Perceptual and motor strategies of car drivers in regulating speed of

Transcription

EMPIRICAL STUDIES
RECHERCHES EMPIRIQUES
PERCEPTUAL AND MOTOR STRATEGIES
OF CAR DRIVERS IN REGULATING SPEED
OF APPROACH TO A PRECEDING VEHICLE
by M. MESKALI*, I. BARBET*,
S. ESPIÉ** and R. J. BOOTSMA*
RÉSUMÉ
STRATÉGIES PERCEPTIVO-MOTRICES UTILISÉES PAR LES CONDUCTEURS D’AUTOMOBILES EN VUE DE RÉGULER LA VITESSE D’APPROCHE VERS UN AUTRE VÉHICULE
L’objectif de ce travail était d’identifier les stratégies perceptivo-motrices utilisées par les conducteurs d’automobiles en vue de réguler la vitesse d’approche
vers un autre véhicule et ainsi d’éviter une collision. Afin d’évaluer l’influence de
l’expérience de conduite, deux groupes de participants étaient testés. Le premier
groupe était formé de 13 conducteurs ayant moins de trois ans d’expérience de
conduite (âge moyen 20,5 ans) et le deuxième était formé de 13 conducteurs
ayant plus de cinq ans d’expérience de conduite (âge moyen 26,5 ans). Tous les
participants étaient testés sur un simulateur à base fixe (INRETS SIM2), dans
16 conditions expérimentales différentes, combinant différentes vitesses initiales et
différentes vitesses d’obstacle. Dans chaque condition, le conducteur démarrait
sur une portion vide d’une route à deux voies et accélérait pour atteindre une
vitesse cible (60, 80, 100 ou 120 km/h). Juste avant d’atteindre la vitesse cible,
un autre véhicule, servant de masque, dépassait le conducteur, se plaçait à une
distance de 2 s devant sur la voie de droite et adoptait la même vitesse. Après
une période variable, le véhicule masque changeait de voie, dévoilant ainsi le
véhicule obstacle (positionné à une distance d’arrêt du véhicule masque). Ce
véhicule obstacle roulait à une vitesse égale à 100%, 67%, 33% ou 0% (véhicule arrêté) de celle du conducteur, créant ainsi des situations allant d’une
absence de danger (obstacle à la même vitesse) jusqu’aux situations présentant
un danger imminent (obstacle immobile).
Dans une première série d’analyses, les effets des différentes conditions expérimentales sur la distance parcourue, l’interdistance et le temps nécessaire pour
** UMR Mouvement and Perception, CNRS et Université de la Méditerranée, Marseille,
France.
Corresponding author: R. J. Bootsma. E-mail address: [email protected].
** MSIS-CIR, INRETS, Arcueil, France.
Le Travail Humain, tome 69, no 2/2006, 183-207
184
M. Meskali, I. Barbet, S. Espié, R. J. Bootsma
atteindre une vitesse d’approche nulle ont été examinés. Une deuxième série
d’analyses porte sur les stratégies utilisées par les conducteurs (freinage moteur
par changement de rapport de boîte de vitesse, freinage actif) pour réduire leur
vitesse d’approche, en fonction de l’information visuelle disponible.
Globalement, les conducteurs débutants et confirmés exhibent des comportements similaires, à la fois fonctionnels (permettant d’éviter la collision) et adaptés à la situation, avec plus d’actions effectuées plus rapidement pour les situations les plus urgentes. Variant leur stratégie de façon systématique avec le degré
d’urgence, les conducteurs ont recours au freinage moteur et/ou au freinage actif
par dépression de la pédale de frein. Dans les situations critiques, les conducteurs
initient les appuis de frein après un temps qui dépend à la fois de l’interdistance
et de la vitesse d’approche. L’analyse de la durée des appuis de frein révèle que le
processus de freinage semble dépendre d’une relation complexe entre la distance
intervéhiculaire et la vitesse d’approche. Les actions de freinage concordent de
façon systématique avec l’information contenue dans le pattern d’expansion de
l’obstacle (c’est-à-dire t et son taux de changement par rapport au temps, ß),
soulignant le rôle de la dynamique de l’information visuelle dans la régulation de
la vitesse d’approche.
Dans le but de garantir à la fois une distance suffisante et une vitesse
d’approche minimale et ainsi d’éviter le risque de collision, les conducteurs semblent s’appuyer sur les patterns informatifs contenus dans le flux optique généré
par l’évolution de la distance intervéhiculaire et de la vitesse d’approche pour
réguler la vitesse de leur véhicule. Les moyens mis en œuvre pour décélérer (frein
moteur, nombre et durée d’appuis de frein) sont liés à l’urgence perçue.
