This is an author produced version of an article published in Accident and Analysis Journal. It has been peer reviewed but does not contain the publishers formatting or pagination. AbstractThis paper reports on the development of a method for automatic monitoring of safety at Pelican crossings. Historically, safety monitoring has typically been carried out using accident data, though given the rarity of such events it is difficult to quickly detect change in accident risk at a particular site. An alternative indicator sometimes used is traffic conflicts, though this data can be time consuming and expensive to collect. The method developed in this paper uses vehicle speeds and decelerations collected using standard in-situ loops and tubes, to determine conflicts using vehicle decelerations and to assess the possibility of automatic safety monitoring at Pelican crossings. Information on signal settings, driver crossing behaviour, pedestrian crossing behaviour and delays, and pedestrian-vehicle conflicts was collected synchronously through a combination of direct observation, video analysis, and analysis of output from tube and loop detectors. Models were developed to predict safety, i.e. pedestrian-vehicle conflicts using vehicle speeds and decelerations.
Speed is one of the main risk factors in road traffic safety and become a traffic problem in developing countries. Three factors that cause accidents are human factor, vehicle, and environment. Speeding is one of the main cause factors in traffic accident. Traffic speed must be limited adjust with the activities in the street and potential accident. The aim of this research is to determine the maximum speed limit in urban road to increase traffic safety and to analyze the percentage of vehicle exceeding speed limit. The method to determine maximum speed limits using 85th percentile. Based on the analysis result, the proposed maximum speed limit on urban road for arterial road type 4/2-UD residential and 4/2-UD CBD is 60 km/h for motorcycle and passenger car, 55 km/h for pick up and light truck, and 50 km/h for bus and truck. Proposed maximum speed limit for collector road type 2/1-UD office area is 45 km/h for motorcycle and 40 km/h for four-wheeled vehicles or more while for collector road type 2/1-UD CBD is 40 km/h for motorcycle and 35 km/h for four-wheeled vehicles or more. The installation of speed limit sign is less effective to reduce the vehicle speed, the speed only reduce 2.9-55 km/h (5.6-10.1%). More than 46.5% of motorcycle users ride exceeding speed limit followed by the passenger cars users (39.43%), microbus/city bus at 31.63%, bus Trans at 28.75%, pick up and light truck at 24.69%. The maximum speed limit in school safety zone on hours/after school is 30 km/h with the consideration that the pedestrian fatality rate on 30 km/h has probability of death 10%.
Deceleration rate, time to collision and impact speed have been commonly employed as accident risk indicators. However, it is hard to assess the level of accident risk since these indicators have not been developed with measurable score criteria. This study focuses on the determination of measurable risk indicators which could be used to assess accident risk level and to determine more appropriate accident risk management strategies by using the descriptive qualitative approach. The data were collected from a braking maneuver test conducted on a dry and level closed circuit course. Risk was a function of accident probability and its possible consequences, while accident probability was determined based on the safety factor, i.e. the ratio of available stopping sight distance (ASSD) to minimum SSD (MSSD), which was used to determine the margin of safety. Subsequently, accident consequence was determined using the impact speed at a predicted point of collision along the braking distance path. The results show that accident risk could be easily determined using the proposed indicators, whilst an objective and appropriate accident risk management strategy could be determined based on the minimum margin of safety value which could be obtained from each risk exposure.
Kota Yogyakarta sebagai pusat tarikan kegiatan pariwisata, ekonomi dan pendidikan telah memiliki pengaruh yang berkembang hingga ke aglomerasinya. Kondisi ini menyebabkan bertambahnya demand terhadap kebutuhan pelayanan transportasi. Manajemen sistem transportasi bertujuan meningkatkan efisiensi infrastruktur yang telah ada dan meningkatkan pelayanan dan penggunaan angkutan umum. Manajemen sistem transportasi memastikan berputarnya roda perekonomian namun juga mempertahankan kinerja transportasi. Penelitian ini bertujuan mengetahui kinerja manajemen sistem transportasi perkotaan Yogyakarta eksisting serta merencanakan manajemen sistem transportasi perkotaan Yogyakarta ideal yang dibuat dengan siklus perencanaan berdasarkan bagan alir dari Gray dan Hoel. Siklus ini mengidentifikasi data kinerja, permasalahan dan kesempatan yang ada, biaya, dampak dan prioritas proyek. Metode analisis SWOT dipakai untuk mengidentifikasi permasalahan dan kesempatan dalam siklus perencanaan sebagai dasar penentuan program dan kegiatan selanjutnya. Mixed method menjadi dasar metode dalam penelitian ini yang menggabungkan metode kualitatif dengan kuantitatif. Hasil dari penelitian ini adalah prioritas perencanaan manajemen sistem transportasi Perkotaan Yogyakarta secara berurutan: Rencana Jaringan Transportasi Jalan, Rencana Tata Ruang Perkotaan Yogyakarta, Rencana Sistem Angkutan Umum, Rencana Sistem Angkutan Wisata, Rencana Fasilitasi Perparkiran dan Rencana Pemanfaatan Terminal Giwangan
Thus far, minimum stopping sight distance (SSD) is determined based on design speed, a minimum reaction time of 1.64 s and a deceleration rate of 3.4 m/s², whereas in certain situations the latter can be shorter than 1 s and higher than 4.5 m/s². Awareness of this can trigger speculative behavior, as can be seen from the choice of speed and/or the critical crossing gap, which is often smaller than the recommended minimum SSD. This study focused on the development of an appropriate minimum SSD model that is suited to risky conditions at an unsignalized intersection and its possible usage in accident risk evaluation, particularly for motorcyclists. The data were taken from direct measurements and related studies. Variables that potentially influence minimum SSD were tested. The results strongly suggest that the speed reduction achieved by downshifting significantly influences both the braking distance and the impact speed. Moreover, the minimum SSD obtained from the proposed model significantly differs from that obtained from a similar model recommended by AASHTO. Therefore, it is worthwhile to consider the application of the proposed minimum SSD as an accident probability indicator parameter.
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