Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007 THE IMPACT OF PUBLIC TRANSPORT ARRIVAL RATE AND STOP TIME IN MODELLING AND ANALYZING A SIGNALIZED INTERSECTION BY USING MICRO SUMULATION AND ANALYTICAL SOFTWARE Gusri YALDI Wen Long YUE Lecturer Senior Lecturer, Program Director Civil Engineering Department Transport Systems Centre Polytechnic of Andalas University University of South Australia Kampus Politeknik Unand North Terrace, Adelaide Limau Manis, Padang South Australia 25161 Indonesia SA 5001 Fax: +62-751-72576 Fax: +61-8-83021880 E-mail: [email protected] E-mail; [email protected] Elvi Roza SYOFYAN Lecturer Civil Engineering Department Polytechnic of Andalas University Kampus Politeknik Unand Limau Manis, Padang 25161 Indonesia Fax: +62-751-72576 E-mail: [email protected] Abstract: The application of micro simulation traffic modeling and analyzing software has been widely spread in many countries, including the developing countries. Before that, many developing countries have been used micro analytical software, for example aaSIDRA. It seems it is more difficult to use micro simulation software in developing countries due to there are more complex problems compared to developed countries, as the models were developed based on the travel behavior of the country. A study to model and analyze a signalized intersection has been undertaken in Padang, West Sumatra, Indonesia. It used CUBE Dynasim, a relatively new micro simulation software, and aaSIDRA. Throught the application of the two models, it has been found that CUBE Dynasim tends to generate lower approach flows compared to the real data while aaSIDRA generates higher lane capacity than the demand. Public transport arrival rate and stop time were reduced with by 10 percent incrementally in order to investigate this case. However, CUBE Dynasim still generates traffic flow which is below the real data. Key Words: Traffic flow, Public transport arrival rate, Public transport stop time 1. INTRODUCTION The majority of developing countries, including Indonesia, are likely having the same problems related to the urban transport systems. The travel demand increases as the urbanization rate increases which could reach as twice quicker as in the United States (Morichi, 2005). It is even higher compared to the countries in Europe. Due to the increases, it has caused difficulties in modeling and analyzing their transport systems in developing countries compared to in developed countries where the system has been well-established, Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007 particularly when the modeling and analysis is undertaken by using micro simulation instead of micro analytical traffic analysis software. Hence, the application of micro simulation traffic analysis and modeling software which have been successfully in developed countries could generate different results when used in developing countries. The use of microscopic traffic simulation plays major roles in the analysis and evaluation of transport systems. It is due to its ability to analyze a transport system based on each vehicle properties and operations. It can analyze the interaction between vehicles in the systems and between vehicles and the infrastructure as well. Therefore, microscopic traffic simulators can be considered as a suitable tool in analyzing various transport operations (Barcelo et al. 2003). It can reproduce a significant level of accuracy and capture the interactive impacts among transport elements in a system. Besides, it can generate outputs which show the variations of particular transport system parameters. For example, it can produce the average travel speed and its variations so that the profile of the speed within certain period of time can be evaluated. Hence, through a simulation analysis the practitioners are able to estimate the likely outcomes in the system after some alternative changes are applied. Therefore, the best scheme among the proposed planes can be selected accordingly (Gomes et al. 2003). However, the capability of a particular traffic simulator to accommodate traffic planners’/engineers’ needs in analyzing a transport system must be equipped with its ability to generate remarkable, accurate and precise outputs. More precisely, the software must have a tool that can be used to adjust the factors to calibrate the analysis based on local conditions. Dowling et al. (2004) explained that calibration process is important since the appropriate analysis parameters can be selected according to the local traffic operation conditions. Some of data which is required to be calibrated are, for examples, traffic volumes, average travel speeds, peak time factor, and acceptable gap. The main aim of this paper is to discuss the use of CUBE Dynasim and aaSIDRA in modeling and analyzing a signalized intersection located in the Central Business District (CBD) of Padang, West Sumatra-Indonesia. Further, it focuses on the impact of Public Transport (PT) arrival rate and stop time to the traffic flow. The