INTRODUCTION
When a car driver approaches another vehicle that is moving at a lower
speed in the same lane (s)he must either engage a manœuvre to pass the
vehicle or reduce speed. The latter can be effected by various means. To
decelerate, the driver may simply remove the foot from the accelerator
pedal. Without energy being injected, the dissipative forces originating
from the flow of air around the car and the mechanical functioning of the
motor will gently reduce the car’s speed. In order to increase the degree of
engine braking, the driver may also downshift the gearbox. Finally, by
using the footbrake pedal a more powerful deceleration can be obtained.
Choosing to use one (or a combination) of the above alternatives, in order
to reduce speed sufficiently in the time span available, implies that the driver must correctly understand and anticipate the situation. Such anticipation is based on the use of visual information, informative of the current
state of affairs and the way in which the situation evolves over time.
In his seminal work on the visual regulation of deceleration in car driving, Lee (1976) proceeded by first analyzing the visual information available. He identified two pertinent optic variables. The first of these, denoted t (tau), specifies the time remaining until collision, if the current
speed of approach were to be maintained (that is, if no deceleration intervened). During head-on approach the optic variable t –defined as the
Perceptual and motor strategies of car drivers in regulating speed
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inverse of the rate of dilation of optic angle j, subtended at the point of
observation by the obstacle– corresponds to the ratio of current distance Z
over current approach velocity –dZ/dt=–þ. This ratio of Z over –þ is equal
to the time remaining until contact, better known in the driving literature
as Time To Contact (TTC). Thus, formally, t(j)=j/÷=–Z/þ=TTC.
Later work demonstrated that the optic flow also contained information relative to the time interval until collision during lateral or oblique
approaches (Bootsma & Craig, 2002; Bootsma & Oudejans, 1993). Since
the identification of such a potentially useful optic variable (i.e., t), its use
in the control of movement has been explored in a large number of studies. Sensitivity of human observers to this informational variable has
been clearly established (Bootsma & Craig, 2002; Cavallo & Laurent,
1988; Cavallo, Mestre, & Berthelon, 1997; McLeod & Ross, 1983; Schiff
& Detwiler, 1979; Todd, 1981). However, there is still debate on the way
in which the information carried in the optic variable t is incorporated
into action (Bardy & Warren, 1997; Bootsma, Fayt, Zaal, & Laurent
1997; Peper, Bootsma, Mestre, & Bakker, 1994; Tresilian, 1997; Wann,
1996; Zaal, Bootsma, & Van Wieringen, 1998). Recently, Treffner, Barret, and Peterson (2002) revived the debate, arguing in favour of a critical
value of TTC at which drivers would initiate braking, as had originally
been proposed by Lee (1976). Thus, the hypothesis that a particular
action (such as braking) would be initiated when TTC (as specified by t)
reaches some threshold is still under debate.
However this may be, it is clear that the optic variable t specifies a
(particularly useful) time interval but does not specify the amount of braking needed to avoid collision. Thus, by itself, the variable t is not sufficiently informative for the regulation of braking. However, as pointed out
by Lee (1976), the rate of change of t over time (an optic variable denoted
tau-dot ß) contains the necessary information. For a current inter-vehicle
distance Z and a current approach speed –þ, the minimal deceleration
required to avoid an upcoming collision is given by ÿ=þ2/2Z. If t specifies –Z/þ, then ß, by definition, specifies (Zÿ/þ2)–1. Substituting the
required minimal deceleration, it becomes clear that for a constant deceleration such that the speed of approach becomes zero exactly at the point
of contact (ÿ=þ2/2Z), ß=–0.5. It is also clear that the current deceleration
is insufficient when ß<–0.5 (approach speed will not reach zero before
impact with the obstacle: ÿ<þ2/2Z), and that it is excessive when ß>–0.5
(approach speed will become zero before distance becomes zero:
ÿ>þ2/2Z). Thus, during approach, collision avoidance is pre-specified by
ß>–0.5, gentle contact by ß=–0.5 and upcoming collision by ß<–0.5. As
the information carried in ß is based on the premise that current deceleration be maintained, changing deceleration can alter the present state of
affairs. The effects of such a change lead to a change in the value of ß, allowing evaluation of adequacy of the operation. Observer sensitivity to the
optic variable ß has been addressed by Kim, Turvey, and Carello (1993),
Andersen, Cisneros, Atchley, and Saidpour (1999) and Bootsma and
Craig (2003). The latter authors evaluated the sensitivity of observers in
situations with (sufficient and insufficient) constant and varying deceleration and showed that, in both situations, perceptual judgments of collision
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danger were to a large extent based on ß. The contribution by Barbet,
Meskali, Berthelon, Mottet, and Bootsma (in press) provides a discussion
of observer sensitivity to the optic variable ß in the framework of car driving, for participants with different degrees of driving experience.
