hardware-in-the-loop simulation system for multi-intersection traffic signal control

JOlUnal of Highway and Transportation Research and Development Vol.8.No.1(2014)067

Hardware-in-the-Ioop Simulation System for Multi-intersection

Traffic Signal Control

REN Yi-long(1f�::tr:)', YU Gui-zhen(�:!lt�)', WANG Yun-peng(::E�JlIl�)',

LI BinC$',ijI;;)2 , WU Jin-wu(:!R'j!fJEl;;)3

(1. School of Transportation. Science and Eng ineering Beihang University, Beijing 100191 , China;

2. Research Institute of Highway, Ministry of Transport, Beijing 100088, China;

3. Shenzhen Electronic Travel Net Traffic Technology Co. ,Ltd., Shenzhen Guangdong 518040, China)

Abstract; To evaluate the performance of a traffic signal control system quickly and efficiently, a hardware-in-the-Ioop simula

tion system of multi-intersection traffic signal is developed. With the hardware-in-the-Ioop approach, a simulation model based

on the microscopic traffic simulation software is established, and the real-time communication between the simulation software

and the traffic signal controllers is achieved, altogether providing a realistic traffic control simulation environment to evaluate the

performance of a multi-intersection traffic signal control system. A case study of Zhongguancun East Road along with the corre

sponding simulation results demonstrates that the hardware-in-the-Ioop system can evaluate not only the performance of various

signal controllers, but also the performance of the traffic signal control system for multi-intersections quickly and efficiently.

Key words; traffic engineering; signal control; hardware-in-the-Ioop; simulation-based evaluation; multi-intersections

1 Introduction

Signalized intersection is one of the main factors that

cause traffic congestions. Traffic signal control has prov

en to be an effective way to eliminate vehicle delay and

Increase vehicle throughput at intersections. Thus far,

many research works have been conducted to optimize the

traffic signal control at intersections. On the basis of the

approaches reported in these works, these works can be

divided into three main categories: The first one includes

the works that use macroscopic simulation models, such

as TRANSYT, to conduct the optimization. The second

one includes works that use professional microscopic sim

ulation software to model and optimally control the traffic

network. The last one includes works that use a practical

trial-and-error method for modifying signal timings in the

field on the basis of observations[l].

The use of macroscopic or mICroscopIC simulation

software to conduct evaluation plays an important role in

developing and analyzing new control methods. Howev

er, because of the competitive market for traffic signal

Manuscript received September 28, 2013

controllers, each vendor uses different procedures and

parameters for configuring its traffic control equipment.

Consequently, it is very difficult and impractical to eval

uate various signal controllers using simulation soft

ware[2]. Further, a newly developed optimization method

is seldom implemented at intersections directly because

such procedures are much less effective and even a tiny

mistake has the potential of causing congestions and

breaking down the traffic system severely.

To address these issues, a hardware-in-the-Ioop

simulation platfonn is proposed III this paper to coordi

nate the microscopic simulation software and the on-site

signal controllers to quickly and efficiently evaluate the

perfonnance of various signal controllers.

Thus, from our investigations, we found that only a

limited number of similar studies on this topic have been

reported in the literature. In 1995, the idea of hardware

in-the-loop was first applied to traffic simulation by UR

BANIK and VENGLAR [3J• In 2000, BULLOCK intro

duced the procedure to establish a hardware-in-the-Ioop

platfonn using a single traffic signal controller and micro-

� Supported by the National Natural Science Foundation of China ( No. 51278021) ; and National high-tech R&D Program of China

( 863 Pwgmm) ( No. 2011AAl10306) * * E-mail address;[email protected]

J. Highway Transp. Res. Dev. (English Ed.) 2014.8:67-72.

Dow

nloa

ded

from

asc

elib

rary

.org

by

UN

IVE

RSI

TY

OF

NE

W M

EX

ICO

on

11/2

9/14

. Cop

yrig

ht A

SCE

. For

per

sona

l use

onl

y; a

ll ri

ghts

res

erve

d.