comparisons regarding the results generated by both software are then compared in order to see the performance differences of the two software in analyzing and modeling a signalized intersection. CUBE Dynasim is an event- based software with stochastic and dynamics outputs. It has tools which can be used to model the real transport system including the application of Intelligent Transport System (ITS) facilities, for instance, actuated traffic signals. It is multimodal traffic simulator software and able to import file or data from CAD, GIS and other databases as well as other traffic analysis programs. This micro simulation software also has some tools to calibrate or adjust the traffic parameters based on the local traffic data. On the other hand, aaSIDRA is micro analytical traffic software and has been used in more than 80 countries, predominantly in the USA and Australia. It has the ability to analyze an intersection with up to 8 legs with options of two-way road, one-way approach or one-way exit. In addition, it can calibrate the analysis based on local conditions and compatible with the Highway Capacity Manual (HCM), for example the signal as well as the road conditions. Moreover, it can determine the optimum cycle time which is unable for micro simulation software to perform. aaSIDRA can count the impact of on-street parking and bus stopping on the system, however, it is only for on-street parking and bus stopping which is located on the approach lane. Therefore, this could be a weaknesses of aaSIDRA compared to CUBE Dynasim. Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007 This study will involve only one signalized intersection in Padang CBD, West Sumatra, as a test case. It is a-four leg intersection and controlled with pre-timed signal. It is an intersection between Sudirman St and Agus Salim St as shown in figure 1. There are only three approaches namely Sudirman St, Agus Salim St and Bagindo Aziz Chan St on the East, South and West approach respectively. The North approach, in this case Pasar St, is exit only and an one-way road. The data are collected by undertaking traffic surveys including traffic volumes and distributions, signal timings, bus headways and on-street parking. Then, a comparison has been made addressing the ability of each software in modeling the intersection as well as the output generated by the two software. The output comparisons will focus on the traffic flow with various of PT arrival rates and stop times. Some limitations are applied in the research. Those are, for example, the vulnerable road users, including non-motorized transport modes were ignored. The adjacent minor junctions were also ignored. The transport modes are categorized into three groups, namely Passenger Car (PC), Heavy Vehicle (HV) and Motorcycles (MC) based on the local code, in this case Manual Kapasitas Jalan Indonesia (MJKI). All motorcycles were converted into passenger car unit by multiplying them with 0.2 while PC-size public transports were converted into heavy vehicles by multiplying them with 1.3. The conversions were made based on the local code (MKJI) and were undertaken before entering the data into both software. Figure 1 Intersection layout 2. COMPARISON OF CUBE Dynasim AND aaSIDRA OUTPUTS The aim of micro simulation modeling and analysis is, for example, to evaluate the traffic movement during a definite period of time. The impact of every intervention such as public transport stopping, traffic signals and crossing pedestrians to the traffic flow can be investigated. Firstly, both UBE Dynasim and aaSIDRA models were developed. All required data used in both models are the same, including the traffic volume and distribution, intersection geometry and phase and signal timings. There are three bus stops in the model. One bus stop located on Bagindo Aziz Chan approach. There is also one bus stop on Bagindo Aziz Chan exit. Another one is on the Sudirman approach. There is no bus stop located on Agus Salim approach. The results of the modeling and analysis are discussed below. In CUBE Dynasim, the traffic flow is considered as instant flow. The instant flow for each lane from a certain origin and destination can be collected by setting up the data collector on the simulation objects. After running the model, the instant flow for each lane is generated by CUBE Dynasim. The proximity of the simulation outputs to the real data is determined by the Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2007 number of simulation undertaken in the analysis. In this study, 10 runs are adopted to form a statistical summary. CUBE Dynasim produces the simulation results in two kinds of statistical outputs which are tables and graphs. Figures 2 and 3 are the examples of graphs resulted from CUBE Dynasim. Those graphs portray the approach, exiting and lane flow at the observed intersection within one hour for each direction. Like other micro simulation traffic analysis software, CUBE Dynasim can generate the output as small as at one second interval.