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Highway safety remains a significant concern, especially in mixed traffic scenarios involving heavy-duty vehicles (HDV) and smaller passenger cars. The vulnerability of HDVs following closely behind smaller cars is evident in incidents involving the lead vehicle, potentially leading to catastrophic rear-end collisions. This paper explores how automatic speed enforcement systems, using speed cameras, can mitigate risks for HDVs in such critical situations. While historical crash data consistently demonstrates the reduction of accidents near speed cameras, this paper goes beyond the conventional notion of crash occurrence reduction. Instead, it investigates the profound impact of driver behavior changes within desired travel speed distribution, especially around speed cameras, and their contribution to the safety of trailing vehicles, with a specific focus on heavy-duty trucks in accident-prone scenarios.

This paper details the advancements and outcomes of the NEXTCAR (Next-Generation Energy Technologies for Connected and Automated on-Road Vehicles) program, an initiative led by the Advanced Research Projects Agency-Energy (ARPA-E). The program focusses on harnessing the full potential of Connected and Automated Vehicle (CAV) technologies to develop advanced vehicle dynamic and powertrain control technologies (VD&PT). These technologies have shown the capability to reduce energy consumption by 20% in conventional and hybrid electric cars and trucks at automation levels L1-L3 and by 30% L4 fully autonomous vehicles. Such reductions could lead to significant energy savings across the entire U.S. vehicle fleet.

This paper presents an energy-optimal plan for the allocation of a heterogeneous fleet of delivery vehicles in a dynamic network of multiple distribution centers and fulfillment centers. Each distribution center with a heterogeneous fleet of delivery vehicles is considered as a hub connected with the fulfillment centers through the routes as spokes. The goal is to minimize the overall energy consumption of the fleet while meeting the demand of each of the fulfillment centers. To achieve this goal, the problem is divided into two sub-problems that are solved in a hierarchical way. Firstly, for each spoke, the optimal number of vehicles to be allocated from each hub is determined. Secondly, given the number of allocated delivery vehicles from a hub for each spoke, the optimal selection of vehicle type from the available heterogeneous fleet at the hub is done for each of spokes based on the energy requirement and the energy efficiency of the spoke under consideration.

Automated driving has become a very promising research direction with many successful deployments and the potential to reduce car accidents caused by human error. Automated driving requires automated path planning and tracking with the ability to avoid collisions as its fundamental requirement. Thus, plenty of research has been performed to achieve safe and time efficient path planning and to develop reliable collision avoidance algorithms. This paper uses a data-driven approach to solve the abovementioned fundamental requirement. Consequently, the aim of this paper is to develop Deep Reinforcement Learning (DRL) training pipelines which train end-to-end automated driving agents by utilizing raw sensor data. The raw sensor data is obtained from the Carla autonomous vehicle simulation environment here. The proposed automated driving agent learns how to follow a pre-defined path with reasonable speed automatically.

The ported shroud casing treatment for turbocharger compressors offers a wider operating flow range, elevated boost pressures at low compressor mass flow rates, and reduced broadband whoosh noise in spark-ignition internal combustion engine applications. However, the casing treatment elevates tonal noise at the blade-pass frequency (BPF). Typical rotational speeds of compressors employed in practice push BPF noise to high frequencies, which then promote multi-dimensional acoustic wave propagation within the compressor ducting. As a result, in-duct acoustic measurements become sensitive to the angular location of pressure transducers on the duct wall. The present work utilizes a steady-flow turbocharger gas stand featuring a unique rotating compressor inlet duct to quantify the variation of noise measured around the duct at different angular positions.

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.

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.

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.