68 Journal of Highway and Transportation Research and Development

scopic simulation software and the penonnances of two

mainstream traffic control systems, namely SCOOT and

SCATS, were evaluated using this procedure[4]. In

2001, ENGELBRECHT introduced the concept of the

hardware-in-the-loop structure and demonstrated that this

structure could be used for evaluating the penormance of

a signal controlierC5]. In 2004, ISERMANN et al. sum

marized the basic technology needed for the hardware-in

the-loop simulation platfonn and constructed a platform

using CORSIM[ll. In 2007 , YUN applied the hardware

in-the-loop idea to the EPAC300 induction traffic control

ler and tested the self-adaptive control optimization meth-

00[6], HUNTER et al. evaluated the penonnance of a

self-adaptive signal control system by using the hardware

in-the-Ioop platfonn[71.

A domestic study of hardware-in-the-Ioop simulation

system began in 2003. WANG et al. developed a hard

ware-in-the-loop simulation platfonn to evaluate the per

formance of a safety space keeping system, in which con

trollers, actuators, and control algorithms were tested [& 1 .

However, the hardware-in-the-Ioop structure was not ap

plied to the traffic signal control system until 2009 , when

YU proposed the scheme of the traffic control hardware

in-the-Ioop real-time simulation platform[91.

It can be concluded that little research on hardware

in-the-Ioop systems has been conducted in the field of

traffic signal control, not to mention the traffic signal

control for multi-intersections. Furthennore, most of the

existing works focus on dealing with some specific types

of controllers, while the compatibility with various signal

controllers has been widely ignored. In this paper, we

present a method to set up a hardware-in-the-Ioop simu

lation system for multi-intersection traffic signal controL

The proposed method can deal with different types of

controllers and provide a real-time hardware-in-the-Ioop

simulation system to evaluate traffic control strategies.

2 Hardware-in-the-loop simulation system

2.1 System architecture

A hardware-in-the-Ioop simulation system is de

signed and the perfonnance of the traffic signal control

system for multi-intersections can be evaluated by estab

lishing real-time communication between the simulation

software and the traffic signal controllers.

The architecture of the hardware-in-the-loop simula

tion system is shown in figure 1. The system consists of

four parts: the microscopic traffic simulation software,

manager module for traffic information collection and sig

nal setting, communication module, and traffic signal

controllers.

The microscopic simulation software is responsible

for traffic simulation and the perfonnance evaluation of

the traffic controllers. In a hardware-in-the-Ioop simula

tion system, the software does not provide any control

logic. By modeling the urban traffic network, the simula

tion software receives the control strategy and outputs the

simulation result.

The manager module for traffic infonnation collec

tion and signal setting is a dynamic link library (DLL).

Its main function is to collect the related traffic informa

tion and to set the signal phase.

The communication module is the core part of the

simulation system, which connects the simulation soft

ware and an external traffic controller, and allows the

controller to be directly involved in the internal signal

control of the simulation software. The module is mainly

responsible for the real-time connection between the traffic

controller and the simulation software. The traffic infonna

tion is sent to the controller, and then, the commands for

phase indications are sent back from the controller.

The traffic signal controller is responsible for the

control logic. The signal phase and the timing scheme of

the simulation network are controlled by the traffic con-

'"

indications

Controller Detector infonnation

Detector Phase infonnation indications

Communication V module

Fig. 1 Architecture of the hardware-in-the-loop

simulation system


Dow

nloa

ded

from

asc

elib

rary

.org

by

UN

IVE

RSI

TY

OF

NE

W M

EX

ICO

on

11/2

9/14

. Cop

yrig

ht A

SCE

. For

per

sona

l use

onl

y; a

ll ri

ghts

res

erve

d.

