Abstract
Congestion has become a problem of traffic on urban road segments in several major cities in Indonesia, it will have a negative impact on the driver or users of the road due to the longer travel time. Congestion resulting in economic and immaterial losses such as cause stress due to fatigue, and congestion in critical condition can result in excessive fuel consumption and air pollution are also higher. Before the congestion is in critical condition there must be performed Indicator, to be able to determine the handling step early, because handling the congestion problem will be more difficult to handle, if the congestion is already in critical condition. The congestion performance indicator is a derivative of a delay which delays the speed of the vehicle free-flow speed due to side barriers on the road. Free-flow speed is an important characteristic for capacity and level-of-service (LOS) analysis of urban road. The objective of this study is to develop models delay form magnitude of results analysis estimating free-flow speed. Many generic factors like weather, environment, vehicles, roadway characteristics, driver and traffic streams either singly or in combination influence the free flow speed. The quantitative measures of these factors are desirable for reliable free-flow speed measurement and system design. Characteristics of diverse urban roads and high side friction characteristics in major urban cities in Indonesia greatly determine the value of vehicle free current velocities, which will determine the parameter of delay values that occur where this can be a performance indicator approach in defining the performance of an urban road segment in Indonesia. This research was conducted in several road segments and part of an urban road segment in Mataram city, Provence of Nusa Tenggara Barat. Primary data traffic is done with video camera, with variation of time and road segment, in order to get variation of traffic characteristic and the variation side frictions characteristic at the same time. With the data will be analyzed relationship between variations characteristics above components with speed data in 5 minutes Time slice on the range of traffic data in under saturated condition. Free Flow speed (FV) vehicles will be analyzed from the relationship between Speed (V) and traffic flow (Q) as well as variations in side friction (SF) characteristics obtained at time slices at the same time. The result of analysis shows the influence of side friction characteristics that vary in magnitude such as: parking vehicles, vehicles in and out of the road segment, the number of pedestrians, and vehicles stopped. The number of motorcycles in the traffic flow also affects the value of free flow speed analysis. The results of free flow speed analysis above also contrast with the results of free flow speed analysis model IHCM 1997.
Concepts :
SDGs
Citations by Year
| Year | Count |
|---|---|
| 2019 | 3 |