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This paper presents a proof of concept for an algorithm to determine the attitude of a multi-layer laser rangefinder or LiDAR (Light Detection And Ranging) relative to a reference frame given the ability of the LiDAR to make measurements to a planar surface with sufficient and proper excitation. Due to the highly non-linear nature of the problem presented, weighted recursive least squares along with a high order unscented transform are used to obtain a final result which is capable of being extended to vehicle safety systems to provide a measurement of the roll and pitch of a vehicle relative to the road's surface with a high degree of accuracy.

LiDAR sensors have played more and more important role on Intelligent and Connected Vehicles (ICV) and Advanced Driver Assistance Systems (ADAS) .However, the development and testing of LiDAR sensors under real driving environment for ADAS applications are greatly limited by various factors, and often are impossible due to safety concerns. This paper proposed a novel functional LiDAR model under virtual driving environment to support development of LiDAR-based ADAS applications under early stage. Unlike traditional approaches on LiDAR sensor modeling, the proposed method includes both geometrical modeling approach and physical modeling approach. While geometric model mainly produces ideal scanning results based on computer graphics, the physical model further brings physical influences on top of the geometric model. The range detection is derived and optimized based on its physical detection and measurement mechanism.

Autonomous vehicles are currently a subject of great interest and there is heavy research on creating and improving algorithms for detecting objects in their vicinity. A ROS-based deep learning approach has been developed to detect objects using point cloud data. With encoded raw light detection and ranging (LiDAR) and camera data, several basic statistics such as elevation and density are generated. The system leverages a simple and fast convolutional neural network (CNN) solution for object identification and localization classification and generation of a bounding box to detect vehicles, pedestrians and cyclists was developed. The system is implemented on an Nvidia Jetson TX2 embedded computing platform, the classification and location of the objects are determined by the neural network. Coordinates and other properties of the object are published on to various ROS topics which are then serviced by visualization and data handling routines.

Although SAE level 5 autonomous vehicles are not yet commercially available, they will need to be the most intelligent, secure, and safe autonomous vehicles with the highest level of automation. The vehicle will be able to drive itself in all lighting and weather conditions, at all times of the day, on all types of roads and in any traffic scenario. The human intervention in level 5 vehicles will be limited to passenger voice commands, which means level 5 autonomous vehicles need to be safe and capable of recovering fail operational with no intervention from the driver to guarantee the maximum safety for the passengers. In this paper a LiDAR-based fail-safe emergency maneuver system is proposed to be implemented in the level 5 autonomous vehicle.

The accuracy of parking slot detection is a challenge for the safety of the Automated Valet Parking (AVP), while traditional methods of range sensor-based parking slot detection have mostly focused on the detection rate in a scenario, where the ego-vehicle must pass by the slot. This paper uses three-dimensional Light Detection And Ranging (3D LiDAR) to efficiently search parking slots around without passing by them and highlights the accuracy of detecting and tracking. For this purpose, a universal process of 3D LiDAR-based high-accuracy slot perception is proposed in this paper. First, the method Minimum Spanning Tree (MST) is applied to sort obstacles, and Separating Axis Theorem (SAT) are applied to the bounding boxes of obstacles in the bird’s-eye view, to find a free space between two adjacent obstacles. These bounding boxes are obtained by using common point cloud processing methods.

Advanced Driver Assistance Systems (ADAS) enable safer driving by relying on the inputs from various sensors including Radar, Camera, and LiDAR. One of the newly emerging ADAS features is Predictive Cruise Control (PCC). PCC aims to optimize the vehicle’s speed profile and fuel efficiency. This paper presents a novel approach of using the point cloud of a LiDAR sensor to develop a PCC feature. The raw point cloud is utilized to detect objects in the surrounding environment of the vehicle, estimate the grade of the road, and plan the route in drivable areas. This information is critical for the PCC to define the optimal speed profile of the vehicle while following the planned path. This paper also discusses the developed algorithms of the LiDAR data processing and PCC controller. These algorithms were tested on FEV’s Smart Vehicle Demonstrator platform.

