The aim of this paper is to point out that the same basic ideas that have appeared useful for data network systems could also be useful in solving  street traffic control problems

Butrimenko, A.

Strobel, H.

International Institute for Applied Systems Analysis (IIASA)

How to Make City Traffic Adaptive on an Algorithm for the Adaptive Automatic Control of the Main Vehicular Traffic Streams in an Urban AreaButrimenko, A. and Strobel, H.IIASA Working PaperWP-74-0141974 Butrimenko, A. and Strobel, H. (1974) How to Make City Traffic Adaptive on an Algorithm for the Adaptive Automatic Control of the Main Vehicular Traffic Streams in an Urban Area. IIASA Working Paper. WP-74-014 Copyright © 1974 by the author(s). http://pure.iiasa.ac.at/157/ Working Papers on work of the International Institute for Applied Systems Analysis receive only limited review. Views or opinions expressed herein do not necessarily represent those of the Institute, its National Member Organizations, or other organizations supporting the work. All rights reserved. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage. All copies must bear this notice and the full citation on the first page. For other purposes, to republish, to post on servers or to redistribute to lists, permission must be sought by contacting repository@iiasa.ac.at HOW TO MAKE CITY TRAFFIC ADAPTIVEON AN ALGORITHM FOR THE ADAPTIVE AUTOMATICCONTROL OF THE MAIN VEHICULAR TRAFFIC STREAMSIN AN URBAN AREAA. Butrimenko and H. StrobelJune 1974Working Papers are not intended fordistribution outside of IIASA, andare solely for discussion and infor-mation purposes. The views expressedare those of the author, and do notnecessarily reflect those of IIASA.WP-74-14How to make City ?raffic AdaptiveOn An Algorithm for the Adaptive Automatic Contrnlof the Main Vehicular Traffic Streamsin an Urban AreabyA. Butrimenko and H. Strobel1. MotivationWe will consider a situation as shown in Fig. 1*: a cararrives ln an urban district, e.g. at the Swain Squareintersection. The driver of the car wishes to £0, forexample, to the Koopmans Place intersection (his destinationpoint). The driver wants to know which route will requirethe ｭ ｩ ｮ ｩ ｭ ｵ ｾ of driving time, taking into account thedifferent traffic densities in the different streets.We are going to give him advice by means of a special kindof road sign which will be placed at a certain distancebefore each of the possible intersections. These roadsigns, which show the driver the recommended route, wouldbe the same as those that are used today to point alIt therecommended direction and the only difference would be thatthese proposed road signs would have to be changeable andcontrolled by an electronic system. The control device(e.g. a decentralized installed mini-computer or even acentral control computer) has to advise the driver of anycar arriving at the Swain Square intersection on the bestroute to take, i.e. the driver chooses his route through theintersections (see Fig. 1) from the road signs shown inRaiffa Street.* The map in Fig. 1 is completely fictional and anyresemblance to a town 6r names in existence" ispurely coincidental..... -'-LIt may be of interest to point out that this problem isvery similar to a traffic control problem arising in datanetworks [IJ. There fore, the aim 0 f this pape r is to pointout that the same basic ideas, which have appeared useful fordata network systems, could also be useful in Sf)l ｶ ｩ ｮ ［ ｾ thedescribed street traffic control problem.2. Basic Idea of the Algori.thmWe now describe, without ｧ ｯ ｩ ｮ ｾ into detail, ｴ ｨ ｾ basicidea of the proposed algorithm. We illustrate it by means ofFig. 1.The advice to the driver will be given, as mentionedabove, by means of changing road signs. 'rhe mai.n contl'olinformation for the updating of these signs will be 3tored incertain matrices. The number of matrices ｣ ｯ ｲ ｲ ･ ｳ ｰ ｯ ｮ ､ ｩ ｮ ｾ to·one particular intersection is equal to the number of streetsleading to this intersection and to the number of r03d ｳ ｩ ｾ ｮtables. For example, the number of matrices for the SWRinSquare intersection is equal to four Ｈ ｡ ｳ ｳ ｵ ｾ ｩ ｮ ｧ that ｾ ｡ ｣ ｨ ofthese streets has traffic in the direction of the intersecti0n).Each of these matrices has the number of rows equal to thenumber of selected destination points. In our example thereare eight of them: IIASA Place, Koopmans Place, Bell Terminal,Rosanov Circus, Ma.yerhofer Airport, Thompson Place, ｾ ﾷ Ｑ ｡ ｮ ｮ ･Square and Swain ｓ ｱ ｵ ｡ ｲ ･ ｾ Ｏ Ｎ 'l'he number of columns if:' 0(1118.1to the number of possible ､ ｲ ｩ ｶ ｩ ｮ ｾ directions from this street.*/ The choice of the destination points depends on many factorsand should not correspond to the number of destination nodesput on the ｣ ｯ ｲ ｲ ･ ｳ ｰ ｯ ｮ ､ ｩ ｮ ｾ road signs. The destination pointsput on the road signs could be different for differentintersections--for example if the direction is not chanred--but all these problems will have to be investip;ated in moredetail. There is also another way to avoid the bewilderin8forest of traffic signs. "Before beginninr: his journeyevery driver keys a destination identification code ｩ ｾ ｾ ｩ ｳvehicle. On the basis of these destination requests" [2:the control device at each intersection sends him, by "mean:;of a special wireless system, in the recommended directionWhich is di3played on the driver panel of hi.s CHr Ｈ ｐ ｩ ｾ Ｎ 4).For example, from Raiffa Street leading to the Swain Squareintersection, we have three possible ､ ｲ ｩ ｶ ｩ ｮ ｾ directions andthree columns of the matrix. The structure of the matrix,with respect to Raiffa Street, is shown in Fig. 2.The elements of the matrix have to renresent the estinatedminimum driving time from the next intersection to thedestination point, assuminp;that the followinr': ｳ ｴ ｙ Ｇ ･ ･ ｴ ｾ Ｓ arechosen in an optimal manner. The separate row, Ｐ ｨ ｯ ｾ ｾ underthe matrix contains the travelling times needed to reach thecorrespondinr; intersection. For Ｈ ｾ ｸ ｡ ｭ ｰ ｬ ･ ,in the rC11 forKoopmans Place the travelling time needed to reach thisdestination point from the road sign in Letov Street equals21; from the road sign in Haefele Avenue - ｬｾ［ fromDantzig Way - 12.To reach the corresponding road siens, from the roadsigns in Raiffa Street, we need 10, 21 and 6 minutesrespectively. These last figures include the time forcrossing the Swain Square intersection Ｈ ｩ ｮ ｣ ｬ ｵ ､ ｩ ｮ ｾ waitingtime) plus driving time through the following streets, i.e.Letov Street, Haefele Avenue and ｄ ｡ ｮ ｴ ｾ ｩ ｧ Way. On thebasis of the information stored in the matrix, we can fixthe road signs. For example, to reach Koopmans Placethrough Letov Street we need 21 + 10 = 31 minutes; throughHaefele Avenue 14 + 21 = 35 minutes; and through DantzigWay 12 + 6 = 18 minutes. Thus, we have to recommendturning right into Dantzig Way from Raiffa Street.The problem is that we cannot keep the road ｳ ｩ ｧ ｾ ｳ fixedbecause of the stochastic nature of the traffic. We haveto update the matrices taking into consideration the rea]traffic situation. The way to this is as follows. Wecalculate continuously the time*needed from the intersectionat Swain Square which consists of waiting time in thecorresponding queues and driving time through the intersectionand following streets. For example, to drive from theintersection in the direction of Haefele Avenue and through• This should he done by means of a special alp;orithm forreal time estimation of the ｴ ｲ ｡ ｶ ･ ｬ ｬ ｩ ｮ ｾ times.-4-this avenue to the np.xt road sign before IIASA Place, we need21 minutes. This time depends on traffic density in HaefeleAvenue and waiting time before Swain Square. Both of thesetimes have to be measured.We carry out this calculation for each intersection ofeach street (matrix). We will store this information in aspecial row for which the number of elements is equal to thenumber of possible driving directions. For example, forRaiffa Street we have 10, 21, 6. Given the information onestimated travelling time from IIASA Place to Koopmans Place.we can calculate the estimated time to reach Koopmans Placefrom Swain Square through Haefele Avenue as a sum of themeasured travelling time from the road sign in Raiffa Streetto the road sign in Haefele Avenue before IIASA Place andthe estimated time from this point to Koopmans Place.We repeat this