted position, and two tests were conducted with the cadavers upright. The jejunum was instrumented with radiopaque markers using a minimally-invasive, intraluminal approach without inducing preparation-related damage to the small intestine. Tests were conducted at a target peak lap belt speed of 3 m/s, resulting in peak lap belt loads ranging from 5.4-7.9 kN. Displacement of the radiopaque markers was recorded using high-speed x-ray from two perspectives.

When the Hybrid III 10-year old (HIII-10C) anthropomorphic test device (ATD) was adopted into Code of Federal Regulations (CFR) 49 Part 572 as the best available tool for evaluating large belt-positioning booster seats in Federal Motor Vehicle Safety Standard (FMVSS) No. 213, NHTSA stated that research activities would continue to improve the performance of the HIII-10C to address biofidelity concerns. A significant part of this effort has been NHTSA’s in-house development of the Large Omnidirectional Child (LODC) ATD. This prototype ATD is comprised of (1) a head with pediatric mass properties, (2) a neck that produces head lag with Z-axis rotation at the atlanto-occipital joint, (3) a flexible thoracic spine, (4) multi-point thoracic deflection measurement capability, (5) skeletal anthropometry representative of a seated child, and (6) an abdomen that can directly measure belt loading.

Interest in pedestrian head injury has prompted a need to measure the potential of head injury resulting from vehicular impacts. A variety of head impactors have been developed to fulfill this measurement need. A protocol has been developed by the International Harmonization Research Activity (IHRA) to use head impactor measurements to predict head injury. However, the effect of certain characteristics of the various head impactors on the measurement procedure is not well understood. This includes the location of the accelerometers within the head-form and testing the head-form under the variety of conditions necessary to establish its global performance. To address this problem, a simple model of the IHRA head-form has been developed. This model was created using MADYMO© and consists of a solid sphere with a second sphere representing the vinyl covering. Stiffness and damping characteristics of the vinyl covering were determined analytically from drop test data of an IHRA head-form.

The International Harmonization Research Activities Pedestrian Safety Working Group (IHRA PSWG) has proposed design requirements for two head-forms for vehicle hood (bonnet) impact testing. This paper discusses the development of MADYMO models representing the IHRA adult and child head-forms, validation of the models against laboratory drop tests, and assessment of the effect of IHRA geometric and mass constraints on the model response by conducting a parameter sensitivity analysis. The models consist of a multibody rigid sphere covered with a finite element modeled vinyl skin. The most important part in developing the MADYMO head-form models was to experimentally determine the material properties of the energy-absorbing portion of the head-form (vinyl skin) and incorporate these properties into MADYMO using a suitable material model. Three material models (linear isotropic, viscoelastic, hyperelastic) were examined.