The technological advancements of Advanced Driver Assistance Systems (ADAS) sensors enable the ability to; achieve autonomous vehicle platooning, increase the capacity of road lanes, and reduce traffic. This article focuses on developing urban autonomous platooning using LiDAR and GPS/IMU sensors in a simulation environment. Gazebo simulation is utilized to simulate the sensors, vehicles, and testing environment. Two vehicles are used in this study; a Lead vehicle that follows a preplanned trajectory, while the remaining vehicle (Follower) uses the LiDAR object detection and tracking information to mimic the Lead vehicle. The LiDAR object detection is handled in multiple stages: point cloud frame transformation, filtering and down-sampling, ground segmentation, and clustering. The tracking algorithm uses the clustering information to provide position and velocity of the Lead vehicle which allows for vehicle platooning.

Intelligent Vehicle-Highway Systems (IVHS) may change the character of automobile accidents and of automobile accident lawsuits in the United States. Successful implementation of IVHS technology will require significant capital investment by manufacturers and highway departments. Investment may be deterred by concern about potential legal liability and the cost of liability insurance. Liability and insurance experience with other pathbreaking technologies -- commercial air transportation, nuclear power, and satellites -- suggests that the liability risks of advanced stages of IVHS technology should be managed through federal or state legislation.

A research crash simulator is described which is located at the Liberty Mutual Research Center in Hopkinton, Massachusetts. A seven-foot sled is accelerated by compressed air at speeds up to 60 mph, and then decelerated by a combination of aluminum honeycomb and a hydraulic energy absorber. Normally the sled carries an automotive seat, with some type of restraint system, and an anthropometric dummy. Information concerning collision events in the simulator is obtained from electronic transducers and high speed motion pictures. A number of car occupant protection systems have been tested on this simulator, and typical data are presented to illustrate its performance.

As the technological revolution continues to hurtle forward, the importance of the licensing or technology transfer contract grows apace. This article gives a relatively brief introduction to certain parts of the licensing agreement and various principles and procedures of licensing negotiations. There is also included a brief explanation of the Disclosure and Secrecy Agreement and its growing variety of applications.

Licensing technology has long been established a viable means for helping both parties of such an agreement improve their technology bases. The licensor/licensee relationship must be close and interactive to optimize these improvements. The importance of the selection process of potential licensees as well as the structuring of how the technology is transferred are key items for the success of license agreements. Future licensing activities may require tighter controls on technology transfers to protect against the creation of new competitors.

High-precision and real-time ego-motion estimation is vital for autonomous vehicle. There is a lot GPS-denied maneuver such as underground parking lot in urban areas. Therefore, the localization system relying solely on GPS cannot meets the requirements. Recently, lidar odometry and visual odometry have been introduced into localization systems to overcome the problem of missing GPS signals. Compared with visual odometry, lidar odometry is not susceptible to light, which is widely applied in weak-light environments. Besides, the autonomous parking is highly dependent on the geometric information around the vehicle, which makes building map of surroundings essential for autonomous vehicle. We propose a lidar inertial odometry and mapping. By sensor fusion, we compensate for the drawback of applying a single sensor, allowing the system to provide a more accurate estimate.

Recently, outboard engine technology has advanced significantly. With these new technologies comes a substantial improvement in emissions compared to traditional carbureted two-stroke engines. Some two-stroke gasoline direct injection (GDI) marine outboard engines are now capable of meeting California Air Resources Board 2008 Ultra-Low emissions standards. With improvement of gaseous emissions, studies are now being conducted to assess particulate matter (PM) emissions from all new technology marine outboard engines which include both four-stroke and two-stroke designs. Methods are currently being developed to determine the best way to measure PM from outboard engines. This study assesses gaseous and PM emissions, mutagenic activity of PM and oil consumption of two different technologies over the useful life of the engines.

A new cell balancing technology was developed under a Department of Energy contract which merges the DC/DC converter function into cell balancing. Instead of conventional passive cell balancing technology which bypasses current through a resistor, or active cell balancing which moves current from one cell to another, with significant cost and additional inefficiencies, this concept takes variable amount of current from each cell or small group of cells and converts it to current for the low voltage system.

