LOGGING, ALERT & EMERGENCY SYSTEM FOR ROAD

TRANSPORT VEHICLES

An Experimental eCall, Black-box and Driver Alerting System

Javier Fernández, Fernando Cantalapiedra, Mario Mata, Veronica Egido, Sergio Bemposta

Computer Architecture and automation dept., Universidad Europea de Madrid, Villaviciosa de Odón, Madrid, Spain

Keywords: Driver assistance, eCall, digital black-box, sign detection, alert system.

Abstract: This paper describes the experimental platform developed at UEM, mounted on a conventional vehicle. It

monitors most of the driver’s actions on the controls of the vehicle, logs the vehicle speed and position

using a GPS, detects and recognizes vertical traffic signs, and records the last seconds of the trip with a

panoramic video camera. If an accident occurs, the system calls emergency services (112 in Spain) sending

vehicle position information (via SMS) and opening a voice channel.

1 INTRODUCTION

The alert and control system developed in SACAT

project (Control and Alert in case of Accident

System for road Transport vehicles) is intended to be

used in freight and also in human transport by road.

It aims to increase security, specially trying to save

human lives by decreasing the time until assistance

arrives.

EU White Book on European Transport Policy for

2010 reveals worrying data. Taking into account all

costs, road transport represents approximately 1

billion Euros (above 10% EU gross domestic

product). Road transport carries 44% of total freight

and 79% of total people transportation. Between

1995 and 2003, road freight transport increased

19.4%, while rail freight transport decreased 43.5%

in the same period. However, road transport is the

most dangerous one, having a terrible cost of human

lives, and provoking expensive traffic jams (fig. 1).

EU proposes a two-lined action: agreement in

penalties, and the promotion of new technologies in

road security. It explicitly establishes that

technological evolution will also allow strengthening

the usual control and penalty means, using automatic

systems and driving-assistance on-board devices.

Related to this, EU proposes the use of black-boxes

in vehicles, for registering relevant parameters to

analyze the causes of an accident (like in other

transportation means).

Figure 1: Multiple accident and closed road.

In the same line, EU has adopted a directive, named

eCall (in the E_MERGE program) that will make

compulsory the installation of an alerting device in

every new vehicle marketed in the EU from 2009

on. This device should automatically alert

emergency services in case of accident using mobile

phones and GPS (EC,2003).

Another EU measure aimed to improve security in

freight vehicles is the obligation of installing digital

tachometers from August 2006 on (in Spain this

date has been moved to august 2005 for vehicles

above 3,5 tons or 9 passengers).

384

Fernández J., Cantalapiedra F., Mata M., Egido V. and Bemposta S. (2006).

LOGGING, ALERT & EMERGENCY SYSTEM FOR ROAD TRANSPORT VEHICLES - An Experimental eCall, Black-box and Driver Alerting System.

In Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics, pages 384-389

DOI: 10.5220/0001204303840389

 SciTePress

The system described in this paper follows all these

lines of action in security matters, and puts them

together in a single prototype. Furthermore, it adds

some functionalities that will surely be included in

security directives in the future, such as automatic

recognition of traffic signs (Escalera,2003) and real-

time alerting to the driver. The whole system tries to

lower the risk of accident; and if it finally happens,

tries to minimize the time until victims are assisted,

and provides critical information for analyzing the

reasons.

The developed prototype is composed of two main

modules, with the following functionalities:

Black-box. Records the detected signs, vehicle data

(speed, position, driver actions) and a panoramic

video of the last minutes of the trip.

Alert System. If an accident takes place, the system

sends a text message (SMS) to emergency services

(112 in Spain). It includes the location of the vehicle

(GPS), kind of vehicle and load data (number of

passengers, dangerous loads, etc). This is an

essential matter, because every minute counts when

a person is wounded in a traffic accident. Recent

studies established that the probability of an accident

victim of surviving is doubled if he/she is assisted in

the first 20 minutes after the crash.

