47 research outputs found

    The Determination of Bus Service Frequency Using Cost-benefit Approach

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    The determination of bus service frequency using cost-benefit approach is presented in this paper. This study was conducted in Malaysia where bus operators could provide feasible bus services using this method. The investment costs include all costs for vehicle, human resources, workshop, operational facilities, andsupporting facilities while the benefits are expected from ticket fare collected and fuel subsidy. The primary data consists of passenger number, ticket fare, travel time, number of vehicles, and route length. The secondary data, provided by bus operators, include vehicle investment and operation and maintenance costs. The results indicate that this method is applicable and can be used by bus operators to provide feasible bus services with adequate frequencies

    THE DETERMINATION OF BUS SERVICE FREQUENCY USING COST-BENEFIT APPROACH

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    The determination of bus service frequency using cost-benefit approach is presented in this paper. This study was conducted in Malaysia where bus operators could provide feasible bus services using this method. The investment costs include all costs for vehicle, human resources, workshop, operational facilities, andsupporting facilities while the benefits are expected from ticket fare collected and fuel subsidy. The primary data consists of passenger number, ticket fare, travel time, number of vehicles, and route length. The secondary data, provided by bus operators, include vehicle investment and operation and maintenance costs. The results indicate that this method is applicable and can be used by bus operators to provide feasible bus services with adequate frequencies.Keywords: cost-benefit analysis, bus service, service frequency

    THE DETERMINATION OF BUS SERVICE FREQUENCY USING COST-BENEFIT APPROACH

    Get PDF
    The determination of bus service frequency using cost-benefit approach is presented in this paper. This study was conducted in Malaysia where bus operators could provide feasible bus services using this method. The investment costs include all costs for vehicle, human resources, workshop, operational facilities, andsupporting facilities while the benefits are expected from ticket fare collected and fuel subsidy. The primary data consists of passenger number, ticket fare, travel time, number of vehicles, and route length. The secondary data, provided by bus operators, include vehicle investment and operation and maintenance costs. The results indicate that this method is applicable and can be used by bus operators to provide feasible bus services with adequate frequencies.Keywords: cost-benefit analysis, bus service, service frequency

    ASSESSMENT OF BUS SYSTEM SERVICE AND PERFORMANCE FOR PUBLIC TRANSPORT IMPROVEMENT

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    This study, entitled “Assessment of Bus System Service and Performance for Public Transport Improvement” was based on a case study of bus service at the Ipoh- Lumut corridor in Perak, Malaysia. This corridor is serviced by stage buses in mixed traffic. The problems faced are low quality of buses, inconvenience, long waiting time, limited facilities, low reliability and low passengers loading which have caused the system to be unattractive to passengers. The purposes of the study were to analyze bus service characteristics and performance of the bus system, to assess bus service reliability and to formulate strategies for the improvement of bus service performance. A fieldwork investigation was conducted covering preliminary survey, primary data survey and secondary data collection. The primary data consisted of bus service operation and passenger boarding and alighting. The approaches of study included description of study area, analysis of bus service characteristics, performance, improvement strategies, evaluation of ridership factors elasticity and sensitivity of bus service demand. Bus service characteristics were analyzed based on fundamental theory, World Bank Standard and TCQSM Standard. In addition, statistical methods such as ANOVA, MARE, MAPPE, ARIMA, MLR and SNN model were applied. The proposed performance indicators to evaluate bus service quality and reliability comprised of on-time performance, regularity, punctuality and waiting time. The concept of elasticity and sensitivity were explored to evaluate bus service demand with respect to ridership factors changes. Finally, gravity model was calibrated to estimate passenger trip distribution by using data of passenger boarding and alighting. From this study, it was concluded that the improvement of bus service quality and performance can be done by changing of frequency, the capacity of passenger and improving the bus service reliability. Based on the elasticity analysis, in the service characteristics category, travel time was an elastic factor, whereas ticket fare, fuel price, per capita income, frequency and headway were inelastic factors in the bus service demand. Meanwhile, in the service reliability category, the punctuality, waiting time, regularity and on-time performance were categorized as elastic factors. Moreover, the bus service demand increased by changes of factors such as the increase in punctuality, decrease in waiting time, increase in level of service and increase in regularity

    Pengukuran dan Perekaman data Ketidakrataan Perkerasan Jalan dengan Sensor Ultrasonic pada Rolling Straight Edge

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    Ketidakrataan permukaan jalan adalah salah satu faktor pelayanan perkerasan yang mempengaruhi kenyamanan (kualitas berkendara) pengemudi. Persyaratan utama untuk jalan yang baik adalah struktur yang kuat, datar, tahan air, tahan lama, dan ekonomis sepanjang masa pakai. Pengukuran ketidakrataan permukaan jalan belum banyak dilakukan di Indonesia mengingat keterbatasan peralatan sehingga pemantauan dan evaluasi jalan yang ada tidak dapat dilakukan dengan benar sesuai dengan standar jalan. Tingkat ketidakrataan permukaan jalan dapat diukur dengan menggunakan berbagai metode yang telah direkomendasikan oleh Bina Marga dan AASHTO. Metode pengukuran ketidakrataan permukaan jalan yang digunakan adalah metode Transport Research Laboratory dengan Rolling Straight Edge. Departemen Teknik Sipil memiliki dua unit Rolling Straight Edge, tetapi fasilitas pembacaan data hanya mengandalkan pembacaan jarum skala manual, membuatnya kurang cepat dan efektif. Tujuan dari penelitian ini adalah mengembangkan instrumen untuk membaca data ketidakrataan dengan sensor ultrasonic untuk menggantikan pembacaan manual pada Rolling Straight Edge. Dengan data logger sensor ultrasonik ini dikembangkan, diharapkan pengukuran dan analisis data dapat dilakukan lebih cepat dan efisien. Objek perkerasan jalan yang diukur adalah lantai ubin, perkerasan paving block, perkerasan aspal, dan perkerasan beton. Hasil yang diperoleh bahwa analisis dan evaluasi kondisi tingkat ketidakrataan jalan dari pengembangan instrumen sensor ultrasonic pada Rolling Straight Edge lebih cepat, lebih efisien dan memiliki produktivitas pengukuran yang lebih tinggi