The visual regulation of deceleration has been studied in a variety of
different settings. In order to maximise experimental control, authors
such as Yilmaz and Warren (1995) and Fajen (2005) have used simulated
approaches with participants regulating deceleration through a hand-held
interface (spring-loaded mouse or joystick). Attempting to render the task
more ecologically valid, authors like Boer, Yamamura, Kuge, and Girshick (2000) and Treffner, Barrett, and Peterson (2002), on the other
hand, have studied braking while driving a real car. In order to guarantee
driver safety, these latter studies have used tasks in which deceleration was
to be controlled relative to a designated position or a mock-up vehicle. As
suggested by Loomis, Blascovich, and Beal (1999), using a simulator can
allow sufficient experimental control in a task with a degree of ecological
validity determined by the quality of the simulator.
The analysis leading to the identification of the t and ß as informative
(and thus potentially useful) optic variables suggests that the pertinent
variables of the environment-agent system are situated at the level of the
relative motion between the driver’s car and the preceding vehicle. In the
present contribution we therefore examined the behaviour of drivers
(with different degrees of driving experience) when closing in on slower
moving vehicles, without a possibility for passing. In particular, the goal
was to study the drivers’ perceptuo-motor strategies in the regulation of
their approach speed and the role played by the optic variables t (specifying the time remaining until contact) and ß (the rate of change of t over
time, specifying the sufficiency of current deceleration). While the
increased risk of being involved in an accident with bodily harm of
novice drivers (Cerreli, 1992) is of a multi-factorial nature, evaluation of
fundamental perceptual (Barbet et al., in press) and perceptuo-motor
skills (this contribution) involved in driving may serve to complement
accidentological studies. Thus, in order to evaluate whether there is an
effect of driving experience on the perceptuo-motor behaviour of drivers
during approach to a preceding vehicle, we studied novice and experienced drivers. The work was conducted on a fixed-base simulator and limited to situations of head-on approach on a rectilinear road with normal
visibility and adherence.
MATERIAL AND METHODS
Two groups of subjects participated in the study. The first group, referred to hereafter as the “novice” group, consisted of 13 participants, with an
average age of 20.5 years (SD=1.1) having obtained their drivers’ licence
less than 3 years ago. These recently qualified drivers had accumulated
between 2,000 and 57,000 km of driving experience. The second group,
with an average age of 26.5 years (SD=2.9), consisted of 13 experienced
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drivers, having obtained their licence more than five years ago and having
cumulated between 22,000 and 275,000 km. All participants had a normal
or corrected-to-normal vision and drove regularly.
The experiments were carried out on a fixed-base simulator SIM2INRETS coupled to an object data base ARCHISIM. The simulator consisted
of a cockpit equipped with all the characteristics of a standard car (car
seat, gearbox, accelerator, clutch and footbrake pedals, a dashboard with
a speedometer, etc.). A dedicated PC organised the various tasks of piloting the simulator, signal acquisition, sound restitution and scenario displays. A video-projector (Nec VT660) projected the images, generated at a
frequency of 30 Hz, onto a screen (H: 49o; V: 37o) located at a distance of
1.90 m in front of the driver’s eyes; the screen centre was located at the
driver’s eye height (1.38 m above the ground). Acquisition frequency for
the various signals (position, speed, acceleration, pedals, gearbox, etc.)
was 30 Hz.
The experimental protocol was based on a rectilinear two-lane road
with normal visibility conditions. Driving along this road, participants
were confronted with situations involving a potential risk of collision at
various degrees of emergency. Each participant was confronted with
16 different scenarios (see Table 1), combining four different initial
speeds of the controlled vehicle and four speeds of the obstacle vehicle.
For each scenario (or condition; see example in Figure 1), the driver controlling the vehicle (simulator) was placed on an empty stretch of road
and instructed to reach a particular target speed V (60, 80, 100 or
120 km/h). Just before reaching the instructed speed, a second vehicle
(serving as a mask) overtook the driver, placed itself in the right lane in
front of the controlled vehicle at a distance of 2 s (33, 44, 56 or 67 m, respectively) and then continued to move at the driver speed V. After the target speed was reached and maintained for a variable time period (4, 6, 8
or 10 s), the mask vehicle changed lane, revealing a third vehicle (the obstacle vehicle) placed in the right lane at a distance corresponding to the
theoretical stopping distance (27, 50, 77 and 111 m, respectively) in front
of the mask vehicle and moving at a speed equal to 100, 67, 33 or 0% of
that of the controlled vehicle. After the lane change, revealing the obstacle
vehicle to the driver, the mask vehicle continued to move in the left lane at
the speed of the obstacle vehicle. Thus, with the two vehicles occupying
both lanes, the driver could not overtake the obstacle vehicle.
