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Convolution Neural Networks today provide the best results for many image detection and image recognition problems. The computational complexity and the amount of parameters learned has increased, yet there is little to no research on the topic of functional safety for systems incorporating CNNs. The analysis on false detections due to random hardware faults concentrates on human made adversarial...
For a safety critical task like driving, it is very important for the driver to be vigilant at all times. In this study, we explore a driver drowsiness monitoring and early warning system, which uses machine learning techniques based on vehicle telemetry data. The proposed system can ensure safe driving by real time monitoring of driving pattern. This proves to be a very cost effective technique over...
Head pose monitoring is an important task for driver assistance systems, since it is a key indicator for human attention and behavior. However, current head pose datasets either lack complexity or do not adequately represent the conditions that occur while driving. Therefore, we introduce DriveAHead, a novel dataset designed to develop and evaluate head pose monitoring algorithms in real driving conditions...
Automobiles are currently equipped with a three-mirror system for rear-view visualization. The two side-view mirrors show close the periphery on the left and right sides of the vehicle, and the center rear-view mirror is typically adjusted to allow the driver to see through the vehicle's rear windshield. This three-mirror system, however, imposes safety concerns in requiring drivers to shift their...
Robust hand detection and classification is one of the most crucial pre-processing steps to support human computer interaction, driver behavior monitoring, virtual reality, etc. This problem, however, is very challenging due to numerous variations of hand images in real-world scenarios. This work presents a novel approach named Multiple Scale Region-based Fully Convolutional Networks (MSRFCN) to robustly...
Driver’s status is crucial because one of the main reasons for motor vehicular accidents is related to driver’s inattention or drowsiness. Drowsiness detector on a car can reduce numerous accidents. Accidents occur because of a single moment of negligence, thus driver monitoring system which works in real-time is necessary. This detector should be deployable to an embedded device and perform at high...
Understanding drivers' behavior under various challenging situations, to avoid accidents, is considered a key research area in the field of safety for Intelligent Transportation System (ITS). Various events (stressors) occurring while driving vehicles may negatively impact drivers' ability to detect and react to unpredictable incident that can possibly cause accidents. A cooperative stress detection...
In this paper a hybrid optimization method consisting in conjunction an evolutionary algorithm and a classical optimization method has been presented. This hybrid method has been used to select the parameters of a driver's seat of a special vehicle, which contributes directly to increase in driving comfort. A brief description of a vehicle mathematical model was formulated by using joint coordinates...
This paper describes the design of two variants of SENT driver structures, which offer a high degree of immunity against conducted electromagnetic interference (EMI) applied to their output pins: these circuits withstand 20 dBm and 30 dBm of “direct power injection” respectively without any on board capacitive and or resistive loading at the output, while keeping the electromagnetic emission (EME)...
This paper proposes a geometric model based lateral control system for a ground vehicle. Lateral control algorithm takes the advantages of two different path tracking methods at different path geometries. Two of the well-known geometric path tracking methods, namely Pure-Pursuit method and Stanley method, are combined with a simple and easy to implement approach. Pure-Pursuit method is very good at...
System landscapes within logistical scenarios is highly heterogenic. Adding specific mechanisms, e.g. to support planing, monitoring and analyses for fully electrical powered vehicles, could become a mess or at least a challenge. While our project Smart City Logistic (SCL) is trying to manage this extension for multiple logistic scenarios, other projects want to do comparable system extensions as...
Driving with distraction or losing alertness increases the risk of the traffic accident. The emerging Internet of Things (IoT) systems for smart driving hold the promise of significantly reducing road accidents. In particular, detecting the unsafe hand motions and warning the driver using smart sensors can improve the driver's self-alertness and the driving skill. However, due to the impact of the...
This paper is faced with group sensing problem, where HD map producers motivate private cars to collect data from real world. Group sensing needs vehicles to communicate physically, and drivers to collaborate strategically. First we consider communication module, three VANET-based methods are proposed to achieve inter-vehicle message relaying. Secondly, we consider collaboration module which motivates...
Up until now, law violation and drowsiness have been major causes of road traffic accident in Thailand. This study presents an approach to detect the risk due to drowsiness and distraction of a driver. In our method, techniques in computer vision are employed to extract facial features of the driver to determine his behaviors. Since the vehicle speed is also an important factor of the accident risk,...
Emergency vehicle prioritization is important to the efficiency of emergency services. To address certain challenges in emergency vehicle prioritization, we perform microscopic simulations of an intelligent transportation system, where emergency vehicles broadcast certain information about their routes to nearby vehicles and traffic lights. Our study shows that broadcasting the route information can...
In surface mine environment, the size of mining equipment is typically very huge. Therefore, the sight of equip- ment operators in high- mounted cockpits is severely limited and those operators are often unaware of the approaching or nearby vehicles. It is reported that this unawareness causes serious accidents, which motivates us for proximity detection of those vehicles. Inter-Vehicle Communication...
The effectiveness of Cooperative Intelligent Transport Systems (C-ITS), both on energy and emissions savings as well as operational improvements, is an on-going research area. This research evaluates the effect of a pilot study on speed advice service, which was implemented along a major urban arterial corridor in the city of Thessaloniki, Greece. Real-time data pertaining to the operation of the...
This paper describes the development of an advanced locomotive simulator for educational purposes. First, an overview of currently existing locomotive simulators is made. Next, requirements for the simulator are specified with the aim of significantly improving the reality of the simulation itself. Based on these requirements a modular system is developed. This system allows the use of common modules...
Vehicle speed prediction plays an important role in Data-Driven Intelligent Transportation System (D2ITS) and electric vehicle energy management. Accurately predicting vehicle speed for an individual trip is a challenging topic because vehicle speed is subjected to various factors such as route types, route curvature, driver behavior, weather and traffic condition. A big data based deep learning vehicle...
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