Threat of human faults danger in car-driver interactions

Mirko NovákConference WSEAS, Prague, March 13, 2005

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Prof. Ing. Mirko Novák, DrSc.,

Czech Technical University in Prague,

Faculty of Transportation Sciences,

Department of Control Engineering and Telematics,

Joint Laboratory of System Reliability,

11000 Prague 1, Konviktská 20, e-mail: mirko@fd.cvut.cz

Abstract:Human activity has to be considered as the less reliable

component of all the human subject – artificial system interactions. This concerns also all the contemporary transportation systems. The losses cause by human faults in transportation reach extreme values and have tendency to increase year by year.

A significant part of these losses comes from the decrease of human subject attention when operating or using the transportation system, namely driving the car.

Another considerably large part of these losses has its origin in splitting of the driver attention between the functional and marginal stimuli.

Also the masking of some minor stimuli by those, which dominate in the set observed by driver, can cause serious accidents.

In this key-note a brief discussion of these factors, having serious negative influence on transportation reliability and safety is mentioned and some ways for its minimization are proposed.

1. Introduction

The very long experience with human beings dealing with artificial systems leads to the regrettable observation, that the human factor is very often the weakest and most dangerous point in the interaction.

The reason for this is quite natural and easy to understand: – Unlike artificial systems, humans cannot operate

indefinitely without a break – human beings need to relax, rest and sleep. Decreases of human vigilance and attention while operation or using an artificial system has always been - and still is - the most frequent cause of system failures, accidents and catastrophes.

- Another source of system failures lies in the possibility that the human operator (or user) of a particular artificial system may react too late, and that his/her decision and reaction may be incorrect.

- No human subject is identical. Human behavior is not fully deterministic; it varies from subject to subject.

All these factors combine, with the result that the reliability of human subject – artificial system interaction is very limited, before all from the human side.

The price that we all pay for insufficiently reliable and safe human – artificial system interaction is tremendous.

If one takes the statistical data on road traffic accidents into account, one finds that only in the EU there were in 2002 rougly 42000 mortal accidents per year, which represented the losses of about 165 billion Euro.

The estimations how much of these losses are caused by unsatisfactory level of human operator (driver, dispatcher etc.) attention differ according to used methodology – which is stil not standardized, unfortunately – but can be taken between 15 and 50%.

If we take the lower limit into account, we can speak on losses about 25 billion Euro in the EU, which are caused by low level of drivers attention.

Moreover, this losses have the tendency to increase in time and also - surprisingly - with the level of the the power and sophistication of the respective transportation system.

We therefore urgently need to counteract this human subject unreliability in interaction with artificial systems.

 

Investigating the reliability of interaction between a human subject and an artificial system, we are interested before all in such situations, when a particular human subject is exposed to the influence of various external stimuli.

These situations are typical namely for the human subject interaction with transportation vehicle (car) and/or with the whole transportation system.

A set of such external stimuli can be characterized as

• very variant,

and • changing significantly under influence of

many independent variables, namely the time.

The signals, with which the driver has to interact when driving the car on the road, can be classified in the following main groups:

a)    Visual signals representing the observed external scene of the road and its nearest environment, which can have the influence on the situation in the front of the car or on both its sides;

» b)    Visual signals observed by driver in the rear and both side mirrors;

» c)     Acoustic signals concerning the traffic on the neighborhood of the car;

» d)    Acoustic signals coming from the car body and car engine;

» e)    Acoustic signals coming from the tires and wind;» f) Signals representing the drivers interaction with the

car control tools and auxiliary cockpit equipments (communication and navigation before all);

» g)    Signals coming from the driver interaction with the car crew.

2. Attention decreases

  From the above-mentioned 7 groups of signals, representing the most important stimuli influencing the driver, only the first 3 can be considered as directly related to driving activity.

Let denote them by word “functional stimuli” Sf.

The other 4 groups of stimuli have no such direct relation to driving reliability and we shall call them as “marginal”.

When driver observes the functional stimuli in the course of his/her driving,

• he/she becomes subsequently tired,

• his/her attention level LAT decreases,

• reaction time TR prolongs and the

• probability Pcorr of his/her correct response on certain

stimulus of the group Sf decreases.

This increases, of course, the danger of an accident.

The resistance of the driver against the influence of attention decrease is very individual,

however it can be • measured, classified and by • special training methods (namely by those,

based on the so- called bio-feedback technology) it can be also significantly improved.

Besides this, there is possible to construct various warning systems, the aim of which is

• to continuously measure the level of driver attention in the course of driving,

• to predict its further development and • to inform and to warn the driver if the decrease of

his/her attention falls under certain limit.

Because the direct measurement of the values LA in the course of driving is quite problematic, various

indirect attention level indicators are used.

Among them, those based of the sophisticated analysis of drivers EEG (electroencephalographic) signals play the dominant role (because allow the most specific, reliable and fast determination of the actual state of driver attention). Though the attention classifiers and predictors derived from EEG analysis are very individual and must be developed for each particular driver specially, they operate considerably reliable for long time (up to few years) if the respective human subject does not undergo some mental decease or accident.

While various warning systems appearing on the market are based usually on the so called secondary attention level indicators (eye movement, skin impedance, face grimaces analysis etc.), only those, using the brain electromagnetic radiation as the key source of information of his/her attention can be considered as satisfactory specific and reliable.

The presence of any marginal stimulus in the set observed by driver can lead to the splitting of his/her attention, so that the part of it, oriented to functional stimuli Sf

related directly to driving decreases.

Another way for improving the driving reliability is therefore to modify the arrangement of the car-cockpit interior so that the influence of the marginal stimuli Sm on the driver

attention splitting is minimized.