Additionally, a bidirectional voice channel is opened

in an automatic manner, allowing direct

communication between 112 emergency services

and the passengers. It can also be manually launched

with an emergency button, if a passenger gets ill, or

the accident of a nearby vehicle is seem; the vehicle

position is also sent to the emergency service, so

there is no need to spend precious time trying to tell

where the incident is.

In the next sections, the system architecture, the two

main modules and the sign recognition subsystem

are detailed. Finally, in section 6, the present system

performance is described, and the opened lines of

work and improvement are discussed.

2 SYSTEM ARCHITECTURE

The system has been implemented on a conventional

vehicle Renault Express (figure 2). This model lacks

of communication bus, so all the instrumentation

and wiring associated to driving devices have been

added. The whole system uses the vehicle’s 12V

battery by means of a 600W dc/ac inverter, sourcing

220 AC volts. This allows using standard

equipments.

Figure 2: Test vehicle from SACAT.

The core of the application is formed by a

conventional PC and a PDA. The sensorial system

includes the following devices:

• Bluetooth GPS module

• Mobile phone with Bluetooth interface

• Panoramic color CCD camera

• Conventional color CCD camera

• Encoder reading steering wheel movement

• All/nothing sensors for pedals, direction

lights, hand brake and contact

The PC hosts the main system interface, feeds the

black-box (external USB drive), captures panoramic

and frontal video, and registers the data from the

driver’s action sensors. It also processes the frontal

camera images for detecting vertical traffic signs.

GPS

PDA

GPRS

Color camera

Panoramic

camera

Vehicle

sensors

Figure 3: SACAT architecture.

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The GPS receiver is used for registering the speed

and coordinates of the vehicle; they are stored in the

black-box. The mobile phone allows communication

(SMS and voice channel) with emergency services

when a collision is detected (using the airbag firing

sensors) or when the driver uses the emergency

button, following eCall standards.

The PDA works as a wireless interface between the

GPS and mobile phone with the PC. It also is used

as input device for the system: data about the driver,

load, route, etc. is loaded in the central control of the

transport firm, and then plugged into the system.

Figure 4: Interface devices in SACAT.

3 LOGGING SUBSYSTEM

This subsystem is responsible of saving relevant

information from the system such as video, sensor

and GPS data, etc. This module is called “Black-

box” because of their similarity to the ones in

airplanes.

Panoramic video (fig. 5) is recorded by saving

periods of time in several consecutive files; the

oldest one is deleted each time a new file is saved, to

avoid running out of storage space in a long trip.

This way, the last images of the environment around

the vehicle before an accident are left available for

posterior analysis. This information facilitates

finding the causes of the accident (to avoid them in

the future), and clarifying responsibilities for it. The

video recording is done as a background process and

doesn’t interfere with the other processes of the

system.

Figure 5: Panoramic video.

Images are obtained using a 3D Sony CCD camera

mounted on the roof of the vehicle. When the

vehicle is stopped for a significant time during a trip

(to rest or have a break, for example), a separate

group of video files are saved, acting as a

surveillance device.

The sensor information is obtained from several

driving devices, such as pedals (clutch, brake, and

accelerator), steering wheel, indicators, hand brake,

and contact. The sensors are read using a data

acquisition card in the PC. The information gathered

is saved in the black-box’s database each time it

changes. A timestamp is added for each entry.

Position and Speed of the vehicle are obtained from

a bluetooth GPS device in the PDA (where a

navigation application can be run), and sent to the

PC via wireless. This information is also saved in

the black-box database.

When an accident occurs, the last GPS position (and

other relevant information, see next section) is sent

to the mobile phone, and then to emergency

services.

The aim of this black-box is to store a log of the trip,

and specially a log of the environment and the last

actions of the driver just before an accident.