calculation for each destination pointand for each possible direction. Then we will take theminimum for each destination point out of the possibledirections and store it as a special vector, each elementof it giving the minimal time to reach each destinationpoint from the intersection for which this calculation hasbeen carried out. For example, for the matrix in RaiffaStreet we have the following (Fig. 3) vector of minimumdestination times. This vector will be sent to allneighbouring intersections with streets leading to thisparticular road sign table in Raiffa Street; in this caseto the devices connected to the road signs in Bykov andHolling Streets. This vector will be stored as a columncorresponding to the direction of Swain Square in the matricesin Holling and Bykov Streets. In turn this would also meanthat information stored in the matrix in Raiffa Street, asshown in Fig. 2, has been sent from devices in Letov Street,Haefele Avenue and Dantzig Way, respectively.-5-The important point is that each matrix correspondingto the intersection, which is itself a destination point,contains a row ｣ ｯ ｮ ｳ ｩ ｳ ｴ ｩ ｮ ｾ of constant zeroes,and the name ofthis row is the destination point. For example, in thematrix in Raiffa Street we have the row ｣ ｯ ｲ ｲ ･ ｳ ｰ ｯ ｮ ､ ｩ ｮ ｾ tothe destination point Swain Square which contains constantelements equal to zero. By ｵｰ､｡ｴｩｮｾ continuously thematrices and ｲ ･ ｡ ｲ ｲ ｡ ｮ ｧ ｩ ｮ ｾ the road signs, we will supplythe drivers with information on the shortest time routes.We have already formulated this algorithn and are goinR,to carry out the following investigations in the near future.3. Some Proposals for Detailed InvestigationsDevelopment of an algorithm for real time estimationof travelling times;Simulation of the street network system on a dir,italcomputer with different traffic densities;Comparison of the sUb-optimal (decentralized) algorithmmentioned above with other algorithms;Answering the question of whether it is possible todetermine the real optimal solution, e.g. by a centralcomputer in real time;Different optimizing criteria;Controlled changes of the lane directions in the street,as additional control parameters to the proposed system.Consideration of synergistic operation of liGhts(green waves);Take into account prediction of congestions by the changingof road signs.References1 Butrimenko, A., "Adaptive Routinr: Technique andSimulation of Communication Networks."IV lTC, Munich, 1970.2 Von Tomkewitsch, Romuald, "Traffic Automation -its Possibilities and Limits. Observations by aCommunications Engineer." 1st IFACIIFIP Symposiumon "Traffic Control and Transportation Systems",Versailles, 1-5 June 1970.1 ..".."" /AIRPORT ｾ Ｎｾ';..f ｾＮ; .-. jTIIO-,/PSONPLACE,b" ｾ,'.'A."/N':S""APOｾ Ｍ Ｂ .".,-_---....l''\ｾD.4:'Tl Ie .AYｾ Ｓ ｹ ･ ｲ ｮ ｯ ｲ ･ ｲ ａ ｩ ｲ ｰ Ｚ ｾ Ｚi ＧＺＧＺｬｏｲＺＧＮｾＩＳ［ＩＮＱ ｾＺｾＺＺＮＺ I ｾ\ !·:3n:l!:' ＿ ﾷ ｾ ｬ ｐ Ａ Ｂ Ｂ ｾ II -1"ｾ'"'"'Ｚｾ\ ..,.• • ｾｬＮＮＮ/1";\-\7:/JROZA/lOrCIRCUSLETOV STREETKOOP/·/A,'SPLAceUll':I '-':lHE:r'Ｍ ［ ［ ［ ｾ 1l !IHSA ?13ce:..-------------------- I r fl _ Pte.oef-., ｾＮ ｋｯｯｲｲＮＮｊＮｮｾ . :1l _ｾ I n.l1 ｔ ･ ｾ ｾ ｬ ｾ ｭ ｬ' " :-IlASA-.-'" PLACE］ ｾ ］ ｾFIG. 1-. A ｎ･ｴｷｯｲＱｴ｣ｯｮｳｩｂ､ｮｾｦｯｲ the-main streets and'intersectionsof an assumed city -( "IIASA TOWN")FIG. 2Matrix of Travelling Timesfor RAIFFA STREET at SWAIN SQUAREFIG. 3Vector of MinimumTravelling TimesFIG. 4(.-:0.."'-:1lI('6262324'-------+----- .,._- -! 21 ｲ Ｍ ｾ ｉ_______ ' I; 18 -r----;;-j, I I 'Ｌｾ \'- _, ". __ II ._.-.!OI !, '---t---- i10 I .,'1'----1----. --1,-- _. ""-I:]2120341721 3ｾＧＩ 30)'-50 ｾ ｪ 430 10'\ｾ \ ｩｾ ":/.....I(1) r-f;:$ (1)ｾ c :::-(1) (1) ;>;, cO(1) :::- cO HH ｾ 3= 8 (1) Cｾ E 0C/) (1) be E'rl ....-j·rlr-f ·rl ;:$8 ｲ ｯ ｾ:::- (1) N E S 00 ｾ ｾ'rl bO 'rl (1)ｾ (1) c c C ｾｈ(1) ro ro·rl 'rl o.·rl....4 ::r:: 0 ｾｲＭｬ 00Rosanov CircusMayerhofer AirportBell Terminal:·ianne Square'='hompson rlaceI' -L'- ａ Ｍ ｔ ｆ ｾ Ｚ Ｚ ａ .- "r. -" ｾ Ｍ Ｍ ｾ ＭI 1.,\ 1· r' ::. 1 ::. ｾ .. ｾＮ ｾL _ 10 I I. ..L.-- ,, .,. _ .... ----'

How to Make City Traffic Adaptive on an Algorithm for the Adaptive Automatic Control of the Main Vehicular Traffic Streams in an Urban Area

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