This study aims to provide a set of reference post-mortem human subject tests which can be used, with easily reproducible test conditions, for developing and/or validating pedestrian dummies and computational human body models against a road vehicle. An adjustable generic buck was first developed to represent vehicle front-ends. It was composed of four components: two steel cylindrical tubes screwed on rigid supports in V-form represent the bumper and spoiler respectively, a quarter of a steel cylindrical tube represents the bonnet leading edge, and a steel plate represents the bonnet. These components were positioned differently to represent three types of vehicle profile: a sedan, a SUV and a van. Eleven post-mortem human subjects were then impacted laterally in a mid-gait stance by the bucks at 40 km/h: three tests with the sedan, five with the SUV, and three with the van.

The Ohio State University EcoCAR 3 team is building a plug-in hybrid electric vehicle (PHEV) post-transmission parallel 2016 Chevrolet Camaro. With the end-goal of improving fuel economy and reducing tail pipe emissions, the Ohio State Camaro has been fitted with a 32 kW alternator-starter belt coupled to a 119 kW 2.0L GDI I4 engine that runs on 85% ethanol (E85). The belted alternator starter (BAS) which aids engine start-stop operation, series mode and torque assist, is powered by an 18.9 kWh Lithium Iron Phosphate energy storage system, and controlled by a DC-AC inverter/controller. This report details the modeling, calibration, testing and validation work done by the Ohio State team to fast track development of the BAS system in Year 2 of the competition.

Despite the increasing knowledge of the thorax mechanics, the effects of inter-individual differences on the mechanical response are difficult to take into account. Several methods are available in the literature to refine the biofidelity corridors or to extrapolate them to other populations (eg: children, small females, large males). Because of the lack of concrete cases, the relevance of the assumptions is rarely investigated. In 2014, Baudrit et al. published data on thorax dynamic responses of small female and midsize male Post Mortem Human Subjects in side and forward oblique impact tests. The impactor mass was 23.4 kg for all the tests and the nominal impact speed was 4.3 m/s. The diameter of the rigid disk was 130 and 152 mm respectively for the small female specimens and for the midsize male specimens. The authors found that the maximum impact force was a function of the total body mass for each loading.

Finite Element Human Body Models (HBM) have become powerful tools to study the response to impact. However, they are typically only developed for a limited number of sizes and ages. Various approaches driven by control points have been reported in the literature for the non-linear scaling of these HBM into models with different geometrical characteristics. The purpose of this study is to compare the performances of commonly used control points based interpolation methods in different usage scenarios. Performance metrics include the respect of target, the mesh quality and the runability. For this study, the Kriging and Moving Least square interpolation approaches were compared in three test cases. The first two cases correspond to changes of anthropometric dimensions of (1) a child model (from 6 to 1.5 years old) and (2) the GHBMC M50 model (Global Human Body Models Consortium, from 50th to 5th percentile female).

The human thermal comfort, which has been a subject of extensive research, is a principal objective of the automotive climate control system. Applying the results of research studies to the practical problems require quantitative information of the thermal environment in the passenger compartment of a vehicle. The exposure to solar radiation is known to alter the thermal environment in the passenger compartment. A photovoltaic-cell based sensor is commonly used in the automotive climate control system to measure the solar radiation exposure of the passenger compartment of a vehicle. The erroneous information from a sensor however can cause thermal discomfort to the occupants. The erroneous measurement can be due to physical or environmental parameters. Shading of a solar sensor due to the opaque vehicle body elements is one such environmental parameter that is known to give incorrect measurement.

Hydraulic bushings are widely used in vehicle applications, such as suspension and sub-frame systems, for motion control and noise and vibration isolation. To study the dynamic properties of such devices, a controlled laboratory bushing prototype is designed and fabricated. This device has the capability of varying different combinations of long and short flow passages and flow restriction elements. Transient experiments with step-up and step-down excitations are conducted on the prototype, and the transmitted force responses are measured. The transient properties of several commonly seen hydraulic bushing designs are experimentally studied. Analytical models for bushings with different design features are developed based on the linear system theory. System parameters are then estimated for step responses based on theory and measurements. Finally, the linear models are utilized to analyze the step force measurements, from which some nonlinearities of the bushing system are identified.

