Interaction between drivers and pedestrians is often facilitated by informal communicative cues, like hand gestures, facial expressions, and eye contact. In the near future, however, when semi- and ...fully autonomous vehicles are introduced into the traffic system, drivers will gradually assume the role of mere passengers, who are casually engaged in non-driving-related activities and, therefore, unavailable to participate in traffic interaction. In this novel traffic environment, advanced communication interfaces will need to be developed that inform pedestrians of the current state and future behavior of an autonomous vehicle, in order to maximize safety and efficiency for all road users. The aim of the present review is to provide a comprehensive account of empirical work in the field of external human-machine interfaces for autonomous vehicle-to-pedestrian communication. In the great majority of covered studies, participants clearly benefited from the presence of a communication interface when interacting with an autonomous vehicle. Nevertheless, standardized interface evaluation procedures and optimal interface specifications are still lacking.
We present ultrabroadband two-beam femtosecond/picosecond coherent Raman spectroscopy on the ro-vibrational spectra of CO 2 and O 2 , applied for multispecies thermometry and relative concentration ...measurements in a standard laminar premixed hydrocarbon flame. The experimental system employs fs-laser-induced filamentation to generate the compressed supercontinuum in-situ, resulting in a ∼24 fs full-width-at-half-maximum pump/Stokes pulse with sufficient bandwidth to excite all the ro-vibrational Raman transitions up to 1600 cm -1 . We report the simultaneous recording of the ro-vibrational CO 2 Q-branch and the ro-vibrational O 2 O-, Q- and S-branch coherent Stokes Raman spectra (CSRS) on the basis of a single-laser-shot. The use of filamentation as the supercontinuum generation mechanism has the advantage of greatly simplifying the experimental setup, as it avoids the use of hollow-core fibres and chirped mirrors to deliver a near-transform-limited ultrabroadband pulse at the measurement location. Time-domain models for the ro-vibrational Q-branch spectrum of CO 2 and the ro-vibrational O-, Q- and S-branch spectra of O 2 were developed. The modelling of the CO 2 Q-branch spectrum accounts for up to 180 vibrational bands and for their interaction in Fermi polyads, and is based on recently available, comprehensive calculations of the vibrational transition dipole moments of the CO 2 molecule: the availability of spectroscopic data for these many vibrational bands is crucial to model the high-temperature spectra acquired in the flue gases of hydrocarbon flames, where the temperature can exceed 2000 K. The numerical code was employed to evaluate the CSRS spectra acquired in the products of a laminar premixed methane/air flame provided on a Bunsen burner, for varying equivalence ratio in the range 0.6–1.05. The performance of the CO 2 spectral model is assessed by extracting temperatures from 40-laser-shots averaged spectra, resulting in thermometry accuracy and precision of ∼5% and ∼1%, respectively, at temperatures as high as 2220 K.
Battery-based Energy Storage Transportation (BEST) is the transportation of modular battery storage systems via train cars or trucks representing an innovative solution for a) enhancing Variable ...Renewable Energy (VRE) utilization and load shifting, and b) providing a potential alternative for managing transmission congestions. This paper focuses on point b) and proposes a long-term transmission-planning model coordinated with both stationary and mobile storage units. The planning-problem objective function minimizes the total system cost, i.e., the sum of i) the investment cost of candidate transmission lines, stationary and mobile storage systems, and ii) the operation cost, including conventional generating units fuel consumption, load shedding penalty and BEST transportation costs. An alternative approach for BEST vehicle scheduling problem is implemented. The contribution lies in the accomplishment of the spatial-temporal scheduling of the mobile storage units by including the Number-of-nonzero mathematical function in the optimization model set of constraints instead of using additional binary variables as generally accomplished. The identification of either storage systems optimal location, or both optimal location and size of storage systems is also allowed. BEST usefulness is analyzed and discussed for a test-system emulating a reals system in China-Northwestern-grid with high VRE penetration divided in five regional areas, of which the most promising one for BEST implementation is identified.
Abstract Railcars are prone to suffer from overloading problems during its operation, which seriously affects the service life of railcars and rails, while posing a serious potential safety hazard. ...This paper In this paper, the weight of the car load is calculated by installation of a gravity sensor on the railcar and collection of the data from the gravity sensor through applying the A/D conversion module of the MCU. The overloading warning function of railcars is realized according to the drive alarm indicator of overloading information, and displaying the overloading information on the liquid crystal display screen.
•Autonomous Cyber-Physical Systems (ACPS) require “Human-in-the-loop” to collaborate in the execution of certain tasks that cannot be performed autonomously.•A trust-based relationship must be built ...between humans and machines so they can work together and achieve effective human-machine integration.•Human integration into the ACPS must be natural, robust, and non-intrusive.•The goal of our framework is to provide a design theory to analyze and design the involvement of humans in ACPSs in order to improve system performance and understandability and to avoid developing intrusive and annoying systems.•Our proposal is instantiated to design and develop a functional prototype of an autonomous car with HiL-ACPS capabilities.
