The objective of this paper is to find object based solutions for a collision avoidance system. In this paper, the authors present an algorithm for obstacle detection, from the actual video images taken by an on-board camera. The proposed technique is based on Histograms of Oriented Gradient (HOG) to extract features of the objects and classify the obstacles by the Time Delay Neural Network (TDNN). The experimental results showed that it can detect general objects, and is not restricted to vehicles, objects or pedestrians. It has provided good results along with high accuracy and reliability.
In recent years, an angular-velocity-based brain injury criterion, BrIC, has been proposed by the National Highway Traffic Safety Administration (NHTSA) for consumer vehicle safety assessment tests. In this study, the cumulative strain damage measure (CSDM), as one of the brain injury metrics, was calculated based on data obtained for a total of 360 anthropomorphic test devices (ATDs) in vehicle crash tests conducted by NHTSA and the Insurance Institute for Highway Safety (IIHS) using the Simulated Injury Monitor (SIMon ver. 4.0), a human brain finite element model developed by NHTSA’s research institute. Self-Organizing Maps (SOMs) and hierarchical clustering were used to classify test data composed of the brain injury risk level based on CSDM and its corresponding head kinematic parameters. Results demonstrated that, in addition to the peak values of angular velocities, the peak values of angular accelerations around three axes are also influential parameters for accurately predicting brain injury risk based on CSDM.
We propose an evaluation methodology to analyze the safety level of advanced driver assistance systems (ADAS) as a human–machine systems in terms of comparing the increase in the safety level during normal system operation and the decrease in the safety level during a system malfunction. We propose a concept of combined error for the human–machine system and quantify this combined error by driving simulator investigations and simulation studies. First, we investigated the drivers’ behavior when avoiding rear-end collisions with a preceding vehicle when equipped with ADASs-like adaptive cruise control systems (ACC) and lane keeping assistance systems (LKA). Then, we confirmed that the risk of collision induced by overdependence on the systems was not increased when the ACC and LKA were mounted on the vehicle using simulation studies based on the concept of combined error for the human–machine system. We also confirmed that the decrease in collisions when the ADASs operated appropriately was much larger than the increase in collisions during a system malfunction.
The aerodynamics of a rotating tire can contribute up to a third of the overall aerodynamic force on the vehicle. The flow around a rotating tire is very complex and is often affected by smallest tire features. Accurate prediction of vehicle aerodynamics therefore requires modeling of tire rotation including all geometry details. Increased simulation accuracy is motivated by the needs emanating from stricter new regulations. For example, the upcoming Worldwide harmonized Light vehicles Test Procedures (WLTP) will place more emphasis on vehicle performance at higher speeds. The reason for this is to bring the certified vehicle characteristics closer to the real-world performance. In addition, WLTP will require reporting of CO2 emissions for all vehicle derivatives, including all possible wheel and tire variants. Since the number of possible derivatives can run into the thousands of models, their evaluation in wind tunnels is not be practically possible. Therefore, simulations are the only alternative especially, since their use is allowed by WLTP. As a first step in order to meet these escalating demands, the current study uses a Lattice Boltzmann method (LBM) based computational fluid dynamics (CFD) solver using an immersed boundary method (IBM) based approach to simulate and validate a standalone rotating treaded tire. Simulated wake plane prediction results are in good agreement with experimental wake plane measurements. Effect of tire loading on wake results is also discussed.
This paper focused on the effect of intrusion magnitude and maximum deformation location in improving the accuracy of Injury Severity Prediction (ISP) for Advanced Automatic Crash Notification (AACN) system. This study used 545-passenger vehicles involved in Car-to-Car side impact data from NASS CDS (CY: 2004-2014). Variables mentioned in Kononen’s 2011 ISP algorithm are considered as base model. In addition to Kononen’s variables, magnitude of intrusion and maximum deformation location are added in the proposed model. As the location of maximum deformation moves away from the B pillar to end regions (front or back), the percentage of serious injury reduces drastically. Similar trend is verified in both accident analysis and FE numerical simulation results. Addition of intrusion magnitude and location of maximum deformation as additional injury predictors helped to improve the proposed model sensitivity, overall accuracy by 16%, 3.12% respectively without any change in specificity value.
Due to each country’s energy policy, various types of gasoline such as ethanol blended gasoline, high/low aromatic content gasoline, etc. are sold in the market. As the production of engines and their part supply chains become more globalized, it is important to develop engines that can be compatible with various types of gasoline. To maintain engine durability, it is necessary to clarify the effects of these gasoline components on engine durability. To understand the friction of metal to metal contact, which are directly connected to engine durability, we examined synthetically the relationship between gasoline components and lubricity.
This paper will describe the journey of magnetic powersplit powertrain technology from its origins in new technology discovery through to packaged, design intent vehicle applications, describing the obstacles overcome and opportunities realised in the journey that delivered magnetic powersplit technology to Global Automotive OEM's. Aspects of technology development, design for manufacture, capability proving and production feasibility will be described in order to demonstrate a credible, world class next generation hybrid powertrain.