For each of the 16 scenarios, the moment that the mask vehicle changed lane, and thereby revealed the obstacle vehicle, constituted the onset
of the section to be analysed. At this moment, the driver was confronted
with one of four situations:
i) a situation without danger, where the obstacle vehicle moved at the
same speed as the controlled vehicle (scenarios V→1V). Correct perception of this situation allows the driver to continue to move at the instructed speed.
ii) a potentially dangerous situation where the obstacle vehicle moved
at two-thirds of the speed of the controlled vehicle (scenarios V→2/3V).
The driver should perceive that (s)he is closing in on the preceding vehicle
and decelerate so as to maintain a sufficiently safe distance.
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TABLE 1
Table presenting the 16 experimental conditions combining 4 driver speeds
V and 4 scenario types as fonction of the obstacle speed (V→1V, V→2/3V, V→1/3V
and V→0V). For a given driver speed, the 4 scenario types created situations ranging
from no danger (V→1V) to imminent danger (V→0V). For each experimental
condition, the number of repetitions (between brackets) during an experimental session
is provided
Tableau représentant les 16 conditions expérimentales combinant 4 vitesses V
du conducteur et 4 types de scénario (V→1V, V→2/3V, V→1/3V et V→0V),
fonction de la vitesse de l’obstacle. Pour une vitesse donnée du conducteur,
les 4 types de scénarios créent ainsi 4 situations allant d’une absence du danger
(V→1V) jusqu’aux situations présentant un danger imminent (V→0V).
Pour chaque condition expérimentale, nous avons donné le nombre
de répétitions (entre parenthèses) au cours d’une session expérimentale
V
V→1V
(20 trials)
V→2/3V
(8 trials)
V→1/3V
(8 trials)
V→0V
(4 trials)
60 km/h
80 km/h
100 km/h
120 km/h
60→60 (5)
80→80 (5)
100→100 (5)
120→120 (5)
60→40 (2)
80→53.33 (2)
100→66.66 (2)
120→80 (2)
60→20 (2)
80→26.66 (2)
100→33.33 (2)
120→40 (2)
60→0 (1)
80→0 (1)
100→0 (1)
120→0 (1)
iii) a dangerous situation where the obstacle vehicle moved at onethird of the speed of the controlled vehicle (scenarios V→1/3V). The driver should perceive that (s)he is rapidly closing in on the preceding vehicle
and decelerate so as to maintain a safe distance.
iv) a critical situation where the obstacle vehicle was not moving (scenarios V→0V). As overtaking is not possible, the driver must bring the
controlled vehicle to a stop before reaching the obstacle. If the driver has a
sufficiently rapid and accurate perception of the situation, it is still possible to avoid collision.
The protocol with the 16 situations described above was designed to
study how drivers deal with situations that can but need not lead to collisions. The inter-vehicle distances and speeds were chosen so that when
the drivers appropriately executed the required manœuvres, they could
under all circumstances avoid collision.
In order to minimize driver anticipation of critical situations, a total
of 40 trials were run, presented in a random order. Half of the 40 trials
were V→1V scenarios (5 repetitions for each of the 4 initial speeds V:
20 trials), 20% were V→2/3V scenarios (2 repetitions for each V:
8 trials), 20% were V→1/3V scenarios (2 repetitions for each V: 8 trials)
and 10% were V→0V scenarios (1 repetition per V: 4 trials). The duration of a trial was about one minute. The 40 trials were run in two sessions (2 blocks of 20 trials each) separated by a five-minute break. The
two experimental sessions were preceded by a training session of 12 trials
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Fig. 1. — Snapshots from an example scenario in which the driver is instructed to reach 100 km/h and the
obstacle vehicle is not moving (a V→0V scenario). Upper left panel (1): just before reaching the target speed, the
mask vehicle overtakes the driver. Upper right panel (2): the mask vehicle places itself in the right lane at the
distance of 2 s ahead of the driver and then continues to move at the driver speed. Lower left panel (3): After
having attained the target speed (100 km/h) and maintained it for a certain time, the mask vehicle changes lanes,
revealing the obstacle vehicle at stopping distance in front of the mask vehicle. Lower right panel (4): with the
mask and obstacle vehicles occupying both lanes, the driver cannot overtake the obstacle vehicle and needs to
bring the controlled vehicle to a full stop.
