Mercedes-Benz Research and Development North America (United States)

Vehicular environments impose a set of new requirements on today's wireless communication systems. Vehicular safety communications applications cannot tolerate long connection establishment delays before being enabled to communicate with other vehicles encountered on the road. Similarly, non-safety applications also demand efficient connection setup with roadside stations providing services (e.g. digital map update) because of the limited time it takes for a car to drive through the coverage area. Additionally, the rapidly moving vehicles and complex roadway environment present challenges at the PHY level. The IEEE 802.11 standard body is currently working on a new amendment, IEEE 802.1 lp, to address these concerns. This document is named wireless access in vehicular environment, also known as WAVE. As of writing, the draft document for IEEE 802.11p is making progress and moving closer towards acceptance by the general IEEE 802.11 working group. It is projected to pass letter ballot in the first half of 2008. This paper provides an overview of the latest draft proposed for IEEE 802.11p. It is intended to provide an insight into the reasoning and approaches behind the document.

This paper proposes a novel approach to health monitoring and multifault detection in permanent magnet synchronous machines using direct flux measurement with search coils. Unlike other spectrum-based fault detection schemes, only the fundamental frequency component of the measured voltage is utilized for fault detection. Therefore, the performance of the proposed scheme is not affected by nonstationary speed or harmonics introduced by the power supply. In addition, location of interturn short circuits and direction of static eccentricity can be detected, which have never been done by any other scheme. In spite of the invasive nature of the technique, it is very suitable for mission-critical applications and emerging applications such as off-shore wind turbines, hybrid vehicle technology, and military applications, where early detection of faults is of paramount importance. 2-D simulations using finite element analysis have been presented to validate the proposed method under different operating conditions. Experimental introduction of stator interturn short circuit, demagnetization, and static eccentricity has been discussed, and the proposed scheme is experimentally implemented to examine its effectiveness.

This paper answers a simple but important question in VANET research: what is the optimal data rate to be used in DSRC-based vehicle safety communications? While it is generally accepted that the default choice is 6 Mbps, this assumption is not rooted in strong technical considerations. This paper provides a systematic evaluation of optimized data rates choices in a variety of scenarios. The answer found enables researchers to generally eliminate one dimension of complexity in relevant VANET studies. Additionally, the methodology used in this paper is possibly as interesting as the conclusion.

Vehicle Safety Communications (VSC) is advancing rapidly towards product development and field testing. While a number of possible solutions have been proposed, the question remains open as how such a system will address the issue of scalability in its actual deployment. This paper presents a design methodology for congestion control in VSC as well as the description and evaluation of a resulting rate adaption oriented protocol named PULSAR. We start with a list of design principles reflecting the state of the art that define why and how vehicles should behave while responding to channel congestion in order to ensure fairness and support the needs of safety applications. From these principles, we derive protocol building blocks required to fulfill the defined objectives. Then, the actual protocol is described and assessed in detail, including a discussion on the intricate features of channel load assessment, rate adaptation and information sharing. A comparison with other state-of-the-art protocols shows that “details matter” with respect to the temporal and spatial dimensions of the protocol outcome.

Proposals for experiments in quantum chemistry on quantum computers leverage the ability to target a subset of degrees of freedom containing the essential quantum behavior, sometimes called the active space. This approximation allows one to treat more difficult problems using fewer qubits and lower gate depths than would otherwise be possible. However, while this approximation captures many important qualitative features, it may leave the results wanting in terms of absolute accuracy (basis error) of the representation. In traditional approaches, increasing this accuracy requires increasing the number of qubits and an appropriate increase in circuit depth as well. Here we explore two techniques requiring no additional qubits or circuit depth that are able to remove much of this approximation in favor of additional measurements. The techniques are constructed and analyzed theoretically, and some numerical proof-of-concept calculations are shown. As an example, we show how to achieve the accuracy of a 20-qubit representation using only four qubits and a modest number of additional measurements for a hydrogen molecule. We close with an outlook on the impact such techniques may have on both near-term and fault-tolerant quantum simulations.

