An Adaptive Service Platform for Trafﬁc Management

and Surveillance

Brahmananda Sapkota and Marten van Sinderen

Department of Electrical Engineering, Mathematics and Computer Science

University of Twente

The Netherlands

Abstract. The increasing number of road vehicles has given rise to increasingly

adverse consequences in the society. Some of the major concerns that arise due

to such an increase in road vehicles are: safety of the people using the road, cost

and efﬁciency of the trafﬁc management and the environmental footprint in terms

of, e.g., air quality, acidiﬁcation, climate change and noise pollution. Moreover,

the increased road trafﬁc, if not managed properly leads to severe congestion re-

sulting into increased delay for people and goods. We argue that we can alleviate

these problems when using an ICT-based service platform that supports localized

monitoring and management of trafﬁc and environmental information collected

from various information sources such as sensors, surveillance camera, weather

station, etc. Such information should be made available through services in order

to increase reusability, loose coupling and management of different information

and their analysis. In this paper, we discuss different functionalities that can be

or even should be supported by the service platform and provide an architecture,

following the service-oriented architecture principles, of such a platform.

1 Introduction

The mobility of people as well as goods is one of the main reasons for having road

infrastructures. Motorized road vehicles have increased the efﬁciency of mobility en-

abling people and goods to travel to longer distances in shorter time. The number of road

vehicles is increasing with the increase of populations as well as their socio-economic

interests. This has caused the saturation of road infrastructures and has ultimately af-

fected our daily lives. This increase in the number of vehicles has in fact given rise to

increasingly adverse consequences not only in the lives of individuals but in society

as a whole. Some of the major emerging concerns are: safety of the people using the

road, cost and efﬁciency of the trafﬁc management and the environmental footprint in

terms of, e.g., air quality, acidiﬁcation, climate change and noise pollution [1, 2]. The

increased road trafﬁc, if not managed properly leads to severe congestion resulting into

increasing delay for people and goods.

Several attempts have been made for developing smart infrastructures and systems

to efﬁciently manage the road trafﬁc [3–7]. Collection and processing of road users

data is performed using information and communication technologies. These systems

van Sinderen M. and Sapkota B. (2011).

An Adaptive Service Platform for Trafﬁc Management and Surveillance.

In Proceedings of the 1st International Workshop on Future Internet Applications for Trafﬁc Surveillance and Management, pages 19-28

DOI: 10.5220/0004472800190028

 SciTePress

and infrastructures are developed independently and are embedded in different vendor-

speciﬁc systems. This makes it difﬁcult for most of the current road users to take full

advantage of these technologies due to the lack of a suitable service platform with

shared conventions and standards. The existing solutions heavily rely on centralized

servers and do not consider the information available at the surroundings of the the

users (e.g., information available at the nearby user) [8]. Moreover, these solutions are

designed to assist managing the road infrastructure and therefore the drivers are unable

to utlise the instantly available information in their surroundings. For example, it is

more appropriate to ask the vehicles ahead for the road condition instead of asking such

context-dependent information from a central system.

To resolve the above mentioned issues, we need a context-aware service platform

where interacting services coexist. Such a platform should provide support for: 1)

uniform access to data and functionality offered by individual system providers and

2) seamless communication with vehicles as well as other services systems. In order

to support this, the service platform should deal with localized monitoring and man-

agement of trafﬁc and environmental information collected from various information

sources (e.g., sensors, surveillance camera, weather condition, etc.). These information

sources can be made available as information providing services. The services approach

is required to increase reusability, loose coupling and management of different informa-

tion and their analysis, which is otherwise inefﬁcient because the services platform has

to deal with an enormous amount of data. The services approach also allows for the

provisioning of the services on the cloud which is useful in achieving performance re-

quirements such as scalability and efﬁciency.

Since the service platform has to deal with real-time information several challenges

exist. We need to deﬁne a service description that allows to specify context information.

A service composition framework capable of utilising real-time (context) information

is required to provide useful information to the road users. This composition framework

should be guided by service intelligence to exploit knowledge acquired from analyzing

observed behavior of the road users. It is also required to deal with service management

(e.g. lifecycle, versioning) because the services need to be composed on a per user basis

and are usually short-lived. Generic functions available in vehicles (e.g., cars) like speed

information, engine parameters, gas usage etc. need to be provided using standardized

interfaces. The differences between existing vendor-speciﬁc technology platforms and

applications have to be bridged by an open service platform for the automotive industry.