Even though full autonomy in Cyber-Physical Systems (CPSs) is a challenge that has been confronted in different application domains and industrial sectors, the current scenario still requires human intervention in these autonomous systems in order to accomplish tasks that are better performed with human-in-the-loop. Humans, machines, and software systems are required to interact and understand each other in order to work together in an effective and robust way. This human integration introduces an important number of challenges and problems to be solved in order to achieve seamless and solid participation. To manage this complexity, appropriate techniques and methods must be used to help CPS developers analyze and design this kind of human-in-the-loop integration. The goal of this paper is to identify the technological challenges and limitations of integrating humans into the CPSs autonomy loop and to break new ground for design solutions in order to develop what we call HiL-ACPS systems. This work defines a conceptual framework to characterize the cooperation between humans and autonomous CPSs and provides techniques for applying the framework in order to design proper human integration. The emergent autonomous car domain is considered as a running example. It covers some of the current limitations of involving drivers into the autonomous functionalities. Finally, to validate the proposal, an autonomous car prototype was built applying the conceptual framework. This prototype was evaluated to check whether the human integration implemented behaves as defined in its specification.
DroNet: Learning to Fly by Driving Loquercio, Antonio; Maqueda, Ana I.; del-Blanco, Carlos R. ...
IEEE robotics and automation letters,
04/2018, Volume:
3, Issue:
2
Journal Article
Peer reviewed
Open access
Civilian drones are soon expected to be used in a wide variety of tasks, such as aerial surveillance, delivery, or monitoring of existing architectures. Nevertheless, their deployment in urban ...environments has so far been limited. Indeed, in unstructured and highly dynamic scenarios, drones face numerous challenges to navigate autonomously in a feasible and safe way. In contrast to traditional "map-localize-plan" methods, this letter explores a data-driven approach to cope with the above challenges. To accomplish this, we propose DroNet: a convolutional neural network that can safely drive a drone through the streets of a city. Designed as a fast eight-layers residual network, DroNet produces two outputs for each single input image: A steering angle to keep the drone navigating while avoiding obstacles, and a collision probability to let the UAV recognize dangerous situations and promptly react to them. The challenge is however to collect enough data in an unstructured outdoor environment such as a city. Clearly, having an expert pilot providing training trajectories is not an option given the large amount of data required and, above all, the risk that it involves for other vehicles or pedestrians moving in the streets. Therefore, we propose to train a UAV from data collected by cars and bicycles, which, already integrated into the urban environment, would not endanger other vehicles and pedestrians. Although trained on city streets from the viewpoint of urban vehicles, the navigation policy learned by DroNet is highly generalizable. Indeed, it allows a UAV to successfully fly at relative high altitudes and even in indoor environments, such as parking lots and corridors. To share our findings with the robotics community, we publicly release all our datasets, code, and trained networks.
This paper proposes an envelope control framework for four-wheel independently actuated autonomous ground vehicle (AGV) to regulate it on desired path and simultaneously control it to the driving ...limits. The envelope control framework is achieved based on the integrated control of active front-wheel steer and direct yaw-moment control. In a speed controller, the G-G diagram is used to describe the driving limits on each path segment. The desired traction and braking force is calculated according to the G-G diagram and desired path. In a path-following controller, a feedforward-feedback lateral controller is designed to calculate the desired steering angle to follow the desired path. In a yaw-moment controller, the β-r phase portraits are utilized to describe the handling limits. The yaw-moment controller aims at keeping the AGV from losing stability in limit driving, which is calculated through a sliding mode controller and provided by the independent motors actuation. Through an independent driving technique, the tyre cornering stiffness is estimated online based on the predefined Magic Formula model to improve the controller's robustness. An autonomous Formula Student racecar developed by the authors is used as testbed. The autonomous driving experiments on racetrack validate the efficiency of the proposed controller.
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•Transition modeling considers the phase-in and -out of technologies and time delays.•Electrification speed is the most important factor toward a carbon-neutral car fleet.•Swiss ...climate goals can be met by phasing out new ICEVs by 2025 and hybrids by 2030.•Electric autonomous cars with ride-sharing will yield the largest emissions reduction.•Autonomous cars without shared mobility will lead to the highest emissions levels.
Car transport is currently undergoing three simultaneous revolutions that are co-shaping the pathway to low-carbon mobility: fleet electrification, shared mobility, and autonomous cars (ACs). So far, studies of the climate impacts have mostly focused on the revolutions in isolation, neglecting potential synergies, and using methodologies that poorly represent the long-term transition of physical systems such as the car fleet. Here, we developed a stock dynamics model and a scenario analysis for direct energy consumption and greenhouse gas (GHG) emissions generated by different combinations of the revolutions in Switzerland. The largest climate change mitigation potential is provided by combining ACs with ride-sharing with rapid fleet electrification, i.e. completely phasing out new gasoline and diesel cars by 2025 and new hybrid cars by 2030. By contrast, ACs without shared mobility generate the lowest mitigation potential. Electric ACs with ride-sharing are crucial for meeting the Swiss climate goals, e.g. carbon neutrality in 2050.
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