This paper provides an overview of IEEE 1609.4, a work in progress standard for multi-channel operations over the 5.9 GHz Dedicated Short Range Communications (DSRC) spectrum. In the U.S., the DSRC spectrum is organized into several channels. IEEE 1609.4 defines a time-division scheme for DSRC radios to alternately switch within these channels to support different applications concurrently. We describe the main features of IEEE 1609.4 in detail and discuss the main concerns with the original protocol design. In particular, we focus on those issues that can have a significant impact on vehicle safety communications. While IEEE 1609.4 is currently being updated and revised, this paper is intended to contribute to the technical discussions, and to bring attention to the most relevant and critical issues. This paper also contains results from software simulations conducted to study vehicle safety communications under stressful but realistic conditions. These results confirm concerns for the currently proposed scheme and provide a motivation for updating and revising the standard.

PS23 (LPPS23) has been reported to delay some age-related disorders. Therefore, here we investigated whether LPPS23 decelerates age-related muscle loss and its underlying mechanism. Female senescence-accelerated mouse prone-8 (SAMP8) mice were divided into three groups (n=6 each): non-aging (16-week-old), control (28-week-old), and PS23 (28-week-old) groups. The control and PS23 groups were given saline and LPPS23, respectively. We evaluated the effects of LPPS23 by analyzing body weight and composition, muscle strength, protein uptake, mitochondrial function, reactive oxygen species (ROS), antioxidant enzymes, and inflammation-related cytokines. LPPS23 significantly attenuated age-related decreases of muscle mass and strength. Compared to the control group, the non-aging and PS23 groups exhibited higher mitochondrial function, IL10, antioxidant enzymes, and protein uptake. Moreover, inflammatory cytokines and ROS were lower in the non-aging and PS23 groups than the control group. Taken together, LPPS23 extenuated sarcopenia progression during aging; this effect might have been enacted by preserving the mitochondrial function via reducing age-related inflammation and ROS and by retaining protein uptake in the SAMP8 mice.

Social interactions often have major fitness consequences, but little is known about how specific interacting phenotypes affect the strength of natural selection. Social influences on the evolutionary process can be assessed using a multilevel selection approach that partitions the effects of social partner phenotypes on fitness (referred to as social or group selection) from those of the traits of a focal individual (nonsocial or individual selection). To quantify the contribution of social selection to total selection affecting a trait, the patterns of phenotypic association among interactants must also be considered. We estimated selection gradients on male body size in a wild population of forked fungus beetles (Bolitotherus cornutus). We detected positive nonsocial selection and negative social selection on body size operating through differences in copulation success, indicating that large males with small social partners had highest fitness. In addition, we found that, in low-density demes, the phenotypes of focal individuals were negatively correlated with those of their social partners. This pattern reversed the negative effect of group selection on body size and led to stronger positive selection for body size. Our results demonstrate multilevel selection in nature and stress the importance of considering social selection whenever conspecific interactions occur nonrandomly.

We estimate the resources required in the fusion-based quantum computing scheme to simulate electrolyte molecules in Li-ion batteries on a fault-tolerant, photonic quantum computer. We focus on the molecules that can provide practical solutions to industrially relevant problems. Certain fault-tolerant operations require the use of single-qubit ``magic states'' prepared by dedicated ``magic state factories'' (MSFs). Producing and consuming magic states in parallel is typically a prohibitively expensive task, resulting in the serial application of fault-tolerant gates. However, for the systems considered, the MSF constitutes a negligible fraction of the total footprint of the quantum computer, allowing for the use of multiple MSFs to produce magic states in parallel. We suggest architectural and algorithmic techniques that can accommodate such a capability. We propose a method to consume multiple magic states simultaneously, which can potentially lead to an order of magnitude reduction in the computational runtime without additional expense in the footprint.