REN Yi-long, et a!: Hardware-in-the-Loop Simulation System for Multi - intersection Traffic Signa! Control 69

Lroller connecled Lo Lhe compuLer. Further, Lhe conLroller

receives the traffic information from the simulated road

network through the communication module.

2. 2 Control performance evaluation

The workflow of the multi -intersection traffic signal

control hardware-in-the-loop simulation system is as fol

lows: First, an actual road network is modeled by the

microscopic simulation software on the basis of the real

road network. By programming the manager module and

the communication module, we can build the simulation

system. Then, the manager module collects the required

traffic information and sets the signal, and finally, the

communication module transfers these data and com

mands in real-time. Altogether, these four parts comprise

the simulation platform. In the process of traffic simula

tion, the traffic information is collected and sent to the

external controller through the communication module.

The traffic controller receives the traffic information and

outputs the phase indications according to the control al

gorithm of the controller. The phase indications are then

sent to the signal setting module and applied to the simu

lation road network. Finally, the experimental data are

gathered by the simulation software. The analysis of the

cxpcrimcntal data complctcs the evaluation of the traffic

signal control performance.

To comprchcnsively cvaluatc thc control pcrform

ance of traffic signal control system, three evaluation in

dicators are chosen to reflect the overall characteristics of

the road network: the average delay of vehicles T", the

average queue length (} v, and the average travel time Tp.

( 1) Average delay of vehicles T"

We assume that the delay for each vehicle is T; ( i =

1 ,2,3 , ... ,S ) . The inactive vehicle number and the total

vehicle number are sand n, respectively. The total vehi

cle delay is T,um' Therefore, we can formulate Ta as fol

lows:

T = u n

( 2) A vcragc qucuc length Q v

The queue length of the intersection includes the

maximum qucuc length Om and the average queue length

o v' The average queue length Q v' which is the average

value of the maximum queue length of each lane of an

entrance link, is chosen as an indicator.

(3) Average Lravel Lime Tp The average travel time is equal to the mean time for

different vehieles passing through a road network.

3 Simulation analysis

To prove that the hardware-in-the-loop simulation

system of multi -intersection traffic signal control is practi

cal and the evaluation of the pelformance is accurate, the

simulation road network of Zhongguancun East Road,

Haidian District, Beijing, is set up using the professional

microscopic traffic simulation software Q-Paramics. By

programming the dll files, we can build the simulation

system. After the simulation experiment, the simulation

results are evaluated and analyzed.

3.1 System construction

The Zhongguancun East Road, Haidian District,

Beijing, is selected as the study object. As shown in fig

ure 2, this road has four main intersections, namely the

Lenovo Bridge and Zhongguancun East Road intersection

(intersection 1 ), the Zhichun Road and Zhongguancun

East Road intersection ( intersection 2), the North

Fourth Ring Road and Zhongguancun East Road intersec

tion (intersection 3 ) , and the Chengfu Road and Zhong

guancun East Road intcrscction (intcrscction 4) .

Fig. 2 Zhongguancun East Road

The reasons for choosing Zhongguancun East Road

are its adequate length, relatively large traffic flow, con

tinuous intersections of the road, and simple but com

plete traffic scenarios. Figure 3 shows the network of

Zhongguancun East Road using the simulation software

Q-Paramics. Thc link length of thc intcrscction is bc

tween 758 m and 1 062 m. Most of the links have 3 - 4


Dow

nloa

ded

from

asc

elib

rary

.org

by

UN

IVE

RSI

TY

OF

NE

W M

EX

ICO

on

11/2

9/14

. Cop

yrig

ht A

SCE

. For

per

sona

l use

onl

y; a

ll ri

ghts

res

erve

d.


lanes, and this number changes to 5 - 6 at intersections.

