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Current traffic monitoring is limited by the small coverage of camera surveillance systems, for example, a specific area around one road intersection. Satellite high definition videos are becoming available which can provide videos over several squared kilometers. Thus, these videos introduce new possibilities for better traffic control and management. However, parallax motions caused by the movements...
This paper proposes a novel estimation method using finite impulse response (FIR) filter for the vehicle roll and bank angles. A vehicle model was constructed using the bicycle model and roll motion model and has parameter uncertainties. The proposed method ensures robust to vehicle parameter uncertainties and has no risk of divergence. Furthermore, the proposed method does not need to use expensive...
The core feature of any intelligent transportation system (ITS) is the vehicle measurement technique incorporated to measure road traffic volumes. Sensors or detectors placed along roads are used to acquire traffic flow data for further processing either manually or through fully automated intelligent systems. Although several different technologies exist, no single vehicle count method is absolutely...
Mapping is a very critical issue for enabling autonomous driving. This paper proposes a robust approach to generate high definition maps based on LIDAR point clouds and post-processed localization measurements. Many problems are addressed including quality, saving size, global labeling and processing time. High quality is guaranteed by accumulating and killing the sparsity of the point clouds in a...
Intelligent automobiles and advanced driver assistance systems (ADAS) are some of the major technological developments that affect human daily life. Today, many studies are being generated to develop state of the art transportation systems. The general objective in these studies is to cope with negative effects of traffic. In this work, our aim is to contribute to the development of ADAS by determining...
In this paper, driver intention estimation near a road intersection is presented, using discrete hidden Markov models (HMM) and the Hybrid State System (HSS) framework as basis. The development of Advanced Driver Assistance Systems (ADAS) has assisted drivers in many driving scenarios and resulted in safe driving. Developing techniques to estimate driver's intention leads to the advancement of ADAS...
In this paper, the problem of developing a model for signal control system with transit priority using Colored Petri Nets (CPNs) is considered. In a regular four phases signal lights control model, transit detection and two kinds of transit priority strategies are integrated to obtain Colored Petri Nets based transit priority signal control model. The resulting model ensures that transit can pass...
Autonomous vehicles pose new challenges to their testing, which is required for safety certification. While Autonomous vehicles will use training sets as specification for machine learning algorithms, traditional validation depends on the system’s requirements and design.The presented approach uses training sets which are observations of traffic situations as system specification. It aims...
Within the world of wireless technologies, Bluetooth has recently been at the forefront of innovation. It is becoming increasingly relevant for vehicles to become aware of their surroundings. Therefore, having knowledge of nearby Bluetooth devices, both inside and outside other vehicles, can provide the listening vehicles with enough data to learn about their environment. In this paper, we collect...
This paper is on a connected and autonomous vehicle hardware-in-the-loop (HiL) simulator for developing automated driving algorithms. This simulator allows the user to run highly realistic hardware-in-the-loop simulation of connected and autonomous driving functions. The HiL simulator of this paper consists of a dSPACE Scalexio system which runs Carsim Real Time with Traffic and Sensors and is connected...
Conventional traffic light control systems are based on fixed time intervals of the traffic lights. These conventional fixed traffic light controllers have limitations and are less efficient because they use a hardware, which functions according to the program that lacks the flexibility of modification and adaptation on a real time basis. Thus due to the fixed time intervals of green and red signals...
In this paper we propose a vehicular speed learning framework that recommends best traffic load based on a particularly required latency and throughput conditions to be achieved. The framework is composed of two main layers, the base layer and two enhancement layers. The base layer aims at providing an in-vehicle wireless receiver to inform the driver about the speed limit within the area he/she is...
The basis of this study is to create an insight for target vehicle path following or improving situational awareness by using path accumulation and ego-motion compensation. Possible application variants of the strategy, for highways and urban roads are also described. The study is also extended for enhancing path accumulation in noisy environment or sensing by making use of spline based curve approximation...
Traffic signal control system is now become very challenging task. It is necessary make road traffic decent, safe, less time and fuel consuming. There is a requirement to improvise the traffic signal control for better traffic control. In past few years traffic control system handles such a situation but not that much effectively because they are static. There should be a system which should be dynamic...
With the construction of highway in China, the transportation industry is gradually stepping into the maintenance stage. Whereas the current linear stake number method cannot accurately locate the pavement disease, the road identification theory is introduced to solve the problem of locating pavement disease and the chain scission on highway effectively. However, it has brought many difficulties to...
Heavy vehicle traffic and flooded areas are problems experienced on roads because of unimproved road infrastructures and environmental deviations. These factors affect vehicle drivers negatively as they contribute to stress, health problems, and wastefulness of time. This study developed a system called ArRoad that monitors and analyzes vehicle traffic and flooded areas using network of sensors and...
The Internet of Things (IoT) is a very promising concept that by connecting numerous devices to the internet and extracting large sums of information (BigData) can enable the realisation of various futuristic scenarios. In order to develop and assess future applications and services, it is necessary the availability of datasets that can be used to train, test and cross validate. Project SCoT (Smart...
VANET and cognitive radio network (CRN) are both new emerging technologies in wireless networking. The application of CR concept in wireless communication systems for intelligent vehicles has been envisioned as a promising idea towards solving the problem of scarce spectrum. This paper discusses CR technologies for VANETs aimed at opportunistic spectrum access (OSA) for improved vehicular communication...
Smart cities are the new settlement structures formed by new technologies that change human life. Among these technologies, intelligent automobiles have an important place, and many scientific studies on it have been realized. Especially Tesla, Apple, and Google have completed their prototypes of autonomous automobiles. One of the indispensable part of recent automotive technologies is Advanced Driver...
An accurate and robust lane recognition is a key aspect for autonomous cars of the near future. This paper presents the design and implementation of a robust autonomous driving algorithm using the proven Viola-Jones object detection method for lane recognition. The Viola-Jones method is used to detect traffic cones that are located besides the road as it can be done in emergency situations. The positions...
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