In this paper we present Semantic Stixels, a novel vision-based scene model geared towards automated driving. Our model jointly infers the geometric and semantic layout of a scene and provides a compact yet rich abstraction of both cues using Stixels as primitive elements. Geometric information is incorporated into our model in terms of pixel-level disparity maps derived from stereo vision. For semantics, we leverage a modern deep learning-based scene labeling approach that provides an object class label for each pixel. Our experiments involve an in-depth analysis and a comprehensive assessment of the constituent parts of our approach using three public benchmark datasets. We evaluate the geometric and semantic accuracy of our model and analyze the underlying run-times and the complexity of the obtained representation. Our results indicate that the joint treatment of both cues on the Semantic Stixel level yields a highly compact environment representation while maintaining an accuracy comparable to the two individual pixel-level input data sources. Moreover, our framework compares favorably to related approaches in terms of computational costs and operates in real-time.

In Vehicle Safety Communications (VSC) based on IEEE 802.11p, vehicles establish a mutual awareness of their presence by periodically broadcasting status messages, aka beacons. If vehicle density is high and beaconing is not regulated, the channel can become congested, impairing reception performance and safety benefit. As a countermeasure, a number of congestion control approaches have been suggested, adapting transmit (Tx) power, beacon generation rate (Tx rate), or both. However, in general these approaches did not show what the optimal outcome for congestion control would be and how and why their solution would lead to the desired result. In this work, we analyze answers to the first question and provide a methodology for the second. We systematically derive a joint power/rate control strategy for VSC which optimizes reception performance for a targeted sender-receiver distance. We start by laying out why we consider average (or percentile of) packet Inter-Reception Time (IRT) at the targeted awareness distance to be a suitable metric for our purpose. Then, we analyze a wide range of Tx parameters to identify which combinations optimize reception in a homogeneous scenario. We show that for each sender-receiver distance, there is an optimal Tx power which, unlike the corresponding Tx rate, is independent of node density. In addition, we analyze the Pareto optimal Tx parameter combinations for two groups of vehicles with different target distances adapting at the same time. We show that the majority of these combinations use the same Tx power as identified in the homogeneous case. We conclude that a simple and efficient strategy to optimize reception performance is to select Tx power w.r.t. the targeted distance and to adapt Tx rate w.r.t. channel load.

In 1998, the U.S. Congress enacted the transportation equity act for the 21st century [TEA98], which directed the Federal Communications Commission (FCC) to consider the spectrum needs "for the operation of intelligent transportation systems, including spectrum for the dedicated short-range vehicle-to-wayside wireless standard." In the United States, the 75-MHz spectrum between 5.850 and 5.925 GHz is referred to as 5.9 GHz dedicated short-range communications (DSRC). It is often necessary to specify 5.9 GHz when referring to DSRC to differentiate the new spectrum from the older 900 MHz band of the same name, used for electronic toll collection. The European Union (EU) also recognized the importance of a dedicated spectrum for ITS. The European DSRC spectrum is structured into five 10-MHz channels, as opposed to the seven 10-MHz channels allotted to DSRC in the United States. Vehicle-to-vehicle (V2V) safety communications are not an officially intended usage of DSRC technology in Japan. Controlled Vocabulary Terms radio spectrum management; transportation

With self-driving vehicles (SDVs), pedestrians cannot rely on communication with the driver anymore. Industry experts and policymakers are proposing an external Human-Machine Interface (eHMI) communicating the automated status. We investigated whether additionally communicating SDVs' intent to give right of way further improves pedestrians' street crossing. To evaluate the stability of these eHMI effects, we conducted a three-session video study with N=34 pedestrians where we assessed subjective evaluations and crossing onset times. This is the first work capturing long-term effects of eHMIs. Our findings add credibility to prior studies by showing that eHMI effects last (acceptance, user experience) or even increase (crossing onset, perceived safety, trust, learnability, reliance) with time. We found that pedestrians benefit from an eHMI communicating SDVs' status, and that additionally communicating SDVs' intent adds further value. We conclude that SDVs should be equipped with an eHMI communicating both status and intent.

