com Abstract Comparing with the traditional traffic simulation software Arena can define a discrete random function and can make simplification of the operation by using customizable interface The discrete environment of modeling and simulation provi ID: 36352 Download Pdf

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com Abstract Comparing with the traditional traffic simulation software Arena can define a discrete random function and can make simplification of the operation by using customizable interface The discrete environment of modeling and simulation provi

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204 A Research on Micro Simulation of Signalized Intersection Based on Arena Qinjun Zhang,Huiyuan Jiang Wuhan University of Technology,Wuhan, China sc20050206@126.com Abstract —Comparing with the traditional traffic simulation software, Arena can define a discrete random function and can make simplification of the operation by using customizable interface. The discrete environment of modeling and simulation provi ded by Arena has obvious advantages during the research on the complex queuing system. In this paper, Arena is applied to resolve the problem of intersection. By

using Arena’s modeling and simulation method, this pa per analyzes the flow of signalized intersection, and studies the relationship between signal control system and each subsystem. Special modules of signalized intersection are built in the discrete environment of modeling and si mulation of Arena. It is concluded that these modules can be used expediently to study on simulation modeli ng, scheme adjustment and result analysis of a certain intersection. Index Terms Signalized Intersection, Micro Simulation, Arena I. NTRODUCTION With the rapid development of social economy, the traffic

problem has been paid more and more attention. As the throat of urban traffic, the capacity of urban Intersection has restricted urban development. Intersection is an extremely complicated system, which is controlled by multiple factors and big randomness. It is far from satisfying by building an exact mathematic model or preestablishing a control sche mes. In recent years, with the development of the computer technology, Traffic simulation had been one of the research highlights. As a system simulation software , the modeling environment of Arena is discrete. It is useful for studying

complicated queuing system. Compared with traditional simulation software (such as VISSIM), Arena has the following advantages: (1) Make simplification operating by using customizable interface ; (2) Arena can custom random distribution functions, which can be used to analyze some Intersections having special traffic flow. In this paper, it will try to take Arena to research the problem of Intersection.[1] II. NALYZE THE FACTORS OF INTERSECTION SYSTEM A. Determine the Boundary of the Target System Before starting to research the system, we must know the boundary of the target intersection

system, and find out factors which must be included in the system while others can be ignored. Make it as simple as possible, and make sure that the primary problem we study can be answered, and can reflect the real system. The main objective of signal control is to reduce delay as possible. If a vehicle arrives at the intersection, we will think it has arrived at the system; if a vehicle drives away from the intersection, we will think it has leaved the system. Then, we define the exit and the entr ance as the boundary of the system. In the successive research, we will adjust the boundary

because of the change of the research scope.[2][3] B. Process Analysis When a vehicle arrives at the entrance of the intersection, it will choose different lanes based on different destinations and the using condition of driveway. If the signal lamp turns red or yellow, then stop; If it is green, then look around to make sure if there is a vehicle ahead, IF Yes Then drive fo llow it, IF No Then drive away from the intersection. See Figure2-1. C. Object Aalysis In order to build the intersection model, abstract each real entity as an object.[4] The objects have the same features with the real

entity. By analyzing the flow of signalized intersection and all subsystem, and abstracting all kinds of the factors of th e real system, we can obtain ISBN 978-952-5726-10-7 Proceedings of the Third International Symposium on Co mputer Science and Computational Technology(ISCSCT ’10) Jiaozuo, P. R. China, 14-15,August 2010, pp. 204-207 © 2010 ACADEMY PUBLISHER AP-PROC-CS-10CN007 Fi ure2-1. Vehicle Process Anal sis

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205 the system objects: Vehicle Generator, Vehicle Controller, Lane Link, Signal Lamp, Signal Controller, Vehicle, Lane. D. Relation of Objects Analysis When the

object analysis ha s completed, we start to analyze the relation of these objects. See Figure2-2, the number is the information code transferred between objects, when we encode in Arena. Figure2-2. Relation of Objects E. Input and Output Parameters of the Model Considering the requirement of the system, as well as the data collected, we confirmed the under parameters as the input parameters. See Table2-1. TABLE2-1 INPUT PARAMETERS Type Input Parameters Vehicle Arrival Distribution Destination Lane Link Number of Entrances and Lane Signal Controller Signal Control Plans Number of Signal Lane

Top Speed, Capacity of Lane Length of Lane Considering the aim of the research, we confirmed the under parameters as the output parameters. See Table2-2. TABLE2-2 OUTPUT PARAMETERS Type Output Parameters Vehicle Max/Min/Mean Travel time Max/Min/ Mean Delay Parking Rate System Structure Max/Min/ Mean Queue Length Traffic Capacity Number of Vehicles In Lane III. XPLAINING OF MODULES IN ARENA A. Module of Vehicle Generator Module of Vehicle Generator is used to create vehicle and attach attribute, such as arrival time, type, destination and color. This module is the basic module of the simulation

model. The arrival time of vehicles is a random event, so the time interval between two adjacent vehicles (time headway) is also a ra ndom variable. When time headway accords with Poisson distributi on, we usual use negative exponential distribution to describe the time headway. The specific form is as follows: Traffic Flow Rate. B. Module of Vehicle Controller Module of Vehicle Controller is used to control the driving of the vehicle, and this module is the heart module of the simulation model. It decides the overall process of vehicle’s parking, freed driving and follow driving.[5][6]

