980 resultados para Automobile driving on highways


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A new method for the detection of abnormal vehicle trajectories is proposed. It couples optical flow extraction of vehicle velocities with a neural network classifier. Abnormal trajectories are indicative of drunk or sleepy drivers. A single feature of the vehicle, eg., a tail light, is isolated and the optical flow computed only around this feature rather than at each pixel in the image.

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Mode of access: Internet.

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Suburbanisation has been internationally a major phenomenon in the last decades. Suburb-to-suburb routes are nowadays the most widespread road journeys; and this resulted in an increment of distances travelled, particularly on faster suburban highways. The design of highways tends to over-simplify the driving task and this can result in decreased alertness. Driving behaviour is consequently impaired and drivers are then more likely to be involved in road crashes. This is particularly dangerous on highways where the speed limit is high. While effective countermeasures to this decrement in alertness do not currently exist, the development of in-vehicle sensors opens avenues for monitoring driving behaviour in real-time. The aim of this study is to evaluate in real-time the level of alertness of the driver through surrogate measures that can be collected from in-vehicle sensors. Slow EEG activity is used as a reference to evaluate driver's alertness. Data are collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device (N=25 participants). Four different types of highways (driving scenario of 40 minutes each) are implemented through the variation of the road design (amount of curves and hills) and the roadside environment (amount of buildings and traffic). We show with Neural Networks that reduced alertness can be detected in real-time with an accuracy of 92% using lane positioning, steering wheel movement, head rotation, blink frequency, heart rate variability and skin conductance level. Such results show that it is possible to assess driver's alertness with surrogate measures. Such methodology could be used to warn drivers of their alertness level through the development of an in-vehicle device monitoring in real-time drivers' behaviour on highways, and therefore it could result in improved road safety.

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Texas State Department of Highways and Public Transportation, Transportation Planning Division, Austin

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In previous research (Chung et al., 2009), the potential of the continuous risk profile (CRP) to proactively detect the systematic deterioration of freeway safety levels was presented. In this paper, this potential is investigated further, and an algorithm is proposed for proactively detecting sites where the collision rate is not sufficiently high to be classified as a high collision concentration location but where a systematic deterioration of safety level is observed. The approach proposed compares the weighted CRP across different years and uses the cumulative sum (CUSUM) algorithm to detect the sites where changes in collision rate are observed. The CRPs of the detected sites are then compared for reproducibility. When high reproducibility is observed, a growth factor is used for sequential hypothesis testing to determine if the collision profiles are increasing over time. Findings from applying the proposed method using empirical data are documented in the paper together with a detailed description of the method.

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Alcohol-related driving is a longstanding, serious problem in China (Li, Xie, Nie, & Zhang, 2012). On 1st May, 2011 a national law was introduced to criminalize drunk driving, and imposed serious penalties including jail for driving with a blood alcohol level of above 80mg/100ml. This pilot study, undertaken a year after introduction of the law, sought traffic police officers’ perceptions of drink driving and the practice of breath alcohol testing (BAT) in a large city in Guangdong Province, southern China. A questionnaire survey and semi-structured interviews were used to gain an in-depth understanding of issues relevant to alcohol-related driving. Fifty-five traffic police officers were recruited for the survey and six traffic police officers with a variety of working experience including roadside alcohol breath testing, traffic crash investigation and police resourcing were interviewed individually. The officers were recruited by the first author with the assistance of the staff from Guangdong Institute of Public Health, Centre for Disease Control and Prevention (CDC). Interview participants reported three primary reasons why people drink and drive: 1) being prepared to take the chance of not being apprehended by police; 2) the strong traditional Chinese drinking culture; and 3) insufficient public awareness about the harmfulness of drink driving. Problems associated with the process of breath alcohol testing (BAT) were described and fit broadly into two categories: resourcing and avoiding detection. It was reported that there were insufficient traffic police officers to conduct routine traffic policing, including alcohol testing. Police BAT equipment was considered sufficient for routine traffic situations but not highway traffic operations. Local media and posters are used by the Public Security Bureau which is responsible for education about safe driving but participants thought that the education campaigns are limited in scope. Participants also described detection avoidance strategies used by drivers including: changing route; ignoring a police instruction to stop; staying inside the vehicle with windows and doors locked to avoid being tested; intentionally not performing breath tests correctly; and arguing with officers. This pilot study provided important insights from traffic police in one Chinese city which suggest there may be potential unintended effects of introducing more severe penalties including a range of strategies reportedly used by drivers to avoid detection. Recommendations for future research include a larger study to confirm these findings and examine the training and education of drivers; the focus and reach of publicity; and possible resource needs to support police enforcement.

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 This article presents SOR, a vehicular social network to enable social communications and interactions among users on the road during their highway travels. Motivated by the limited connection to Internet contents and services, the essential goal of SOR is to encourage distributed users on the road to spontaneously contribute as the information producer, assembler, and distributer in order to provide timely and localized infotainments to each other through low-cost inter-vehicle communications. To be specific, SOR enables individual users to maintain a personal blog, similar to one on Facebook and Twitter, over which users can create and share personal content information to the public such as travel blogs with pictures and videos. By accessing each other's SOR blogs and commenting on interesting topics, passengers can exchange messages and initiate social interactions. In the specific highway environment, SOR addresses two challenges in the context of vehicular social communications. First, vehicular social communications tend to be frequently interrupted by diverse vehicle mobility and intermittent intervehicle connections, which is annoying to users. To address this issue, SOR adopts a proactive mechanism by estimating the connection time between peer vehicles, and recommending vehicles with relatively long-lasting and stable intervehicle connections for social communications. Second, as users on the road are typically strangers to each other, they are reluctant to disclose personal information to others. This makes it challenging to identify users of shared interests and accordingly restricts the scale of users' social interactions. To remedy that, SOR provides a secured solution to protect sensitive user information during social communications. Lastly, we use simulations to verify the performance of SOR. © 2015 IEEE.

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BACKGROUND: Central and peripheral vision is needed for object detection. Previous research has shown that visual target detection is affected by age. In addition, light conditions also influence visual exploration. The aim of the study was to investigate the effects of age and different light conditions on visual exploration behavior and on driving performance during simulated driving. METHODS: A fixed-base simulator with 180 degree field of view was used to simulate a motorway route under daylight and night conditions to test 29 young subjects (25-40 years) and 27 older subjects (65-78 years). Drivers' eye fixations were analyzed and assigned to regions of interests (ROI) such as street, road signs, car ahead, environment, rear view mirror, side mirror left, side mirror right, incoming car, parked car, road repair. In addition, lane-keeping and driving speed were analyzed as a measure of driving performance. RESULTS: Older drivers had longer fixations on the task relevant ROI, but had a lower frequency of checking mirrors when compared to younger drivers. In both age groups, night driving led to a less fixations on the mirror. At the performance level, older drivers showed more variation in driving speed and lane-keeping behavior, which was especially prominent at night. In younger drivers, night driving had no impact on driving speed or lane-keeping behavior. CONCLUSIONS: Older drivers' visual exploration behavior are more fixed on the task relevant ROI, especially at night, when driving performance becomes more heterogeneous than in younger drivers.

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Alabama Office of Highway Traffic Safety, Montgomery

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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

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Mode of access: Internet.

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Mode of access: Internet.