4 ECALL SUBSYSTEM

In this section, the alerting module of the system is

described. It is designed to be adapted to the rules

established by the European Commission (EC), the

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European Association of Vehicle Manufacturers

(ACEA) and the multi-sector public/private-

partnership for the implementation of Intelligent

Transport Systems and Services (ERTICO). These

entities work for the introduction of an emergency

call system that will be automatically launched in

case of accident, named eCall. This system will

automatically alert emergency systems and provide

them with critical information about the accident.

eCall has therefore the potential to greatly reduce the

number of fatalities, the severity of injuries and the

stress in post-crash situations, by speeding up the

response of the emergency services and allowing to

choose the adequate material and human resources

needed for each accident.

This emergency call module incorporates this

functionality, and some others, according to the

configuration shown in figure 6.

Figure 6: Emergency call module.

Figure 6 shows the hardware elements involved in

the emergency module, and the steps given after an

accident occurs. Hardware architecture is composed

of a GPS receiver, the main PC, a PDA and a mobile

phone with Bluetooth connectivity.

If an accident occurs, the PC receives the airbag

signal, and then activates the emergency module.

This module sends an SMS via the mobile phone to

the corresponding PSAP (Public Safety Answering

Point), 112 in Spain. The message sent to the PSAP

should contain the so-called MDS (Minimum

DataSet). This minimum set of data consists of the

following information: “When”, “Where” and

“Who” (E-merge,2004).

This information is considered the minimum needed

for speeding up emergency services’ response with

the adequate resources. The message sent contains

the instant of the transmission ‘hh:mm:ss’ (“When”),

the latitude, longitude and movement direction of

the accident (“Where”), and information about the

driver and the load of the vehicle (“Who”). With the

standardization of the e-Call information, messages

will be adapted to the same model for all countries.

The system implemented in this project could be

easily adapted to send the so-called FDS (Full

DataSet) that would contain additional data

(enterprise information, insurance data, etc.). The

idea promoted in the European program is to send a

MDS to the PSAP and more detailed information to

a private service provider (PSP).

Considering the importance of the emergency

message, after sending it for the first time, the PC

sends a signal and the information to the PDA, that

will be in charge of two different tasks: sending

again the message via mobile phone, and

establishing a voice call to make possible to the

emergency services to talk with the vehicle

occupants if conscious. This call can also be

manually established.

5 SIGNAL RECOGNITION

SUBSYSTEM

Detection of vertical traffic signs is a classic

application for computer vision researchers, that still

remains unsolved (except in particular and

controlled situations). In the last decades, promising

results have been obtained thanks to new

computational techniques ((Bahlmann,2005),

(Escalera,2001), among others) but surprisingly very

few systems has been integrated in a real vehicle

with some success, as for example (Priese,1994) in

their vehicle VITA II. The system developed in our

project SACAT, although far from being

commercial, opens real and promising

experimentation and improvement ways.

Accident

MDS information is sent via

wireless

1º

2º

3º

GPS

information

Accident

MDS information is sent via

wireless

1º

2º

3º

GPS

information

LOGGING, ALERT & EMERGENCY SYSTEM FOR ROAD TRANSPORT VEHICLES - An Experimental eCall,

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The traffic signs recognition module integrated in

the system tries to detect and then read the vertical

signs present along the road. This is done aiming at:

- Logging the signs in the Black-box’s

database.

- Alerting the driver in dangerous situations,

such as:

o Over speeding

o Overtaking prohibitions

o Crossroads, Stops, Give way signs

o Curves, slopes, road works

This module uses a color CCD camera with

adjustable zoom, mounted inside the vehicle and

aiming at the movement direction. Each image is

processed following the these steps:

Step 1: Sign detection.

First, objects candidate to be signs are detected and

isolated. A color segmentation, followed by a shape

analysis, are used for this purpose.

Color segmentation is done in HLS space, using a

parametrization learned off-line with a genetic

algorithm. It results in a series of objects that are

subjected to a shape analysis (figure 7).

Figure 7: Color segmentation and shape analysis.