Parking If the signal lamp turns red, yellow or there is a vehicle ahead, then stop. Free driving If the distance between a vehi cle and the front vehicle surpasses some dmax, we will consider the front vehicle do not impact on the following vehicle, and the vehicle drive away from the intersection as normal speed. Follow driving If the distance is less than dm ax, then the front vehicle will impact the speed of the follow vehicle. The following vehicle module is the most important dynamic model of a Traffic simulation model. This text uses the new line following model which is brought forward

by Hglly. It considers the influence of the speed of the two front vehicle. The model as follow: Xn Dn Dn Xn D(t) expected speed of following drive C1 Based on the survey of action of 14 drivers, when correlation coefficien t greater then 0.8, the numeric area of T is 0.5 2.2s, then C1 is 0.17 1.3. C2 To make the front and the following vehicle have the same acceleration by setting v and x. At last, we will obtain the final formula: 20 )) 125 Dn Dn C. Module of Lane This module is a carrier which connects the origin and destination. It is the important component of the simulation model. Its

function is offering the space for the vehicle. D. Module of Lane Link In order to guarantee that we can build the model in Arena, we design the module of lane link. Its function is making vehicle arrive at the right lane with different destination.

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206 E. Module of Signal Controller This module is used to describe dynamic entity which is related to the road. It can produce light signal and restrict the action of vehicle, which is driven by system clock. We transform Signal Control Plans to Phase Step Table at the progress of encoding this module in Arena. Consequently, when

input the parameter, we should also do this thing. Take four-phase (Dual Left Turn) for example, Its Phase Step Tabl e as follow, See Table3-1. IV. ASE ANALYSIS A. Basic Condition Collect the basic data of a intersection from Wuhan, its Hourly traffic volume as follow, look at Table 4-1, unit is pcu/h. S- moving straight, L-turn left, R-turn right. TABLE2-3 OURLY TRAFFIC VOLUME FLOW LANE FLOW LANE W S 545 2 N S 476 2 L 104 1 L 41 1 R 54 1 R 53 1 FLOW LANE FLOW LANE E S 564 2 S 558 2 L 177 1 L 54 1 R 109 1 R 51 1 B. Parameter Input Input of Arriving Function We can confirm the arriving function

by using the function of Input Analyzer in the Arena. After analyzing, we can obtain the parameter of arriving function: d =4.23 x=6.38 n=5.39 b=6.31. Input of Signal Control Plans There are two programs, one’s Cycle time is 60s, the other is 100s. See Table4-2. TABLE2-4 NPUT OF HASE TEP STEP 1 2 3 4 5 6 7 8 9 TIME 2 3 3 2 2 15 3 3 2 TIME 2 5 3 2 2 21 3 3 2 TABLE2-5 NPUT OF HASE TEP STEP 10 11 12 13 14 15 16 17 18 TIME 2 15 3 2 2 13 3 3 2 TIME 2 21 3 2 2 19 3 3 2 C. Simulation Result Analysis Working procedure after input parameter, by 10 times simulation, we can obtain the result as

Figure4-1. From TABLE2-1 PHASE STEP 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 1G 1Y 1R 1A 1PG 1PR 2G 2Y 2R 2A 2PG 2PR Time 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Phase means switched on, means blink, blank means turn off, unit of time is s. 1G green light of E-W 2G green light of N-S 1Y yellow light of E-W 2Y yellow light of N-S 1R red light of E-W 2R red light of N-S 1A green light of left turn of E-W 2A green light of left turn of N-S 1PG green light of pedestrian of E-W 2PG green light of pedestrian of N-S 1PR red light of pedestrian of E-W 2PR red light of pedestrian of N-S

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this figure, it is obvious that the programI is better than programII. 3,3,,3,3,, 0HDQ'HOD\V0HDQOHQJWKRI TXHXHP (DVW :HVW 6RXWK 1RUWK Figure4-1 Result Analysis V. ONCLUSION By using Arena’s modeling and simulation method, special modules of signalized intersection are built in the discrete environment of modeling and simulation of Arena. It is concluded that these modules can be used expediently to study on simulation modeling, scheme adjustment and result analysis of a certain intersection. However, there still might be some other aspects that we hope

to do more research on this topic. One thing is that the paper only takes one intersection into consideration, other than several adjacent in tersections on main traffic flow which could possibly have more complicated scenarios. That is also one of our research focuses in next step. EFERENCES [1] W.David Kelton, “Simulation With Arena,” M.The McGraw-Hill Companies, In USA,2002. [2] Zaibao Guan, “The Research of Algorithm and Model of Traffic Control at Signaled Intersection,” D.Chengdu, Sichuan Province,Southwest Jiaotong University,2007. [3] Huapu Lu, “Modern Management of urban

traffic,”China Communications Press, 1999. [4] JixiuHao, and ZhaoruiZheng,“T raffic Simulation Based on Object-Oriented Method,”J.Jour nal of Taiyuan University Of Technology,2004,35(4). [5] Yan Feng, Yulong Pei,and Chen ghai Cao, “Application of VISSIM in the Public Transportation Priority Signal Timing,” Journal of HARBN in stitute of Technology,2007. [6] Jianhe sha, “A Microscopic Traffic Simulation System Based on MAS Theory, D.Shandong University, Jinan,Shandong Province,2007.

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