The characterization of the interior-permanent-magnet synchronous machine (IPMSM) is limited due to the nonlinearity of the flux-linkage profile by using the conventional motor model. A nonlinear flux-linkage model for the IPMSM with 12 coefficients is proposed in this paper. It can generally be used to estimate the real d-axis flux linkage, q-axis flux linkage, maximum-torque-per-ampere (MTPA) locus, and torque without the information of the machine known, such as the geometry and material of the permanent magnet. The corresponding torque equation and MTPA condition are presented. An optimization problem is formulated to find the appropriate factors for the proposed model based on the measured flux-linkage data at only nine specific operating points. No selection of weight factors is required in the cost function. The desired copper-loss minimization control can be achieved and good torque identification can be implemented in real time. Both simulation and experiment have been conducted to validate the proposed algorithm in motoring and generating modes. Compared with the conventional IPMSM model, the torque estimation accuracy has been significantly improved by considering the saturation and cross-coupling effects in the nonlinear flux-linkage model of the machine.

Autonomous vehicles are technologically feasible and are becoming a reality. However, before they can be launched, thorough testing is necessary. In this paper, we present a novel approach to automatically generate test scenarios for regression testing of autonomous vehicle systems as a black box in a virtual simulation environment. To achieve this we focus on the problem of generating the motion of other traffic participants without loss of generality. We combine the combinatorial interaction testing approach with a simple trajectory planner as a feasibility checker to generate efficient test sets with variable coverage. The underlying constraint satisfaction problem is solved with a simple backtracking algorithm.

Abstract The Electron Loss and Fields Investigation with a Spatio-Temporal Ambiguity-Resolving option (ELFIN-STAR, or heretoforth simply: ELFIN) mission comprises two identical 3-Unit (3U) CubeSats on a polar (∼93 ∘ inclination), nearly circular, low-Earth (∼450 km altitude) orbit. Launched on September 15, 2018, ELFIN is expected to have a &gt;2.5 year lifetime. Its primary science objective is to resolve the mechanism of storm-time relativistic electron precipitation, for which electromagnetic ion cyclotron (EMIC) waves are a prime candidate. From its ionospheric vantage point, ELFIN uses its unique pitch-angle-resolving capability to determine whether measured relativistic electron pitch-angle and energy spectra within the loss cone bear the characteristic signatures of scattering by EMIC waves or whether such scattering may be due to other processes. Pairing identical ELFIN satellites with slowly-variable along-track separation allows disambiguation of spatial and temporal evolution of the precipitation over minutes-to-tens-of-minutes timescales, faster than the orbit period of a single low-altitude satellite (T orbit ∼ 90 min). Each satellite carries an energetic particle detector for electrons (EPDE) that measures 50 keV to 5 MeV electrons with $\Delta $ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>Δ</mml:mi> </mml:math> E/E &lt; 40% and a fluxgate magnetometer (FGM) on a ∼72 cm boom that measures magnetic field waves (e.g., EMIC waves) in the range from DC to 5 Hz Nyquist (nominally) with &lt;0.3 nT/sqrt(Hz) noise at 1 Hz. The spinning satellites (T spin $\,\sim $ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mspace/> <mml:mo>∼</mml:mo> </mml:math> 3 s) are equipped with magnetorquers (air coils) that permit spin-up or -down and reorientation maneuvers. Using those, the spin axis is placed normal to the orbit plane (nominally), allowing full pitch-angle resolution twice per spin. An energetic particle detector for ions (EPDI) measures 250 keV – 5 MeV ions, addressing secondary science. Funded initially by CalSpace and the University Nanosat Program, ELFIN was selected for flight with joint support from NSF and NASA between 2014 and 2018 and launched by the ELaNa XVIII program on a Delta II rocket (with IceSatII as the primary). Mission operations are currently funded by NASA. Working under experienced UCLA mentors, with advice from The Aerospace Corporation and NASA personnel, more than 250 undergraduates have matured the ELFIN implementation strategy; developed the instruments, satellite, and ground systems and operate the two satellites. ELFIN’s already high potential for cutting-edge science return is compounded by concurrent equatorial Heliophysics missions (THEMIS, Arase, Van Allen Probes, MMS) and ground stations. ELFIN’s integrated data analysis approach, rapid dissemination strategies via the SPace Environment Data Analysis System (SPEDAS), and data coordination with the Heliophysics/Geospace System Observatory (H/GSO) optimize science yield, enabling the widest community benefits. Several storm-time events have already been captured and are presented herein to demonstrate ELFIN’s data analysis methods and potential. These form the basis of on-going studies to resolve the primary mission science objective. Broad energy precipitation events, precipitation bands, and microbursts, clearly seen both at dawn and dusk, extend from tens of keV to &gt;1 MeV. This broad energy range of precipitation indicates that multiple waves are providing scattering concurrently. Many observed events show significant backscattered fluxes, which in the past were hard to resolve by equatorial spacecraft or non-pitch-angle-resolving ionospheric missions. These observations suggest that the ionosphere plays a significant role in modifying magnetospheric electron fluxes and wave-particle interactions. Routine data captures starting in February 2020 and lasting for at least another year, approximately the remainder of the mission lifetime, are expected to provide a very rich dataset to address questions even beyond the primary mission science objective.

