250 resultados para Lane drops.


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'Homegrown is an initiative of the Design Institute of Australia–Queensland Branch to promote the collaboration and cultivation of local design talent in Queensland and strengthen the connection between design, plate, planet, people and culture.' Homegrown 2011 Exhibition Catalogue Excerpt

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In Victoria, as in other jurisdictions, there is very little research on the potential risks and benefits of lane filtering by motorcyclists, particularly from a road safety perspective. This on-road proof of concept study aimed to investigate whether and how lane filtering influences motorcycle rider situation awareness at intersections and to address factors that need to be considered for the design of a larger study in this area. Situation awareness refers to road users’ understanding of ‘what is going on’ around them and is a critical commodity for safe performance. Twenty-five experienced motorcyclists rode their own instrumented motorcycle around an urban test route in Melbourne whilst providing verbal protocols. Lane filtering occurred in 27% of 43 possible instances in which there were one or more vehicles in the traffic queue and the traffic lights were red on approach to the intersection. A network analysis procedure, based on the verbal protocols provided by motorcyclists, was used to identify differences in motorcyclist situation awareness between filtering and non-filtering events. Although similarities in situation awareness across filtering and nonfiltering motorcyclists were found, the analysis revealed some differences. For example, filtering motorcyclists placed more emphasis on the timing of the traffic light sequence and on their own actions when moving to the front of the traffic queue, whilst non-filtering motorcyclists paid greater attention to traffic moving through the intersection and approaching from behind. Based on the results of this study, the paper discusses some methodological and theoretical issues to be addressed in a larger study comparing situation awareness between filtering and non-filtering motorcyclists.

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This paper comprehensively reviews recent developments in modeling lane-changing behavior. The major lane changing models in the literature are categorized into two groups: models that aim to capture the lane changing decision-making process, and models that aim to quantify the impact of lane changing behavior on surrounding vehicles. The methodologies and important features (including their limitations) of representative models in each category are outlined and discussed. Future research needs are determined.

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Weaving sections, a common design of motorways, require extensive lane-change manoeuvres. Numerous studies have found that drivers tend to make their lane changes as soon as they enter the weaving section, as the traffic volume increases. Congestion builds up as a result of this high lane-changing concentration. Importantly, such congestion also limits the use of existing infrastructure, the weaving section downstream. This behaviour thus affects both safety and operational aspects. The potential tool for managing motorways effectively and efficiently is cooperative intelligent transport systems (C-ITS). This research investigates a lane-change distribution advisory application based on C-ITS for weaving vehicles in weaving sections. The objective of this research is to alleviate the lane-changing concentration problem by coordinating weaving vehicles to ensure that such lane-changing activities are evenly distributed over the existing weaving length. This is achieved by sending individual messages to drivers based on their location to advise them when to start their lane change. The research applied a microscopic simulation in AIMSUN to evaluate the proposed strategy’s effectiveness in a one-sided ramp weave. The proposed strategy was evaluated using different weaving advisory proportions, traffic demands and penetration rates. The evaluation revealed that the proposed lane-changing advisory has the potential to significantly improve delay.

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This study examines the benefits of Cooperative Intelligent Transport Systems (C-ITS) in weaving sections. The research proposes a lane-changing advisory application to alleviate the lane-changing concentration in weaving sections by coordinating weaving vehicles. While non-weaving vehicles travel as normal, weaving vehicles are monitored and advised through personalized messages based on their destination lane. The findings of this research, derived from a microscopic simulation in AIMSUN, reveal that the proposed strategy has the potential to improve delay significantly and that it can be applied to any existing one-sided weaving sections.

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Understanding pedestrian crash causes and contributing factors in developing countries is critically important as they account for about 55% of all traffic crashes. Not surprisingly, considerable attention in the literature has been paid to road traffic crash prediction models and methodologies in developing countries of late. Despite this interest, there are significant challenges confronting safety managers in developing countries. For example, in spite of the prominence of pedestrian crashes occurring on two-way two-lane rural roads, it has proven difficult to develop pedestrian crash prediction models due to a lack of both traffic and pedestrian exposure data. This general lack of available data has further hampered identification of pedestrian crash causes and subsequent estimation of pedestrian safety performance functions. The challenges are similar across developing nations, where little is known about the relationship between pedestrian crashes, traffic flow, and road environment variables on rural two-way roads, and where unique predictor variables may be needed to capture the unique crash risk circumstances. This paper describes pedestrian crash safety performance functions for two-way two-lane rural roads in Ethiopia as a function of traffic flow, pedestrian flows, and road geometry characteristics. In particular, random parameter negative binomial model was used to investigate pedestrian crashes. The models and their interpretations make important contributions to road crash analysis and prevention in developing countries. They also assist in the identification of the contributing factors to pedestrian crashes, with the intent to identify potential design and operational improvements.

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After a year long public campaign, the Future Fund has today announced plans to end its $222 million investment in tobacco.

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The purpose of "Claiming the Lane way" was to question the identity and potential use of Brisbane lane ways through the application of street furniture design in collaboration with industry partners and local stakeholders. The basis for student furniture design and prototype construction was provided by the site specific stakeholders brief requirements. This engagement extended to the donation of construction materials, structural engineering expertise, funding and ultimately the multi disciplinary public exhibition event - "Changing Lanes". The lane way was demonstrably activated through the language of design and creative expression to bring a community together as well as identifying the potential of the lane way as significant and valuable public space in the urban environment.

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Car following (CF) and lane changing (LC) are two primary driving tasks observed in traffic flow, and are thus vital components of traffic flow theories, traffic operation and control. Over the past decades a large number of CF models have been developed in an attempt to describe CF behaviour under a wide range of traffic conditions. Although CF has been widely studied for many years, LC did not receive much attention until recently. Over the last decade, researchers have slowly but surely realized the critical role that LC plays in traffic operations and traffic safety; this realization has motivated significant attempts to model LC decision-making and its impact on traffic. Despite notable progresses in modelling CF and LC, our knowledge on these two important issues remains incomplete because of issues related to data, model calibration and validation, human factors, just to name a few. Thus, this special issue will focus on latest developments in modelling, calibrating, and validating two primary vehicular interactions observed in traffic flow: CF and LC.