2018
DOI: 10.20858/tp.2018.13.2.1
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Speed Management Efficacy on National Roads - Early Experiences of Sectional Speed System Functioning in Podlaskie Voivodship

Abstract: Driving speed is one of the most important factors in road safety, and speed not only affects the severity of a crash, but is also related to the risk of being involved in a crash. Inappropriate speed is responsible for more than a third of all fatal accidents occurring on the roads. In Poland, the problem of speeding drivers is widely common. Hence, effective speed management and enforcement of speed limits on existing road plays an important role. Possible solutions for rural roads are very limited and have … Show more

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Cited by 6 publications
(5 citation statements)
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“…The establishment of traffic calming groups must provide good uniformity of speed. The lack of uniformity of speed can lead to frequent and dangerous deceleration and acceleration maneuvers [26]. These maneuvers cause higher fuel consumption and noise emissions, which have a negative impact on the environment [27].…”
Section: Introductionmentioning
confidence: 99%
“…The establishment of traffic calming groups must provide good uniformity of speed. The lack of uniformity of speed can lead to frequent and dangerous deceleration and acceleration maneuvers [26]. These maneuvers cause higher fuel consumption and noise emissions, which have a negative impact on the environment [27].…”
Section: Introductionmentioning
confidence: 99%
“…); physical obstructions (raised median through intersections, semi and diagonal diverter, right-in and rightout island, etc. ); and signs and pavement markings (Kveladze and Agerholm, 2018;Gonzalo-Orden, Rojo, Pérez-Acebo and Linares, 2016;Pérez-Sansalvador, Lakouari, García-Díaz, and Pomares Hernández, 2020;Torres, Cloutier, Bergeron, and St-Denis, 2019;Ziolkowski, 2018). In urban areas, the succession of traffic calming measures and traffic lights maintains the speed of vehicles low.…”
Section: Introductionmentioning
confidence: 99%
“…In the last two decades, there have been significant improvements on the camera sensors, in terms of image quality and resolution, and on the digital infrastructure to transmit and store video data. Nevertheless, with the possible exception of Automatic Number Plate Recognition (ANPR) for speed control (e.g., see Ziółkowski [10]) and to analyze passenger and freight movements, as discussed by Hadavi et al [11], the analysis of the video data of CCTV systems in public transport networks has remained largely based on manual analysis, mostly because of the challenges posed by localizing people, their motions, and, ultimately, their behavior in realistic scenarios. More recently, however, there have been major scientific and technological improvements in computer vision, led by intelligent sensors that use deep-learning methods and that can offer a way forward.…”
Section: Introductionmentioning
confidence: 99%