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This paper proposes a parameter estimator for four-wheel-independently driven electric (4 WID) vehicle with in-wheel motors. The mass and location of payload have great impacts on the stability and maneuverability of lightweight vehicles (LWVs). Fast, effective and real-time parameter estimator can make the existing controller adjust the changed parameter caused by additional payload. The proposed...
To enable an effective traffic management and signal control, it is important to know the road traffic density. In recent years, video surveillance based systems and monitoring tools have been widely used for obtaining road traffic density for traffic management. To address the needs of autonomous traffic data extraction and video analysis, a vast body of research exists. However, these schemes are...
Target tracking is an essential part in automotive driver assistance systems. Most maneuvering target tracking algorithms are based on model, and an accurate model can enhance the tracking performance. Compared with constant velocity (CV) model, constant acceleration (CA) model and Singer model, the current statistical (CS) model matches well with the actual motion of target vehicle. But when a target...
For more accurate estimation of urban traffic emissions, it is necessary to study the emission estimates under different traffic conditions. In this paper, a novel emission estimation method on the basis of levels-of-service (LOS) is presented to estimate city emissions under different traffic conditions. The primary contributions of our work are a novel set of velocity-acceleration features to distinguish...
In this report, we discuss about a data mining method for multi-modal in-vehicle sensor signals. Though several methods were previously proposed for symbolization of the multi-modal in-vehicle signals, the effectiveness of such method were not discussed in detail. We adopt the Bag-of-System (BoS) technique, a variation of the Bag-of-Features for sensor signals used in motion analysis, and evaluate...
A collision risk estimation plays a crucial role in both driver and pedestrian safety in advanced driver assistance systems (ADAS) and autonomous vehicle navigation(AVN). In the proposed approach, an object warning collision system is implemented using a laser sensor. We focus on high conflict vehicle/pedestrian zones within a range of [20km/h, 30km/h]. The proposed method was implemented in four...
In order to enhance road safety, this article presents a robust methodology for estimation of vehicle's lateral dynamics states, including velocities, sideslip angles, accelerations and tire forces. Awareness of vehicle dynamics states is essential for most intelligent vehicle control systems. However some of these states are not available by direct sensor measurement for technical and economical...
This paper proposes modelling and estimation parameters of Electronic Differential System (EDS) for an Electric Vehicle (EV) with in-wheel motor using Radial Basis Neural Network (RBNN). In this study, EDS for front wheels is analysed instead of rear wheels which are commonly investigated in the literature. According to steering angle and speed of EV, the speeds of the front wheels are calculated...
Traffic Level of Service (LOS) information is crucial for traffic management systems, especially in urban areas. One method to estimate traffic LoS is to use a central server system to process traffic images captured by road side cameras. However, this approach requires a high performance server system as well as high network throughput to transmit images from the cameras to the server, which results...
The wide diffusion of Full and Hybrid Electric Vehicles is stimulating research on electric energy storage systems and Battery Management Systems (BMS). The Battery management system must ensure many complex features such as charge control, battery-capacity monitoring, remaining run-time information and charge-cycle counting. An optimization of the BMS can allow an improvement on security of the vehicle,...
An estimation framework is presented that improves the robustness of GPS-denied state estimation to changing environmental conditions by fusing updates from multiple view-based odometry algorithms. This allows the vehicle to utilize a suite of complementary exteroceptive sensors or sensing modalities. By estimating the vehicle states relative to a local coordinate frame collocated with an odometry...
This work focuses on the remote sensing of thermal updrafts under cumulus clouds for glider UAVs. Previous remote estimation techniques assume unlimited thermal lifespans under the clouds. Naturally occuring thermals are however of limited duration which increases the risk of an outlanding when utilizing these methods. By observing the evolution of the cloud's diameter, human glider pilots draw conclusions...
A method for cooperative estimation is proposed for use in multi-vehicle unmanned air systems with vision-based target tracking capabilities. The method first seeks to estimate the relative rotational and translational biases that exist between tracks from different vehicles. It then accounts for the biases and performs the track-to-track association, which determines if the tracks originate from...
This paper describes systematically two methods used in intelligent transportation systems: Distance Estimation using an onboard camera and car position detection. Distance estimation is a method for detecting distance for the preceding vehicles based on monocular camera. Vehicle position detection is a method of specifying the vehicle position relative to the road that can serve as Lane Departure...
Nowadays, the technological and scientific research related to underwater perception is focused in developing more cost-effective tools to support activities related with the inspection, search and rescue of wreckages and site exploration: devices with higher autonomy, endurance and capabilities. Currently, specific tasks are already carried out by remotely-operated vehicles (ROV) and autonomous underwater...
Humans are increasingly cooperating with machinery/robots in a high number of domains and under uncontrolled conditions. When persons are interacting with machinery, they are exposed to distraction/fatigue, which can lead to dangerous situations. The evaluation of individual's attention and fatigue levels is highly needed in such situations. This is an important measurement to avoid the interaction...
Increased traffic and hence congestion is a major problem in cities or urban areas. To mitigate this problem of congestion a real-time traffic density estimation model is essential. This research proposes one such model for estimating the traffic congestion level with the help of Vehicular Ad-hoc Network (VANET) and Cloud Computing. In this work, a novel architecture and algorithm has been proposed...
The knowledge of Inter-vehicle link duration is an important parameter in Vehicular Ad hoc Networks (VANETs), as it is useful for vehicles to delay their information transmission if link breakage is anticipated before completing the transmission. In addition, it plays a pivotal role in routing, as it allows proactive construction of long-life paths, and optimizing next-hop selection in position-based...
Abstract-In VANETs, information exchange plays an important role to make vehicles aware to each other and provide references for safety or non-safety related applications. At intersections, vehicles are forced to maintain a lower mobility thereby have more time to exchange on-road or off-road context information. However, if an effective control scheme is not applied to this specific scenario, a packet...
High-speed image sensors, designed for machine vision and control, provide the “eyes” for autonomous and connected vehicle. A noteworthy feature of high-speed image sensors is their ability to be used as a reception device for visible light communication (VLC) signals. Due to the massive number of pixels available and the ability to spatially separate sources, a signal-receiving pixel in the image...
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