However, because each human subject has in any instant only a limited capacity of his/her attention at disposal, the presence of signals belonging to any of marginal group lead to splitting of the driver attention into two parts:

   that, which is immediately concentrated to driving and

   that, which is consumed by the sum of all the marginal signals.

The total attention disposable capacity CAT of the

particular driver driving certain car at some specific situation can be expressed as

………………………..(1)

The value of the integral (1) varies from driver to driver and depends also on his/her physical and psychical condition.

dttLCft

tATAT

0

In any case this disposable capacity is subsequently exhausted, of course not in monotonic manner. In the instant tk only the part

………………………………….(2)

remains.

The procedure of the driver disposable attention capacity CAT depends also on the type of the

respective car, on the type and quality of the road, on traffic intensity and on the whole set of environmental conditions of driving.

dttLCCrkt

tATATAT

0

Let us denote

the intensity of partial visual signals concerning the transportation situation in front of the car as sfi,,

and

the intensity of individual visual signals with regard to the marginal situation as smj.

The total intensity of visual signals coming to the driver’s brain on the basis of the road observation, can be then expressed as:

Sr = = Sf + Sm, ……………………...(3)

where i = 1…nf is the number of significant signals, and j = 1…nm

is the number of marginal signals.

m

j

f

i

ni

jm

ni

if ss

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In reality, the no human subject can observe all the acting stimuli at once, thus, also his/her short-term memory has to be taken into account in the course of the entire recognition process.

Therefore the driver attention is switched into the above-mentioned two parts by the influence of Sf and Sm.

The dynamic such attention switching is considerably complicated and its detail analysis was till now not finished.

In any case, the necessity that driver reacts on some marginal signal detour his/her attention for some instant out of the main direction, i.e. the observing of the signals Sf and

reaction on them.

This is the reason, why, as for the driver’s attention, we are interested in the ratio

= Sf/Sm,…………………………………...(4)

and also in the ratio

, ………………………………(5)

representing the corresponding splitting of the drivers attention level LA.

fm ATAT LL /

The attention splitting is not only the result of the impact of the environment, irrelevant to driving, but also by some other stimuli, such as the lights of the surrounding buildings, the road illumination lights, the sun shining at low angles, the lights reflecting on the wet road surface, road semaphores and marks, as well as various signs, and, particularly the advertisements.

Disturbing signals coming from the cockpit interior are to be taken into account as well. It is obvious that often the number of these disturbing signals is quite high.

At present many car manufacturers are interested in improvement of cockpits of their cars with respect to higher driving safety and reliability.

Many various solutions appear.An extreme example of such a solution is shown in Fig. 1. It presents a view of a experimental cockpit design Here, the driver is forced to deal with many stimuli undesirable for driving. The main part of them badly distract his/her attention from focusing on the situation on the road.

Fig.1: Example of a scene loaded with a quantity of signals from the car interior which distract the driver’s attention from the situation on the road

Fig. 2: The view of the cockpit of the Skoda Superb car, in which the deviations of the driver’s view are shown from the standard point of the observation of the external scene on the road to the views on internal control display (yellow arrow), navigation display (blue arrow) and radio display (green arrow).

In Fig. 2 is the cocpit of the Skoda Superb car.

Here the situation is much simpler and the driver can control in much easily than the one shown in Fig. 1.

However, also here the navigation tools, which forms an un-negligible part of the information content sources, involved in the cockpit of modern car, has to bee optimized.

In Fig.2 the navigation display is too small, and unsuitably located – actually, it can only be noticed when the driver diverts his sight from the situation on the road.

This is evident from the length of the blue vector shown in Fig. 2., representing the necessary deviation of the driver’s sight, one counts on, while having a look in the direction of the navigation display, and, at the same time, fulfilling the activities of driving. Similar situation occurs when dealing with the car control display (yellow arrow in Fig. 2) or the radio receiver panel (green arrow in Fig. 2).

Investigation of the time period needed to distract the driver attention from the situation on the road to the navigational system, located in the previously mentioned manner is extremely important, together with the presented information recognition, because during this particular time interval the driver is not able to observe the situation on the road, and, in fact, operates as if being blinded.

The same applies for the operation of mobile phones within hand-free sets or radio-receivers as parts of a conventional arrangement and also for the operation with the buttons and switches, used for the control of the car and cockpit interior functions.

In Fig. 4, the schematic sketch shows to which extent the location of the above mentioned instruments influences the attention of the driver and his/her reaction time.

Fig. 4: The driver’s interaction with a conventionally located navigation display (pink arrow) and a radio set (yellow arrow) as compared with the location of this panel in the left lower corner of the windshield and the respective control elements at the top of the front panel (blue rectangle and green arrows).

Though the proposed attention splitting measurement methodology seems to be practically applicable and will with high probability help to the car designer to receive a considerably objective recommendation for optimization of the position of the selected car interior control tool, many open problems remain.

These concern not only the influence of the

- location, type, shape and color of other car cockpit interior tools, but also the

- proper choise of the proband set (using the results of the analysis of the anamneses questionnaires) and

- further refinement of the determination methods. - Also the problem of time (and other independent variables)

dynamics has to be taken into account.

Refferences

[1]…Novák M., Faber J., Votruba Z.:

Neural Network World,

Monography No. 2, Prague 2004

[2]…Faber J., Bouchner P., Hrubeš P., Machan J., Nedoma P., Novák M.: Methods for investigation of driver attention splitting

caused by car cockpit tools

Research Report No. LSS 191/04, CVTU, Prague, 2004