Automotive telematics services have to be identiﬁed, satisfying the needs of the business

domain and using the technical capabilities of the network and sensor domain. Such

services, possibly run on the open service platform, may also interact with information

and computation services in the public domain, e.g., in the cloud, in order to reach its

full potential.

In this paper, we focus on the problem of providing a services platform to support

communication and coordination between road users, road infrastructure services and

third party services. Through such communication and coordination, it is possible to

increase road safety, to decrease environmental pollution and to increase the level of

comfort of the drivers at the road. To deﬁne this service platform we follow the princi-

ples of service oriented architecture [9] and context-aware computing [10, 11]. The ser-

vice oriented architecture (SOA) allows for the integration of varieties of services and

technologies whereas context-aware computing allows for real-time adaptation system

behaviour according to the changes in the users environment.

The rest of the paper is structured as follows: Section 2 describes an application

scenario to motivate the requirements of the work presented in this paper. Section 3

highlights technical challenges that need to be considered while providing a service

platform in the trafﬁc domain. Section 4 presents an initial architecture of the proposed

service platform based on SOA principles. Section 5 discusses some related works.

Section 6 points some of the issues that needs to be further considered and Section 7

concludes this paper with some suggestions for future work.

2 Application Scenario

Bob lives in the outskirt of Enschede with his wife and two children. He is scheduled

to have a project meeting in Soﬁa at 11:00 PM on Friday. He is occupied the entire

day because of the kick-off meeting of his recently acquired project on Thursday. Be-

cause Bob is mostly busy with his work (delivering lectures, attending meetings, and

doing research) during the weekdays, he spends his weekend with his family as much

as possible. When his children know about his forthcoming trip to Soﬁa on Friday, they

were sad that they will not see him during the weekend. So he promises his children

that he will return to take them to the world-famous zoological garden in Emmen at the

weekend.

He decides to travel Friday morning to Schiphol where he will take an early ﬂight

to Soﬁa. Since taking a train would not leave him enough time to check in, he takes his

car, which is equipped with Intelligent Route Planning (IRP) agent, radio and Global

Positioning System (GPS) devices.

He books the ﬂight accordingly and downloads his e-ticket to his smartphone. When

the e-ticket is downloaded, his smart phone recognizes it and wirelessly communicates

with an IRP agent installed on his car. This agent communicates with the GPS device

installed on the car and determines the required travel time to reach to the Schiphol air-

port. The IRP agent, knows that Bob normally wants to arrive at the airport 30 minutes

before the normal time as suggested by the airlines and thus calculates the time Bob

needs to start his journey. The IRP agent communicates this information to Bob’s smart

phone. Bob’s mart phone then uses this information and sets his alarm accordingly.

When he follows the route shown on his GPS system, he suddenly encounters that

the road is blocked because construction works. He then ignores the advice from the

GPS system and drives on a different road than suggested by the GPS system. The

GPS system apparently does not know about this situation and road that Bob is driving

because it is a newly constructed road, it keeps advising Bob to take a U-turn if possible.

Bob keeps ignoring the advice and keeps driving using his own instinct and sense of

direction. After a while, the GPS system recognizes the stretch of road that Bob is

driving and recalculates the route for Bob. The road that Bob was driving based on his

own sense of direction turns out to be a faster section of the road in early morning travel

time. The IRP agent on his car records this newly discovered route and updates the map

and broadcasts the plan to the passerby cars.

While on his way, the IRP agent installed on a car coming from the opposite direc-

tion communicates information of long jam of cars 10 KM ahead because of a recent

accident to the IRP agent installed on Bob’s car. The IRP agent then communicates this

information to the GPS system to re-calculate the route.

When he is driving on the re-calculated route, the IRP agent communicates with

the Road-Side Infrastructure (RSI) and ﬁnds out that the trafﬁc near the next junction

where Bob has to turn right is congested (the RSI can determine such a situation by

using information from loop detectors). The IRP agent informs Bob to change the lane

well in advance. The IRP agent also predicts, based on the current weather conditions,

total number of current road users and their average speed, that the joining road ahead

of the next junction could have black ice. The IRP agent then informs Bob to drive at

safe speed to avoid a possible slippery road condition.

