加强万隆 LMU Nurtanio 路交叉口--Abdul Rahman Saleh 十字路口的交通流量和安全性

An An Anisarida, Irvan Budi Wicaksono
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引用次数: 0

摘要

万隆是西爪哇省最大的大都市,也是该省的省会。车辆排队或交通拥堵的地点之一是公路与铁轨之间的平交道口,包括位于安迪尔的 LMU Nurtanio 街 - Abdul Rahman Saleh 街的直接交叉口 (JPL)。本研究的目的是评估现有路段的性能,使用 PTV VISSIM 程序进行模拟,并针对发现的问题寻找替代解决方案。在这项研究中,主要数据是通过直接实地测量获得的,包括车辆流量、排队长度和道路几何数据。此外,还从 PT Kereta Indonesian Fire 公司获得了通过该交叉口的火车数量的二手数据。本分析中使用的 PTV VISSIM 程序是学生许可程序,因此在分析中存在局限性和简化。通过对路段的性能计算,LMU Nurtanio 街的饱和度(Ds)值为 0.73,Abdul Rahman Saleh 街的饱和度(Ds)值为 0.77。根据政府规定的道路服务等级,这两条道路的服务等级均低于 C 级。PTV VISSIM 模型结果显示,LMU Nurtanio 街的排队长度为 66.59 米,Abdul Rahman Saleh 街的排队长度为 105.18 米。万隆研究使用 PTV VISSIM 评估了 LMU Nurtanio - Abdul Rahman Saleh 街道,揭示了拥堵问题。队列长度凸显了改善需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing Traffic Flow and Safety at LMU Nurtanio Road Crossings - Abdul Rahman Saleh Intersection in Bandung
Bandung is the largest metropolitan city in West Java Province and serves as its provincial capital. One of the locations where vehicle queues or traffic congestion occurs is at the level crossings between the highway and railway tracks, including the direct crossing (JPL) at Andir on LMU Nurtanio Street - Abdul Rahman Saleh Street. The purpose of this research is to assess the performance of the existing road section, simulate it using the PTV VISSIM program, and find alternative solutions to the identified problems. In this study, primary data was obtained through direct field measurements, including vehicle volume, queue length, and road geometry data. Additionally, secondary data on the number of trains passing through the crossing was obtained from PT Kereta Indonesian Fire. The PTV VISSIM program used in this analysis is a student-licensed program, which implies limitations and simplifications in the analysis. The performance calculation of the road section yielded a degree of saturation (Ds) value of 0.73 for LMU Nurtanio Street and 0.77 for Abdul Rahman Saleh Street. According to the road service levels set by the government, both roads fall below service level C. The PTV VISSIM modeling results indicated a queue length of 66.59 m for LMU Nurtanio Street and 105.18 m for Abdul Rahman Saleh Street. Bandung study uses PTV VISSIM to assess LMU Nurtanio - Abdul Rahman Saleh Streets, revealing congestion issues. Queue lengths highlight improvement needs.
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