Suite de scènes tirée d’un scénario exemple dans lequel le conducteur doit atteindre une vitesse cible de 100 km/h et le
véhicule obstacle est arrêté (un V→0V scénario). (1) Peu avant l’atteinte de la vitesse cible, le véhicule masque dépasse le
conducteur. (2) Le véhicule masque se place dans la voie de droite à une distance de 2 s et prend la vitesse du conducteur.
(3) Après avoir atteint la vitesse cible et l’avoir maintenue pendant un certain temps, le véhicule masque déboîte, révélant
le véhicule obstacle, sur la voie de droite à une distance de freinage du véhicule masque. (4) Avec les véhicules masque et
obstacle occupant les deux voies, le conducteur ne peut pas éviter le véhicule obstacle en le dépassant et doit donc réduire sa
vitesse à zéro.
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(12 minutes duration) drawn randomly among the 40 scenarios. The
total duration of the experiment was thus approximately an hour. The
training session served to familiarise drivers with the equipment and the
scenarios that could be encountered.
DATA
ANALYSIS
Data processing routines and algorithms were designed using Matlab.
To study driver strategies and particularly the various events involved in
the regulation of inter-vehicle distance and collision avoidance, we first
defined the beginning and the end of the pertinent perceptuo-motor section for all scenarios (Figure 2).
— The effective start (t0 ) was defined as the moment that the
driver of the controlled vehicle moving at a speed V was first
confronted the obstacle vehicle, that is when the mask vehicle changed
lanes.
— The end of the perceptuo-motor section (tf) was defined as the
moment that the driver of the controlled vehicle reached the speed of the
obstacle vehicle (cases of V→2/3V, V→1/3V and V→0V). Because for the
V→1V control scenarios this was the case from the start, in these conditions the end of the perceptuo-motor section coincided with the end of
the scenario, that is after one minute.
On the basis of the distance, speed, and deceleration time-series, we
determined for each manœuvre a series of parameters with respect to
over-ground distance travelled, inter-vehicle distance, approach speed
and manœuvre time. Figure 2 shows the inter-vehicle distance (distance
separating the controlled and obstacle vehicles) at t0(IVD0 ), at tf(IVDf)
and at the moment of foot brake initiation (IVDi). Also shown is the
approach speed (relative velocity or speed difference between controlled
and obstacle vehicles) at t0(RV0 ), at tf(RVf) and at the moment of brake
initiation (RVi). Note that for the V→2/3V, V→1/3V and V→0V scenarios, the approach speed at time tf (i.e., RVf) is equal to zero (tf being
defined as the moment that controlled vehicle speed is equal to that of
obstacle vehicle). When participants used the foot brake, it was almost
always depressed completely, probably due to the lack of vestibular and
somesthetic stimulation inherent to the use of a fixed-base simulator.
Thus, in the analyses we concentrated on the duration of braking, rather
than on its (practically invariant) intensity. The ti parameter corresponds
to time of activation of the foot brake pedal (FBP). We calculated the
duration of each foot brake pedal depression in order to calculate total
duration T of all depressions; in the example of Figure 2, the total duration of the 3 depressions (FBP1, FBP2 and FBP3) is T=T1+T2+T3.
Finally, Figure 2 presents the evolution over time of the two optic variables (t and ß), calculated from the relevant parameters of inter-vehicle
distance, approach speed and deceleration between the controlled and
obstacle vehicles. Durations are expressed in seconds (s), distances in
meters (m), speed in meter per second (m/s) and deceleration in meter
per second squared (m/s2).
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Fig. 2. — Example of the evolution over time of the signals recorded during a V→0V scenario
(with V=120 km/h). The upper panel shows the over-ground distance travelled by the driver and the
obstacle vehicle (not moving). The second panel shows their respective speeds. The third panel
shows the deceleration of the controlled vehicle, together with the state of the accelerator pedal, the
gearbox (GB5 to GB2), the footbrake pedal (activated three times in this example, FBP1, FBP2 and
FBP3) and the respective durations of those activations (T1, T2 and T3). The lower panel shows the
evolution of the optic variables t (tau) and ß (tau-dot) over time. The initiation of braking (ti), the
start (t0) and the end (tf) of the manœuvre are indicated by vertical dashed lines. The inter-vehicle
distances (IVD0, IVDi, IVDf) and relative speeds (RV0, RVi, RVf) measured respectively at t0, ti and tf
are indicated by arrows.