In 1991, Hamilton Standard initiated an Independent Research and Development program to enhance the performance characteristics of solid amine based regenerative CO2 removal systems. A solid amine based system had been selected by NASA/JSC for Extended Duration Orbiter missions. As a result of this research effort, two promising new solid amine candidates, designated HSC+ and HSG, were identified. Bench scale testing indicated that these formulations provided 25% to 33% greater initial cyclic capacity when compared to the baseline HSC solid amine sorbent. This paper reports on comparative life testing of HSC, HSC+ and HSG. The solid amine sorbents were exposed to accelerated life testing with laboratory air under controlled temperature and flow conditions.

A mathematical programming decision model - Life Cycle Activity Analysis (LCAA), integrating economics and environment in the optimization of the life cycle of products is presented. LCAA is based on the integration of “activity analysis” with the “life cycle assessment” framework. An illustrative application taken from the Portuguese used tire market is described. The model features two scenarios for tire end-of-life recovery technologies, where the environmental consequences of the prohibition of tire landfill are analyzed, namely in terms of energy use. Alternative end of life strategies such as tire remanufacture (retreading), recycling, heat generation in cement plants is considered in the model. The model shows that, provided the Portuguese constraints on the capacity of the alternative solutions, the prohibition of tire landfill result in a 5% decrease of energy consumption over the total tire life cycle.

Policy makers, especially in the European Union, are pushing towards an early transition to electric mobility, with the internal combustion engine supposed to be phased out by 2030. With a world population projected to exceed 10 billion peoples by 2050, the electric car mobility still lacks the significant development needed to become a real alternative to the internal combustion engine based mobility. Resources availability, and environmental, energetic and economic downfalls, are currently largely underrated or simply unassessed. It is unclear how many will be able to afford to purchase and recharge an electric vehicle in this new world.

The goal of this study is to assess the total Life Cycle Global Warming Impact of the current HFC-134a (R134a) refrigeration system and compare it with the effect of proposed alternatives, HFC-134a Enhanced, HFC-152 (R152a), R744, R744 Enhanced and R290, based on life cycle analysis (LCA). The enhanced systems include control strategies to elevate the compressor suction pressure as the evaporator load is reduced. The hydrofluorocarbons HFC-134a and HFC-152a are greenhouse gases (GHGs) and are subject to the Kyoto Protocol timetables, which when the treaty takes effect will require participating developed countries to reduce their overall CO2 equivalent emissions of six GHGs by at least 5% by 2012 from 1990 levels.

Vehicle lightweighting has been a focus of the automotive industry, as car manufacturers seek to comply with corporate average fuel economy (CAFE) and greenhouse gas (GHG) emissions standards for model year (MY) 2017-2025 vehicles. However, when developing a lightweight vehicle design, the automotive industry typically targets maximum vehicle weight reduction at minimal cost increase. In this paper, we consider the environmental impacts of the lightweighting technology options. The materials used for vehicle lightweighting include high-strength steel (HSS), aluminum, magnesium and carbon fiber reinforced plastic (CFRP). Except for HSS, the production of these light materials is more GHG-intensive (on a kg-to-kg basis) compared with the conventional automotive materials they substitute. Lightweighting with these materials, therefore, may partially offset the GHG emission reductions achieved through improved fuel economy.

Using the Life Cycle Analysis methodology, a detailed study of the car glass production phases (from the extraction of raw materials until the recycling) has been developped. This kind of approach goes in the board of the new Fiat strategies to achieve declared goals of environmental efficiency, not only to adapt its choices to new parameters of law, but also to obtain advantages of competitivity on the global market. In particular, with reference to the outline of FARE (Fiat Auto REcycling) project, the end of life of used glass for cars has been evaluated; the primary products of Fiat Punto model (windshield, windshield rear and lateral windows) are recovered to remanufacture and to get a new secondary product as the glass bottles for packaging (open loop recycling), since, until now, it is impossible to have a good quality of glass for cars from the same glass scraps.