34,333 research outputs found

    Use of CCTV to determine road accident factors in urban areas

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    This paper sets out to assess whether there is a potential use for images collected through the increasingly ubiquitous use of CCTV cameras in urban areas as a means of increasing understanding of the causes of road traffic accidents. Information on causation and contributory factors is essential as a means of understanding why accidents occurred and how the occurrence of similar events may be prevented in the future. CCTV records of accidents could provide an independent perspective on an accident and have the potential to increase both the quality and quantity of information available to the safety researcher. This study focuses on an area of central Leeds in the UK and shows that an existing CCTV camera system used for urban traffic management reasons has the potential to 1 record around a quarter of the accidents which occur in the area, based on patterns of past occurrence. Most city centres in the UK will have similar camera systems set up. By the introduction of additional strategically placed cameras and replacement of existing cameras with ones dedicated to accident recording, this figure could be increased substantially. The paper also considers how effective cameras and video records will be as a means of identifying contributory factor information once an accident is recorded. The contributory factor classification used by a recently introduced system in Britain is assessed in terms of how visible each of the factors is likely to be on video and their relative frequency of occurrence. It is concluded that CCTV has a high potential to provide corroborative evidence about many of the most commonly occurring factors, and to throw further light on accident causation

    The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems

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    Scenario-based testing for the safety validation of highly automated vehicles is a promising approach that is being examined in research and industry. This approach heavily relies on data from real-world scenarios to derive the necessary scenario information for testing. Measurement data should be collected at a reasonable effort, contain naturalistic behavior of road users and include all data relevant for a description of the identified scenarios in sufficient quality. However, the current measurement methods fail to meet at least one of the requirements. Thus, we propose a novel method to measure data from an aerial perspective for scenario-based validation fulfilling the mentioned requirements. Furthermore, we provide a large-scale naturalistic vehicle trajectory dataset from German highways called highD. We evaluate the data in terms of quantity, variety and contained scenarios. Our dataset consists of 16.5 hours of measurements from six locations with 110 000 vehicles, a total driven distance of 45 000 km and 5600 recorded complete lane changes. The highD dataset is available online at: http://www.highD-dataset.comComment: IEEE International Conference on Intelligent Transportation Systems (ITSC) 201

    Hierarchical video surveillance architecture: a chassis for video big data analytics and exploration

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    There is increasing reliance on video surveillance systems for systematic derivation, analysis and interpretation of the data needed for predicting, planning, evaluating and implementing public safety. This is evident from the massive number of surveillance cameras deployed across public locations. For example, in July 2013, the British Security Industry Association (BSIA) reported that over 4 million CCTV cameras had been installed in Britain alone. The BSIA also reveal that only 1.5% of these are state owned. In this paper, we propose a framework that allows access to data from privately owned cameras, with the aim of increasing the efficiency and accuracy of public safety planning, security activities, and decision support systems that are based on video integrated surveillance systems. The accuracy of results obtained from government-owned public safety infrastructure would improve greatly if privately owned surveillance systems ‘expose’ relevant video-generated metadata events, such as triggered alerts and also permit query of a metadata repository. Subsequently, a police officer, for example, with an appropriate level of system permission can query unified video systems across a large geographical area such as a city or a country to predict the location of an interesting entity, such as a pedestrian or a vehicle. This becomes possible with our proposed novel hierarchical architecture, the Fused Video Surveillance Architecture (FVSA). At the high level, FVSA comprises of a hardware framework that is supported by a multi-layer abstraction software interface. It presents video surveillance systems as an adapted computational grid of intelligent services, which is integration-enabled to communicate with other compatible systems in the Internet of Things (IoT)

    The DRIVE-SAFE project: signal processing and advanced information technologies for improving driving prudence and accidents

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    In this paper, we will talk about the Drivesafe project whose aim is creating conditions for prudent driving on highways and roadways with the purposes of reducing accidents caused by driver behavior. To achieve these primary goals, critical data is being collected from multimodal sensors (such as cameras, microphones, and other sensors) to build a unique databank on driver behavior. We are developing system and technologies for analyzing the data and automatically determining potentially dangerous situations (such as driver fatigue, distraction, etc.). Based on the findings from these studies, we will propose systems for warning the drivers and taking other precautionary measures to avoid accidents once a dangerous situation is detected. In order to address these issues a national consortium has been formed including Automotive Research Center (OTAM), Koç University, Istanbul Technical University, Sabancı University, Ford A.S., Renault A.S., and Fiat A. Ş

    "Not the Usual Suspects": A Study of Factors Reducing the Effectiveness of CCTV

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    Previous research on the effectiveness of Closed Circuit Television (CCTV) has focused on critically assessing police and government claims that CCTV is effective in reducing crime. This paper presents a field study that investigates the relationship between CCTV system design and the performance of operator tasks. We carried out structured observations and interviews with 13 managers and 38 operators at 13 CCTV control rooms. A number of failures were identified, including the poor configuration of technology, poor quality video recordings, and a lack of system integration. Stakeholder communication was poor, and there were too many cameras and too few operators. These failures have been previously identified by researchers; however, no design improvements have been made to control rooms in the last decade. We identify a number of measures to improve operator performance, and contribute a set of recommendations for security managers and practitioners. Security Journal (2010) 23, 134-154. doi:10.1057/sj.2008.2; published online 6 October 200

    The development test flight of the flight telerobotic servicer

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    The Development Test Flight (DTF-1) is the first of two shuttle flights to test operations of the Flight Telerobotic Servicer (FTS) in space and to demonstrate its capabilities in performing tasks for Space Station Freedom. The DTF-1 system, which Martin Marietta Astronautics Group is designing and building for the Goddard Space Flight Center, will be flown in December, 1991, as an attached payload on the shuttle. The design of the DTF-1 system, the tests to be performed, and the data to be gathered are discussed
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