Exemple de signaux enregistrés pour un scénario V→0V (avec V=120 km/h). Le premier graphique
représente les distances parcourues des véhicules piloté (conducteur) et obstacle (arrêté) et le deuxième leurs
vitesses. Le troisième graphique représente la décélération du véhicule, avec l’état de l’accélérateur, de la
boîte à vitesse (GB5 à GB2), de la pédale de frein (trois activations dans cet exemple, FBP1, FBP2 et
FBP3) ainsi que la durée respective de chaque activation (T1, T2 et T3). Le moment d’initiation de
frein (ti) ainsi que le début (t0) et la fin (tf) de la manœuvre de décélération sont indiqués par des tirets
verticaux. Les distances intervéhiculaires (IVD0, IVDi, IVDf) et les vitesses d’approche (RV0, RVi, RVf)
mesurées respectivement à t0, ti et tf sont indiquées par des flèches.
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RESULTS
We recall that the different scenarios were designed in such manner
that a collision could be avoided, although some scenarios required vigorous intervention. Two novice drivers were unable to avoid a collision on
one occasion and one experienced driver collided twice with the obstacle.
All four collisions were produced in a V→0V scenario. With two groups of
13 participants each and four different V→0V scenarios, collisions thus
constituted 3.8% of the V→0V trials and 0.4% of all trials. These collision
trials were excluded from further analysis.
We began by analyzing the effect of collision risk on the overground distance travelled until safety, on the final inter-vehicle distance
and on manœuvre duration. We then analysed deceleration strategies
based on engine braking by downshifting the speed ratio of the gearbox
and on use of the footbrake pedal. We continued to analyse the times ti
and TTCi (specified by the optic variable t) at the moment of initiation of
the first depression. Finally, we analyzed the total duration T of the
brake depressions, before examining the role of played by the optic
variable ß.
DISTANCE
TRAVELLED, INTER-VEHICLE DISTANCE
AND MANŒUVRE DURATION
Figure 3 presents, for each initial speed V of controlled vehicle, the
over-ground distance travelled until the speed of controlled vehicle was
equal to the speed of obstacle vehicle, the inter-vehicle distance when
such equal speed was reached and the duration of the manœuvre.
To analyse the effect of collision risk on these different variables, we
used ANOVAs with factors Group (2 levels; novice and experienced), Controlled Vehicle Speed (4 levels: V 60, 80, 100 and 120 km/h), and Scenario Type (3 levels: V→2/3V, V→1/3V and V→0V), with repeated measures on the last two factors.
The ANOVA on distance travelled showed significant main effects for the
factors Controlled Vehicle Speed (F(3,63)=318, p<.001) and Scenario
Type (F(2,42)=116, p<.001), as well as a significant interaction between
the two (F(6,126)=35, p<.001). No significant effects related to the factor
Group were observed. The ANOVA on final inter-vehicle distance revealed
significant main effects of Controlled Vehicle Speed (F(3,63)=63, p<.001)
and Scenario Type (F(2,42)=122, p<.001) and a significant interaction
between these two factors (F(6,126)=33, p<.001). Again, no significant
effects related to the factor Group were observed. The ANOVA on manœuvre duration revealed the same pattern, with significant main effects of
Controlled Vehicle Speed (F(3,63)=125, p<.001) and Scenario Type
(F(2,42)=42, p<.001), as well as a significant interaction of the two
(F(6,126)=5, p<.001). The factor Group did not give rise to any significant
effects.
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Fig. 3. — Over-ground distance travelled (left column) and inter-vehicle distance at tf (right
column) for each of the three potential collision scenarios at each of the four initial speeds. Data
for experienced drivers are in filled symbols and data for novice drivers in open symbols. Error bars
represent interindividual variability.
Distances parcourues (colonne de gauche) et distances intervéhiculaires à tf (colonne de droite) pour
chacun des trois scénarios à collision potentielle et pour chacune des quatre vitesses initiales. Les données
pour les conducteurs expérimentés sont représentées par des symboles pleins et les données pour les
conducteurs novices par des symboles vides. Les barres d’erreur représentent la variabilité interindividuelle.
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As can be seen in Figure 3 and as demonstrated by post-hoc analyses
of the interactions, all three variables decreased as a function of both the
speed V of the controlled vehicle and the speed of the obstacle vehicle.
The drivers’ behaviour thus closely depended on the degree of emergency
of the situation, with drivers taking less time and travelling a shorter distance when reducing their speed to that of the obstacle vehicle in more
risky situations. Inspection of Figure 3, together with the lack of significant effects involving the factor Group, suggests that this pattern was
quite similar for the two groups of drivers.
BRAKING
STRATEGIES
Dependent on the degree of risk of future collision, drivers used
various combinations of engine braking by downshifting the speed ratio of
the gearbox and foot braking by depression of the footbrake pedal.