When Bob drives some 100 KM, The IRP agent receives information from the RSI

that there is a poor visibility 20 KM ahead of the road and schedules the light control

system to brighten their light calculating the time required to reach that spot. When

Bob passes the poor visibility area, the IRP agent identiﬁes that the visibility is OK and

resets the high to their original intensity through the light control system.

When at parking lot at the airport, Bob’s car recognises that his friend Dave is also

at the airport, and sends him an invitation for a coffee if he has time. Dave replies with

a call and they meet at a nearby coffee shop. After having a chat with his friend, Bob

goes to check-in his ﬂight and leaves for Soﬁa.

After his meeting in Soﬁa, Bob returns to the Netherlands. When he lands at the

Schiphol airport, he turns his smart phone on. His smart phone then wirelessly com-

municates with the IRP Agent at his car. The agent then communicates with the GPS

system and calculates the time required to reach his home and informs his wife Alice

about his arrival time. Bob then continues his journey towards his home following the

route displayed on his GPS system.

After driving 45KM, the road RSI communicates to the radio device installed on his

car that the road further ahead is busy (which is expected because it is a Friday night).

The RPI agent receives this information through the radio device installed on Bob’s

car and communicates with the GPS system to recalculate the new route and new time

required to reach Bob’s home. It appears that Bob will arrive home 30 minutes later

than previously expected, the IRP agent then informs Alice that Bob will be late by 30

minutes because of busy trafﬁc.

The new road that Bob is driving now is relatively empty ahead of him, however

there are few cars behind him. When he approaches Enschede, the IRP agent commu-

nicates with the RSI and ﬁnds that an ambulance is coming on the joining road at the

junction ahead and Bob will not be able to cross it safely. The IRP agent then informs

Bob to slow down because the trafﬁc light at the junction is going to turn red because

of the high priority vehicle on the other road. When he starts decelerating, the IRP

agent communicates with the IRP agent on the car behind Bob (which was out of the

range of RSI communication) and informs that Bob is decelerating. The IRP agent on

the car behind Bob then informs his driver Tim to start decelerating to avoid possible

environmental pollution (noise, air) and a possible collision because the car in front is

decelerating for some reason.

When the ambulance crosses the junction, RSI broadcasts the message that it is

going to turn the trafﬁc light to green because there are no other vehicles on the joining

road. The IRP agent informs Bob to smoothly accelerate and move forward. Finally,

when Bob arrives at home, Alice is waiting for him with a hot cup of coffee, he starts

talking with Alice while drinking his coffee.

2.1 Functional Requirements

Based on the application scenario described in Section 2, we deﬁne a set of functional

requirements that should be provided by a service platform. Below we describe some

of these functionalities and the information required to provide these functionalities.

Lance Changing. The lane changing is one of the complex tasks, which needs to be

decided by the driver based on the current situation at road. There might be various

reasons for decising on changing the lane while driving on the road. Drivers need

to assess the situation, ﬁnd the appropriate gap, ensure there is no bliend-spot situa-

tion and make the decision instantly. The reasons for changing the lane could either

be mandatory or discretionary. It is mandatory to change the lane when the current

lane is ending or the vehicle is facing the hazardious situation or the driver intends

to take a turn at upcoming junction and therefore the vehicles needs to be on the dif-

ferent lane. It is discretionary to change the lane if the preceding vehicle is driving

slower than normal speed. In such situations drivers can be assisted to change their

lane safely based on route calculation (e.g., turn left at next junction) or current traf-

ﬁc situation (e.g., overtake to move faster). While assisting the drivers, bliend-spot

situation must be assesed based on run-time information possibly collected through

inbuilt sensors to prevent possible crash with a nearby vehicle.

Curve Speed. Driving at the curved can be difﬁcult especially when the weather con-

dition and visibility are poor. Informing the driver as far ahead as possible about

the existence of a curve and the weather condition will allows drivers in negotiating

curves at appropriate speeds. This will help in reducing the possible risk of sliding

and unexpected crashes. This can be supported possibly by combining weather in-

formation, current speed of the vehicle, its GPS position and the digital map of the

street.