Quantum simulations of electronic structure with a transformed Hamiltonian that includes some electron correlation effects are demonstrated. The transcorrelated Hamiltonian used in this work is efficiently constructed classically, at polynomial cost, by an approximate similarity transformation with an explicitly correlated two-body unitary operator. This Hamiltonian is Hermitian, includes no more than two-particle interactions, and is free of electron-electron singularities. We investigate the effect of such a transformed Hamiltonian on the accuracy and computational cost of quantum simulations by focusing on a widely used solver for the Schrödinger equation, namely the variational quantum eigensolver method, based on the unitary coupled cluster with singles and doubles (q-UCCSD) Ansatz. Nevertheless, the formalism presented here translates straightforwardly to other quantum algorithms for chemistry. Our results demonstrate that a transcorrelated Hamiltonian, paired with extremely compact bases, produces explicitly correlated energies comparable to those from much larger bases. For the chemical species studied here, explicitly correlated energies based on an underlying 6-31G basis had cc-pVTZ quality. The use of the very compact transcorrelated Hamiltonian reduces the number of CNOT gates required to achieve cc-pVTZ quality by up to two orders of magnitude, and the number of qubits by a factor of three.

Quantum chemistry simulations of some industrially relevant molecules are reported, employing variational quantum algorithms for near-term quantum devices. The energies and dipole moments are calculated along the dissociation curves for lithium hydride (LiH), hydrogen sulfide, lithium hydrogen sulfide, and lithium sulfide. In all cases, we focus on the breaking of a single bond to obtain information about the stability of the molecular species being investigated. We calculate energies and a variety of electrostatic properties of these molecules using classical simulators of quantum devices, with up to 21 qubits for lithium sulfide. Moreover, we calculate the ground-state energy and dipole moment along the dissociation pathway of LiH using IBM quantum devices. This is the first example, to the best of our knowledge, of dipole moment calculations being performed on quantum hardware.

Monitoring permanent magnet synchronous machine (PMSM) faults including partial demagnetization, inter-turn short circuit is necessary for safety and reliable operation. This paper studies vibration acceleration to detect faults using both mode shape and vibration frequency information. For this purpose, Finite element analysis is used to calculate the radial force distribution applied on the stator teeth and mode shape of the PMSM. 2-dimensional Fast Fourier Transformation (FFT) is employed to extract the significant harmonic orders, which dominate the vibration. Simulation and experimental results indicate that featured low mode order and corresponding frequency component would appear under fault conditions. Simulation and experimental results are used to analyze the effectiveness of the proposed approach.

Occupancy grid mapping is a well-known environment perception approach. A grid map divides the environment into cells and estimates the occupancy probability of each cell based on sensor measurements. An important extension is the Bayesian occupancy filter (BOF), which additionally estimates the dynamic state of grid cells and allows modeling changing environments. In recent years, the BOF attracted more and more attention, especially sequential Monte Carlo implementations (SMC-BOF), requiring less computational costs. An advantage compared to classical object tracking approaches is the object-free representation of arbitrarily shaped obstacles and free-space areas. Unfortunately, publications about BOF based on laser measurements report that grid cells representing big, contiguous, stationary obstacles are often mistaken as moving with the velocity of the ego vehicle (ghost movements). This paper presents a method to fuse laser and radar measurement data with the SMC-BOF. It shows that the doppler information of radar measurements significantly improves the dynamic estimation of the grid map, reduces ghost movements, and in general leads to a faster convergence of the dynamic estimation.