Fig.3 Road network of Zhongguancun East Road

With its plug-in structure and application program

interfaces (APIs) , Q-Paramics offers an extensible solu

tion to meet diverse requirements as more plug-ins can be

easily written through the APIs to expand the function of

Q-Paramics[ IOJ •

The manager module for traffic information collec

tion and signal setting and the communication module are

programmed using the API function. The submodule for

traffic information collection is used for collecting the

traffic information of the intersection when the simulation

is running. The submodule for signal setting is used for

receiving the phase indication from the controllers and

setting the signal phase in the simulation network.

The communication should be real-time and ensure

that the information transmitted by the module is correct

and complete. To meet these requirements, the commu

nication module is developed on the basis of the TCP lIP

network communication protocol. The communication

mechanism [11 J is shown in figure 4.

I I Information � Information

Q-Paramics" .. TCP/IP. .. Controller

Fig. 4 Communication mechanism

The communication module is based on the Client!

Server model. The server is the microscopic traffic simula

tion software, and the client is the controller. Each con

troller corresponds to an intersection. In this model, the

server listens for the request. The service process remains

in a dormant state until a controller asks the software to

connect with it; then, the service program "wakes up"

and provides services to the signal controller.

To ensure that the data can be accurately transmit

ted, the hardware-in-the-loop simulation system uses a

connection-oriented data transmission model. In this

mode, communication parties must comply with the same

communication rule. Both the client and the server have

to establish a connection before transmitting any informa

tion. When the data transmission is completed, the con

nection is closed and the resources occupied by the sock

et are released.

3.2 Simulation results and analysis

On the basis of the multi-intersection hardware-in

the-loop simulation system, three types of control strate

gies, i. e. , fixed signal timing strategy[12J , fully actuated

signal control strategy, and arterial coordinated control

strategy, are tested. After the simulation, the simulation

results have been evaluated and analyzed.

The average delay of vehicles T" the average queue

length Q" and the average travel time Tp are selected as

the evaluation indicators. Note that the queue length Q, has

the unit of Passenger Car Units (PCUs) in Q_Paramics[13J•

Table 1 shows the simulation results with three different

types of control strategies under various traffic flow rates. Tab. 1 Simulation results of dilTerent signal control methods

Traffic flow 300 400 500 600 700 800 900

Vehicle delay ( s) Fixed signal

Queue length(PCU) timing

Travel time( s)

9.828 11.791 16.338 26.276 32.437 37.092 42.269

1. 53 1. 955 2.663 3.264 3.813 4.695 5.271

415 410 455 603 706 850 1 038

Vehicle delay ( s) Fully actuated

Queue length(PCU) signal control

Travel time( s)

3.984 5.447 7. 066 9.665 13.026 40.241 45.069 0.589 0.869 1. 269 1. 713 2.229 6.002 6.429

303 322 348 430 527 993 1 159

Arterial coordinated Vehicle delay ( s) 9.029 10.923 14.302 23.502 29.856 32.765 36.179

control Queue length(PCU) 1. 399 1. 949 3.004 3.235 3.744 4.256 4.466

Travel time( s) 287 297 346 561 647 823 880


Dow

nloa

ded

from

asc

elib

rary

.org

by

UN

IVE

RSI

TY

OF

NE

W M

EX

ICO

on

11/2

9/14

. Cop

yrig

ht A

SCE

. For

per

sona

l use

onl

y; a

ll ri

ghts

res

erve

d.

REN Yi-Iong, et al;Hardware-in-the-Loop Simulation System for Multi -intersection Traffic Signal Control 71

Figure 5 shows a comparison of the average delay

per vehicle for different traffic flow rates. Compared with

other control strategies, the fully actuated signal control

strategy is flexible to adjust the phase sequence and the

green duration, and responds promptly to flow changes

under the condition of low traffic flow rates. Consequent

ly, the fully actuated signal control strategy performs best

when the traffic flow rates is low. Figure 6 shows the

comparison of the travel time with different control strate

gies. See from figure 6, the travel time of arterial coordi

nated control strategy is shorter than the travel time of

fixed signal timing strategy, but the average vehicle delay

and queue length of the arterial coordinated control strat

egy are almost same with that of the fixed signal timing

strategy. So the arterial control strategy has better control

perfonnance than the fixed signal timing strategy. The ar

terial road gets a non-stop traffic capacity at the expense

of the traffic capacity of other directions by using the ar

terial road coordinate control. When traffic flow rate is

low, the advantage of the arterial road coordinate control

is not obvious, due to the disadvantage of other direc

tions, the control perfonnance of the arterial road coordi

nate control is almost same with the fixed signal timing,

only has shorter travel time in arterial.