For both groups, the number of gearbox changes systematically varied
with the type of scenario (c2(9)=43, p<.001 for novices and c2(9)=30,
p<.001 for experienced drivers). For each scenario, we compared (c2 test)
the number of gearbox changes of novice drivers with that of experienced
drivers. Using this procedure, no effect of driving experience on the number
of gearbox changes could be demonstrated. Drivers did not change gears for
V→1V scenarios. In general, they down geared once for V→2/3V scenarios,
and twice for V→1/3V scenarios. In critical situations (V→0V scenario)
either they did not touch the gearbox at all or they down geared several times.
For both groups, the number of times the foot brake pedal was depressed also systematically varied with the type of scenario (c2(9)=53, p<.001
for novices and c2(9)=54, p<.001 for experienced drivers). As for gearbox
changes, no difference between groups could be demonstrated for the
number of times that the footbrake was used (c2 test). For V→1V scenarios drivers did not touch the footbrake pedal. For V→2/3V scenarios, the
footbrake was used occasionally, the deceleration obtained by engine braking mostly being sufficient. In V→1/3V scenarios drivers often used a
single depression of the footbrake, while in the critical V→0V scenarios
the footbrake was activated several times.
To summarize, novice and experienced drivers seemed to use comparable strategies for braking. The V→1V scenarios that did not require any
deceleration indeed gave rise to a total absence of engine or foot pedal braking. For V→2/3V scenarios, a single change in gearbox gave rise to sufficient engine brake and drivers generally did not need to press the footbrake
pedal. For V→1/3V scenarios, drivers increased the amount of engine braking with two or more consecutive gear changes combined with a single
footbrake activation. Finally in the most critical situations (V→0V scenarios), engine braking was totally abandoned by some drivers and the foot
pedal brake was actively used by all, most often with successive bouts of
activation.
The present analysis revealed that use of the footbrake pedal is quite
specific to the more critical situations (V→1/3V and V→0V). Analysing
Temps ti écoulé (en haut) et TTC (en bas) au moment d’initiation de la première activation de frein pour les scénarios V→1/3V et V→0V en fonction de la distance
intervéhiculaire (IVD0) et de la vitesse d’approche (RV0) chez les conducteurs novices et expérimentés. Les surfaces représentent l’équation de la régression multiple.
Fig. 4. — Time after onset ti (upper panels) and TTC (lower panels) at the moment of first foot brake pedal activation for V→1/3V and V→0V scenarios as a
fimction of inter-vehicle distance (IVD0) and relative speed (RV0) for novice and experienced drivers. The surface depicted in each graph represents the multiple
regession equation.
196
these latter situations in more detail, we studied i) the moment ti at which
the first footbrake action began; ii) the value of TTC at that moment;
iii) the total duration of foot pedal braking T; and iv) the value of the optic
variable t before, during and after each brake activation.
In order to examine the influence of approach speed and inter-vehicle
distance on the initiation of footbrake activation, we used multiple linear
regression to fit a model of the form p=a+b . IVD+c . RV, with p the studied
variable (ti, TTCi or T), IVD the inter-vehicle distance (IVD0 or IVDi) and RV
the approach speed (RV0 or RVi); a, b and c are coefficients to be determined
by multiple linear regression analysis. From the regression equations,
we calculated the effective contributions of the two components (intervehicle distance and approach speed) on the evolution of each particular
variable.
The results of this procedure for the variables ti, TTCi and T were
comparable, whether they were taken with respect to the initial conditions
(IVD0, RV0) or with respect to the situation at the moment of first footbrake activation (IDVi, RVi). Figure 4 depicts the co-variation of IVD0 and
RV0 for the time elapsed until brake initiation (ti) and for the time remaining until collision at that moment (TTCi); the evolution of T is similar
and is not presented in the figure. Statistical analyses and results are
reported for both.