Collision Avoidance. A vehicle on the road is vulnerable to collision not only because

of the carelessness of its driver but also because of the actions of the drivers on

other vehicles. It can also happen because of the occurrence of the unexpected

and emergency events at the road. For example, icy road surface can cause the

collision between cars. If emergency situation arise, a preceding car (not only the

one at immidiate front but could also be the one at ten cars ahead) could suddenly

break, leaving insufﬁcient time to react safely. In such situation, drivers can be

assisted based on the speed of the preceding cars which can possibly be collected

by backward propagation of preceeding cars. Drivers can be informed to slow down

if the preceding cars suddenly decelerate because of some unexpected reasons.

Pollution Control. Increasing number of vehicles on the road is one of the contributors

to air pollution in urban areas. In fact, the driving/speeding pattern of a vehicle can

be used to determine how much it contributes to the environmental pollution. The

drivers can be assisted to maintain their speed at optimal level on the road thereby

assisting in minimising their pollution contribution. Since the speed of a vehicle is

dependent on the speed of other vehicles, weather condition, condition of the road

and other situations at the road (e.g., maintenance, accident) such information could

possibly be backward propagated for avoiding abrupt deceleration/acceleration of

succeding vehicles.

Hazard Situation Avoidance. Drivers on the road often encounter hazardious situa-

tions. This could be because of bad weather condition, poort visibility, construction

works at the road or sudden emergency etc. In such situation, drivers should be

adviced in good time such that such situation can be avoided. Drivers can be ad-

vised, for example, to prepare to slow down because the road ahead is slippery or

road ahead has poor visibility. In order to provide such advices, information could

be gathered from different sources such as weather station, road infrastructure ser-

vices or oncoming vehicles, etc.

Rerouting. When the road ahead is blocked because of some unexpected situation, it

might be beneﬁcial to advice drivers to take different route to their destination. The

alternative route can be calculated based on information collected from vehicles

coming from opposite direction, road infrastructure services or information from

central server (providing trafﬁc information of the local areas). Vehicles coming

from the opposite direction can provide information based on their observation of

the road, e.g., re-route because the road ahead is blocked due to recent accident,

which may not be available through other sources.

The list of functionalities discussed above is not exclusive and these functionali-

ties are also not orthogonal to each other. However, the list gives the impression about

what type of functionalities are useful to maintain safety of the drivers, environmental

sustainability as well as the management of the road trafﬁc.

3 Challenges

In order to fulﬁll the requirements of trafﬁc management and surveillance, the service

platform should support integration of and interoperation between different services.

The services are heterogenous in nature, i.e., they could be context dependent, short

lived, localized and situation aware. Similarly, the interaction between these services

could also be ad hoc and use heterogeneous communication protocols. In addition, these

services has to deal with near real-time information. There are several technical chal-

lenges that need to be tackled to achieve integration and interoperation between these

services in this domain.

Since the services are typically context dependent, exhibit dynamic behaviour and

heterogeneous, the existing tools and technologies cannot be used as it is. We need a

suitable service description model, which allows to describe not only the functional

charecteristics of the services but also the context and situation at which these services

can be used. This further requires a suitable composition model, which allows to com-

pose such services based on (near) real-time information. The real-time information

can be complemented with the knowledge extracted from the past behaviour of the road

users. In order to support this, a suitable service intelligence model is required such that

the extracted knowledge can be utilised in delivering the useful services to the users.

Drivers on the road are busy controlling the vehicle with their hands and legs oc-

cupied. This requires for a suitable iterface to the systesm such that the drivers can

still concentrate on driving while being assisted. Similarly, the provisioning of services

taking into account the interests of the users and the technical capabilities of the com-

munication infrastructures and the sensors is another challenge which needs a serious

attention. Moreover, providing consistency and the performance guarantee of such sys-

tem is far from trivial.

4 Solutions

We describe a service platform to support communication between vehicles as well as

between vehichles and road infrastructure through the concept of services orientation.

The concept of service orientation is used to integrate various types of systems and

services. It is also used for supporting interoperation between these services and sys-

tems. Figure 1, shows the high level interaction between these systems and services.

Furthermore, the service orientation allows us to deploy services in the cloud to achieve

performance requirements such as scalability and efﬁciency.