The engine start-up process introduces speed-dependent transient vibration problems in ground vehicle drivelines as the torsional system passes through the critical speeds during the acceleration process. Accordingly, a numerical study is proposed to gain more insights about this transient vibration issue, and the focus is on nonlinear analysis. First, a new nonlinear model of a multi-staged clutch damper is developed and validated by a transient experiment. Second, a simplified nonlinear torsional oscillator model with the multi-staged clutch damper, representing the low frequency dynamics of a typical vehicle driveline, is developed. The flywheel velocity measured during the typical engine start-up process is utilized as an excitation. The envelope function of the speed-dependent response amplification is estimated via the Hilbert transform technique. Finally, the envelope function is effectively utilized to examine the effect of multi-staged clutch damper properties.

This article studies the effects of tooth surface waviness and sliding friction on the dynamics and radiated structure-borne noise of a spur gear pair. This study is conducted using an improved gear dynamics model while taking into account the sliding frictional contact between meshing teeth. An analytical six-degree-of-freedom (6DOF) linear time varying (LTV) model is developed to predict system responses and bearing forces. The time varying mesh stiffness is calculated using a gear contact mechanics code. A Coulomb friction model is used to calculate the sliding frictional forces. Experimental measurements of partial pressure to acceleration transfer functions are used to calculate the radiated structure-borne noise level. The roles of various time-varying parameters on gear dynamics are analyzed (for a specific example case), and the predictions from the analytical model are compared with prior literature.

Several statistical methods are currently used to build injury risk curves in the biomechanical field. These methods include the certainty method (Mertz et al. 1996), Mertz/Weber method (Mertz and Weber 1982), logistic regression (Kuppa et al. 2003, Hosmer and Lemeshow 2000), survival analysis with Weibull distribution (Kent et al. 2004, Hosmer and Lemeshow 2000), and the consistent threshold estimate (CTE) (Nusholtz et al. 1999, Di Domenico and Nusholtz 2005). There is currently no consensus on the most accurate method to be used and no guidelines to help the user to choose the more appropriate one. Injury risk curves built for the WorldSID 50th side impact dummy with these different methods could vary significantly, depending on the sample considered (Petitjean et al. 2009). As a consequence, further investigations were needed to determine the fields of application of the different methods and to recommend the best statistical method depending on the biomechanical sample considered.

The development of the WorldSID 50th percentile male dummy was initiated in 1997 by the International Organization for Standardization (ISO/SC12/TC22/WG5) with the objective of developing a more biofidelic side impact dummy and supporting the adoption of a harmonized dummy into regulations. More than 45 organizations from all around the world have contributed to this effort including governmental agencies, research institutes, car manufacturers and dummy manufacturers. The first production version of the WorldSID 50th male dummy was released in March 2004 and demonstrated an improved biofidelity over existing side impact dummies. Full-scale vehicle tests covering a wide range of side impact test procedures were performed worldwide with the WorldSID dummy. However, the vehicle safety performance could not be assessed due to lack of injury risk curves for this dummy. The development of these curves was initiated in 2004 within the framework of ISO/SC12/TC22/WG6 (Injury criteria).

A multi-chamber silencer is designed by a computational approach to suppress the turbocharger whoosh noise downstream of a compressor in an engine intake system. Due to the significant levels and the broadband nature of the source spanning over 1.5 – 3.5 kHz, three Helmholtz resonators are implemented in series. Each resonator consists of a chamber and a number of slots, which can be modeled as a cavity and neck, respectively. Their target resonance frequencies are tuned using Boundary Element Method to achieve an effective noise reduction over the entire frequency range of interest. The predicted transmission loss of the silencer is then compared with the experimental results from a prototype in an impedance tube setup. In view of the presence of rapid grazing flow, these silencers may be susceptible to whistle-noise generation. Hence, the prototype is also examined on a flow bench at varying flow rates to assess such flow-acoustic coupling.