60

50

40 -'" " 30 -" "

20 -

10

.. Fixed signal timing --11-- Fully actuated signal control ---At-- Arterial coordinated signal control �

/?-+ J> /" ? __ LII_/lIV

///-lIV�oJt"- �/ .. A---k--- ¥

300 400 500 600 1'00 800 900 1 000 Traffic flow (veh/h)

Fig. 5 Comparison of average delay per vehicle As the traffic flow rate increases, the traffic flow of

the artery is also increased. Now, the advantage of the

arterial coordinated control becomes obvious. The three

evaluation indicators of arterial coordinated control strate

gy have the slowest growth rate. The growth rate of the

fixed signal timing indicators is in the middle. The indi

cators of the fully actuated signal control have the fastest

growth rate. That's because as the traffic flow rate increa-

ses, the actuated signal control has more green extension

for each phase and this control strategy gradually loses

the advantage of flexible phase changing. As shown in

figure 7, with an increase in the traffic flow rate, the av

erage queue length of the fully actuated signal control in

creases significantly and the disadvantage is increasingly

prominent. The perfonnance gap between the fully actua

ted signal control and other controls also widens.

1400 � ----+ - Fixed signal liming ] 200 - .. Full} actuated sIgnal .A...----�

control �/ / ,3 4r 1-1.rtt'l Ja coor matec �

1000>- , 1 drJP � .EJ 800' sIgnal control A;1 -----" S 600_ �/1 t=: _� L / 100 L +----------+-- _ ......

t=��-200 f-

o�' __ �� __ � __ L-� __ � __ �_ 300 '100 500 600 700 800 900 1 000

Tramc flO\v (veh .. l1)

Fig. 6 Comparison of average travel time

----+---- Fixed signal timing 7 -- ----II- Fully actuated signal /4 6 - control r-----.tr"

� ... Alterial coordinated / • __ ---+ :i : -_ signal control �-f�:�-----'" � 3- fi�j g 2 -- ",,/

___ ,,/

--k- __ k..----,j("-

o 'c-c�cc-�c_c��ccc�ccc�cc_�� 300 400 500 600 1'00 800 900 1 000 Traffic flow (vehlh)

Fig. 7 Comparison of average queue lengths The simulation results show that the fully actuated

signal control can make full use of its advantage and has

the best control perfonnance when the traffic flow rate is

low and the control parameter is appropriate. When the

traffic flow rate is high, particularly when the artery has

a relatively high traffic flow rate, the arterial coordinated

signal control has the best control perfonnance. The ideal

control method is the fully actuated signal control if the

traffic flow rate is low and the arterial coordinated signal

control if the traffic flow rate is high.

4 Conclusions

The multi-intersection traffic signal control hard

ware-in-the-Ioop simulation system can be used for evalu

ating the control performance of the entire road network.


Dow

nloa

ded

from

asc

elib

rary

.org

by

UN

IVE

RSI

TY

OF

NE

W M

EX

ICO

on

11/2

9/14

. Cop

yrig

ht A

SCE

. For

per

sona

l use

onl

y; a

ll ri

ghts

res

erve

d.


The simulation results demonstrate that the hardware-in

the-loop system can not only evaluate the performances of

different signal controllers but also support multi-inter

sections, and that it can quickly and efficiently evaluate

the performance of multi-intersections and finally the per

formance of a regional control system.