The shape analysis is done by first filtering by

geometric restrictions, followed by a probabilistic

adjustment of straight and curve lines to the shapes

(Blake,2005), (Gonzalez,2002). Objects surviving

both processes have a high probability of being

traffic signs, because at least they have the right

colors and shapes.

Step 2: Sign reading and interpretation.

Objects surviving first step filtering are passed to the

reading phase. The content of the objects is matched

with a data base with the legal traffic signs. This is

based on correlation matching techniques with

dynamic deformation.

Figure 8: Reading and interpretation.

The final result is an interpreted sign (figure 8), that

is logged into the black-box’s database, and can be

used for driver alerting policies. If the interior of the

object is not recognized, it is discarded.

6 CONCLUSSIONS AND FUTURE

WORK

The prototype described in this article, developed

within the SACAT project, has been driven in tests

for more than 5000 km. Its current state and

performance is as follows.

The Black-box module is fully operative, logging

data of the vehicle and trip every second. The output

of this module can be adapted to any of the

upcoming UE standards for this kind of systems.

Within this module operates the signal recognition

subsystem, that currently works with vertical danger

and prohibition signs. This subsystem is currently in

a full experimentation and improvement phase,

having promising results:

- Right recognition in 83% of danger and

prohibition signs

- 5% confusion between similar signs at long

distances (2% short distances)

- Detection distance between 10 and 50 m

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- One image per second processing

Alert module is also fully operative. Results

highlights in crash simulations (alert messages were

sent to a private mobile phone) are:

- SMS with the MSD successfully received in

destiny: 98%. A few SMS were lost or not

sent in absence of coverage.

- Voice channel successfully established

when coverage available (95%).

Future improvements we are currently working in

are:

- Enhancing traffic sign recognition

subsystem by:

o Improving system robustness.

o Including informative panels to the

set of signals handled.

- Detecting road lines and lane markings for

preventing involuntary lane changes

- Using optical flow techniques to estimate

distances to other vehicles and to the road

limits (active radar). This helps the driver

to keep secure distances.

- Improving communication with emergency

services using UMTS (3G) technology.

This allows to establish a video call as well

as a voice call, allowing to evaluate the

state of the vehicle and its occupants.

REFERENCES

European Comission (DG Enterprise and DG Information

Society), eSafety forum: Summary report 2003, March

2003.

A. de la Escalera; J. Mª Armingol; M. Mata. “Traffic Sign

Recognition and Analysis for Intelligent Vehicles”.

Image and Vision Computing 21, pp 247-258, 2003 .

E-merge final report June 2004 IST-2001-34061.

http://www.gstforum.org/en/subprojects/rescue/about_

gst_rescue/introduction/e-merge.htm

Claus Bahlmann, Ying Zhu, Visvanathan Armes, Martin

Pellkofer, Thorsten Koehler: “A System for Traffic

Sign Detection, Tracking, and Recognition Using

Color, Shape, and Motion Information”. IEEE

Intelligent Vehicles Symposium (IV 2005). 2005.

A. de la Escalera, J. M. Armingol,, M.A. Salichs. “Traffic

Sign Detection for Driver Support Systems”. 3rd

International Conference on Field and Service

Robotics, pp 141-146.Espoo, Finlandia. June 11-13,

2001

Priese, Lutz and Klieber, Jens and Lakmann, Raimund and

Rehrmann, Volker and Schian, Rainer. “New Results

on Traffic Sign Recognition”. Proceedings "Intelligent

Vehicles Symposium '94".pp. 249-254. 1994.

Andrew Blake and Michale Isard. “Active Contours. The

Application of Techniques from Graphics, Vision,

Control Theory and Statistics to Visual Tracking of

Sahpes in Motion”. Springer-Verlag Berlin

Heidelberg. New York. ISBN 3-540-76217-5

E. González, V. Feliú, A. Adán, L. Sánchez. “Descriptores

de Fourier para identificación de objetos en entornos

3D”. http://www.isa-

cr.uclm.es/xxvjornadas/ConfMan_1.7/SUBMISSIONS

/140-liezgarthg.pdf

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