    Investigasi Kekesatan Perkerasan Jalan Menggunakan Wessex Skid Tester ( Investigation of Skid resistance of Road Pavement Using the Wessex Skid Tester)

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    ABSTRAK Skid resistance of road pavement present the resistance condition between surfaces of pavement and tire so that vehicle do not slipped whether at the time of wet or dry road surfaces. This article aim to explain the result of measurement of skid resistance of road using the Wessex Skid Tester. Statistical Analysis is made to evaluate the skid resistance level of road pavement and to compare the level of skid resistance among three types of road pavement structure in different location. Three types of structure of road pavement therewith the location successively are asphalt concrete (Kaliurang Street), concrete block (Teknika Selatan - Keselzatan-Bhineka Street) and hot rolled sheet (HRS) in Yacaranda Street. The result of analysis is level of skid resistance related to each types of road and comparison of three road structure types. Here, the rate of skid resistance of asphalt concrete, concrete block and HRS successively are 45,29 (standard deviation of 3,55), 48,18 (standard deviation of 3,57), and 60,05 (standard deviation of 6,66). Concrete block paving has the higher level of skid resistance than asphalt concrete. The level of skid resistance of HRS is higher than the concrete block caused by the HRS condition at the time of that measurement was medium damage. Keywords: skid resistance, slip, and pavement

    BUS TRAVEL TIME IN THE MIXED TRAFFIC BASED ON STATISTICA NEURAL NETWORK

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    This paper presents the assessment of a number of factors affecting bus travel time and a relationship model between those factors and bus travel time. Statistica Neural Network (SNN) tool is used to solve this complex phenomenon. Data collected include bus travel time, distance, average speed, and number of bus stop. The results show that bus travel time is well predicted using variables of distance, average speed, and number of bus stops. The bus travel time increased due to the increase of distance and number of bus stops, while the higher the average speed from one stop to another, the lower bus travel time.Keywords: bus travel time prediction, distance, average speed of bus, number of bus sto

    ASSESSMENT OF BUS SYSTEM SERVICE AND PERFORMANCE FOR PUBLIC TRANSPORT IMPROVEMENT

    Get PDF
    This study, entitled “Assessment of Bus System Service and Performance for Public Transport Improvement” was based on a case study of bus service at the Ipoh- Lumut corridor in Perak, Malaysia. This corridor is serviced by stage buses in mixed traffic. The problems faced are low quality of buses, inconvenience, long waiting time, limited facilities, low reliability and low passengers loading which have caused the system to be unattractive to passengers. The purposes of the study were to analyze bus service characteristics and performance of the bus system, to assess bus service reliability and to formulate strategies for the improvement of bus service performance. A fieldwork investigation was conducted covering preliminary survey, primary data survey and secondary data collection. The primary data consisted of bus service operation and passenger boarding and alighting. The approaches of study included description of study area, analysis of bus service characteristics, performance, improvement strategies, evaluation of ridership factors elasticity and sensitivity of bus service demand. Bus service characteristics were analyzed based on fundamental theory, World Bank Standard and TCQSM Standard. In addition, statistical methods such as ANOVA, MARE, MAPPE, ARIMA, MLR and SNN model were applied. The proposed performance indicators to evaluate bus service quality and reliability comprised of on-time performance, regularity, punctuality and waiting time. The concept of elasticity and sensitivity were explored to evaluate bus service demand with respect to ridership factors changes. Finally, gravity model was calibrated to estimate passenger trip distribution by using data of passenger boarding and alighting. From this study, it was concluded that the improvement of bus service quality and performance can be done by changing of frequency, the capacity of passenger and improving the bus service reliability. Based on the elasticity analysis, in the service characteristics category, travel time was an elastic factor, whereas ticket fare, fuel price, per capita income, frequency and headway were inelastic factors in the bus service demand. Meanwhile, in the service reliability category, the punctuality, waiting time, regularity and on-time performance were categorized as elastic factors. Moreover, the bus service demand increased by changes of factors such as the increase in punctuality, decrease in waiting time, increase in level of service and increase in regularity

    BUS TRAVEL TIME IN THE MIXED TRAFFIC BASED ON STATISTICA NEURAL NETWORK

    Get PDF
    This paper presents the assessment of a number of factors affecting bus travel time and a relationship model between those factors and bus travel time. Statistica Neural Network (SNN) tool is used to solve this complex phenomenon. Data collected include bus travel time, distance, average speed, and number of bus stop. The results show that bus travel time is well predicted using variables of distance, average speed, and number of bus stops. The bus travel time increased due to the increase of distance and number of bus stops, while the higher the average speed from one stop to another, the lower bus travel time.Keywords: bus travel time prediction, distance, average speed of bus, number of bus sto
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