References

[ 1 J

[2J

[3J

[4J

[5J

[6J

ISERMANN R, SCHAFFNIT J, SINSEL S. Ha,dwa,e-in

the-loop Simulation for the Design and Testing of Engine

Control Systems [ J ] . Control Engineering Practice,

1999, 7 (5) , 643 -653.

BULWCK D, JOHNSON B, WELLS R B, et al. Ha,d

ware-in-the-loop Simulation [JJ. Transportation Research

Part C: Emerging Technologies, 2004, 12: 73 -89.

URBANIK T, VENGLAR S. Advanced Technology Appli

cation: The " SMART" Diamond [RJ. Compendium of

Technical Papers, Institute of Transportation Engineers

65th Annual Meeting. Denver, CO: Institute of Transpor

tation Engineers, 1995.

BULLOCK D, URBANIK T. Hardware-in-the-Ioop Evalu

ation of Traffic Signal Systems [C J II Proceedings of the

2000 IEEE Conference on Road Transport Information and

ContcoI. London, IEEE, 2000, 177 -181.

ENGELBRECHT R. Using Hardware-in-the-Ioop Traffic

Simulation to Evaluate Traffic Signal Controller Features

[C J / / 27th Annual Conference of the IEEE. Denver.

CO, IEEE, 2001, 1920 -1925.

YUN I, BEST M, PARK B. Evaluation of the Adaptive

Maximum Feature in EPAC300 Actuated Traffic Controller

[7 J

[8J

[9J

Using Hardware-in-the-Ioop Simulation [1]. Transporta

tion Research Record, 2007, 2035: 134 -140.

HUNTER M P, ROE M, WU S K. Hardware-in-the-Ioop

Simulation Evaluation of Adaptive Signal Control [J J .

Transportation Research Record, 2010, 2192: 167 -176.

WANG Jian-qiang, LI Ke-qiang, GAO Feng, et al. A

Hardware-in-the-Ioop Simulator for Vehicles Safety [J J .

Automotive Engineering, 2004, 26 (5): 577 -580. (In

Chinese)

YU Quan, RONG Jian. Real Time Simulation Platform

Design of Traffic Control Hardware-in-the-Ioop [1]. Jour

nal of Chongqing Institute of Technology: Natural Science

Edition, 2009, 23 (10) , 57 -60. (In Chine�e)

[lOJ ZHAO Xian-hua, CHEN Yang-zhou, SHI Jian-jun, et al.

Realization of Traffic Control Algorithm Using Traffic Simu

lation Software Paramics [J J. Journal of Highway and

Transportation Research and Development, 2006, 23 (6) :

136 -139. (In Chine�e)

[11 J HE Zhao-cheng, YU Zhi. Research on Communication

Mechanism between Paramics and Outer Programs [J J .

Computer and Communications, 2005, 23 (1): 43 -46.

(In Chinese)

[12J SU Yue-Iong, LU Lu, YAO Dan-ya, et al. Evaluation of

Imbalanced Development between Vehicles and Urban

Road Using Classical Traffic flow Model [JJ. Journal of

Highway and Transportation Research and Development,

2010, 27 (11) , 43 -46. (In Chine�e)

[13 J GAO Xiang, BAO Li-xia, BAO Jia-jia. Simulation of ETC

lanes Layout Based on Paramics [J J. Journal of Highway

and Transportation Research and Development, 2011, 28

(SI),67-70. (In Chine�e)

(Chinese version's doi, 10. 3969/j. issn. 1002 - 0268.2013.01. 019, vol. 30, pp. llO - ll4, 125, 2013)


Dow

nloa

ded

from

asc

elib

rary

.org

by

UN

IVE

RSI

TY

OF

NE

W M

EX

ICO

on

11/2

9/14

. Cop

yrig

ht A

SCE

. For

per

sona

l use

onl

y; a

ll ri

ghts

res

erve

d.

hardware-in-the-loop simulation system for multi-intersection traffic signal control

Documents