8-11-2011

Initial Service Platform

Road Side Infrastructure

Cars with Smart Devices and FIATS-M Agent

Back-end IS Infrastructure

Third Party Services

Fig. 1. Communication between Cars, Infrastructure and Services.

As seen in the ﬁgure, the service platform needs to provide supprot for different

communication protocols as well as service descriptions. To supprot this requirement,

the service platform provides a standard communication interface which bridges the

protocol heterigeneity through the use of adapter. The heterogeneity between service

descriptions can be handled by deﬁning an intermediate description language which

can allows us to deﬁne mappings without knowing the targed description language. The

back-end IS infrastructure is used to process the collected information and to derive

useful information or the composition of services for the user. The services can either be

registered to the back-end IS infrastructure or be discovered on demand. The vehicles

in the range, can communicate with themselves without requiring to go through the

back-end IS infrastructure.

5 Related Works

There is signiﬁcant ongoing work in the area of road trafﬁc management and surveil-

lance through smart technologies. An agent based approach is used in [12], aiming at

providing a semantic middleware for context-aware smart road dnvironments. The con-

text information is extracted using data mining techniquest over the collection of data

obtained from various sensors.

A Peer-to-Peer based infrastructure supporting communication between vehicles

and with the road-side infrastructure is deﬁned in [10]. This work is focused on sharing

context-aware road and safety information between different road users. Though their

work supports such a communication, it does not spacify how up-to-date are the shared

information.

In [13], an approach for supporting vehicle to vehicle communication is proposed.

It employes message broadcasting as a means to support communication between vehi-

cles. Using some intelligent communication pattern, a vehicle can notify about certain

events to the nearby vehicles.

Using the color and edge information, a technique to detect trafﬁc light is proposed

in [14]. The proposed technique is deﬁned based on image processing and statistical

techniques. Detection of trafﬁc light helps in replanning the route or suggesting drivers

to stop safely at right time.

The existing systems focus on trafﬁc management and surveillance taking into ac-

count the interests of the infrastructure providers and not the interests of the road

users. Moreover, these systems do not fully utilise the collective intelligence and spatio-

temporal correlations of the vehicles and their movement pattern.

6 Discussion

In the trafﬁc-domain, a huge amount of information about road user is collected and

processed to manage the road trafﬁc in an efﬁcient manner. The sensors, loop detectors

and cameras are the commonly used tools and techniques for collecting these informa-

tion. The information thus collected are sparse, dealing with these information to make

certain decision is not as easy as it should be. Therefore, it is necessary to identify what

information is needed and how these information can be gathered to provide usefuls

services to the users.

The speed of a vehicle depends on the speed of the preceding vehicle. The preceding

vehicle may be intentionally driving slowly. It is not clear how to deal with such a situ-

ation. If the preceding vehicle is the main source of congestion and hence the cause of

other problems (e.g., air pollution), the vehicle behind it is left with no option that just

contributing to the problem caused by the preceding vehicle. This problem may possi-

bly require some business intelligence to panalize the intentionally troubling vehicles

possibly through communication between vehicles and/or vehicle to infrastructure.

When such communication takes place, the information need to be shared between

the communicating parties. It is therefore necessary to identify how privacy sensitive is

the information being shared. If the information is privacy sensitive, it has to be dealt

with accordingly to avoid any unauthorised manipulation of the information.

7 Conclusions

This paper discusses how a service platform can support communication between ve-

hicles and between vehicles and road infrastructure services as well as third party ser-

vices. The service platform is based on the concept of service oriented architecture and

is aimed at supporting integration of and interoperation between different systems, ser-

vices and information in road trafﬁc domain. This further allows for providing various

user-centric services which help at maximizing user safety, minimizing congestion and

environmental pollution, and optimizing the use of road with maximum efﬁciency. In

the current work, we identiﬁed different challenges which need to be technically tack-

led. In our future work, we aim at ﬁnding the solution to these challenges and extending

the architecture accordingly.

Acknowledgements. This material is based upon works jointly supported by the IOP

GenCom U-Care project (http://ucare.ewi.utwente.nl) sponsored by the Dutch Ministry

of Economic Affairs under contract IGC0816 and by the DySCoTec project sponsored

by the Centre for Telematics and Information Technology (CTIT), University of Twente,

The Netherlands.

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