TIME
AND
TTC
AT FIRST FOOTBRAKE ACTIVATION
Table 2 presents the statistical details for the linear regressions. The
time elapsed since the preceding vehicle became visible (ti) was found to
be systematically related to IVD and RV (0.89≤R2≤0.99). For the experienced drivers, the effective contributions of IVD and RV were 61% and
39%, respectively. For the novice drivers, the effective contributions were
58-59% and 41-42%, respectively. Summarising the above, the linear
regression models established for novice and experienced drivers demonstrated that the time (after first vision of obstacle vehicle) at which the footbrake was first activated was a systematic function of both inter-vehicle
distance and relative speed. The initiation time for a null inter-vehicle distance and approach speed was approximately 2 s; this time increased with
an increase in inter-vehicle distance and a decrease in approach speed,
with a ratio of about 0.6 for the inter-vehicle distance and about 0.4 for
approach speed. These results could be taken to suggest that drivers use
information about inter-vehicle distance and approach speed, incorporated into the decisional process with a somewhat different weighing, to
decide when to initiate braking. It should, however, be remembered that
this analysis pertains to the time elapsed since the driver first saw the obstacle vehicle and it would seem unlikely that a weighted combination of
perceived inter-vehicle distance and approach speed would influence the
duration of the time during which the driver was preparing to activate the
footbrake. Rather than reasoning from the start of the scenario, it seems
more pertinent to reason in terms of the temporal proximity of potential
Novice
Experienced
Novice
Experienced
Novice
Experienced
Novice
Experienced
Novice
Experienced
Novice
Experienced
Novice
Experienced
Novice
Experienced
ti(IVD0, RV0)
[ln(T)] [ln(IVDi), ln(RVi)]
[ln(T)] [ln(IVD0), ln(RV0)]
T(IVDi, RVi)
T(IVD0, RV0)
TTCi(IVDi, RVi)
TTCi(IVD0, RV0)
ti(IVDi, RVi)
Drivers
Parameters
ti=2.20+0.03 IVD0–0.13 RV0
ti=2.52+0.03 IVD0–0.14 RV0
ti=1.85+0.05 IVDi–0.12 RVi
ti=1.97+0.05 IVDi–0.12 RVi
TTCi=3.56+0.03 IVD0–0.17 RV0
TTCi=3.90+0.03 IVD0–0.18 RV0
TTCi=3.11+0.05 IVDi–0.17 RVi
TTCi=3.19+0.05 IVDi–0.16 RVi
T=–0.47–0.01 IVD0+0.23 RV0
T=–0.60–0.01 IVD0+0.23 RV0
T=–0.17–0.02 IVDi+0.21 RVi
T=0.01–0.02 IVDi+0.20 RVi
ln(T)=–1.57–0.52ln(IVD0)+1.65ln(RV0)
ln(T)=–1.97–0.56ln(IVD0)+1.84ln(RV0)
ln(T)=–1.61–0.39ln(IVDi)+1.42ln(RVi)
ln(T)=–1.50–0.42ln(IVDi)+1.42ln(RVi)
Linear regressions
61–39
59–41
61–39
58–42
56–44
54–46
56–44
54–46
31–69
30–70
25–75
24–76
R2=0.99,
R2=0.97,
R2=0.94,
R2=0.89,
R2=0.94,
R2=0.94,
R2=0.99,
R2=0.98,
R2=0.99,
R2=0.99,
R2=0.99,
R2=0.98,
R2=0.97,
R2=0.99,
R2=0.97,
R2=0.97,
Respective
contributions
(percent) Statistics
F(2,5)=173, p<.001
F(2,5)=84, p<.001
F(2,5)=41, p<.001
F(2,5)=21, p<.001
F(2,5)=40, p<.001
F(2,5)=40, p<.001
F(2,5)=238, p<.001
F(2,5)=129, p<.001
F(2,5)=454, p<.001
F(2,5)=200, p<.001
F(2,5)=402, p<.001
F(2,5)=105, p<.001
F(2,5)=91, p<.001
F(2,5)=295, p<.001
F(2,5)=89, p<.001
F(2,5)=92, p<.001
Résultats des régressions linéaires multiples du temps écoulé jusqu’au moment de l’initiation de frein ti le temps restant jusqu’à la
collision au même moment TTC, le temps total de freinage T et ln(T), chez les conducteurs novices et expérimentés. Pour chaque
variable, l’équation de régression a été étudiée en fonction des conditions initiales (IVD0, RV0), et en fonction des conditions au
moment de l’activation de frein (IVDi, RVi)
Multiple linear regression results for time elapsed until first foot brake pedal activation ti, the remaining until collision at this moment TTC, total
duration of braking T and ln(T), for novice and experienced drivers separately. For each variable, regression results are provided with respect
to the initial conditions (IVD0 and RV0) and with respect to the conditions at the moment of foot brake pedal activation (IVDi and RVi)
TABLE 2
198
collision. Information with respect to the latter is available through the
optic variable t, specifying Time To Contact (TTC).
As was done for ti, the dependence of TTCi (as specified by the optic
variable t) at the moment of onset of footbrake activation on inter-vehicle
distance and approach speed was evaluated using multiple linear regression. As can be seen from Table 2, TTCi was found to vary systematically
with IVD and RV (0.94≤R2≤0.99) for both groups of drivers. Whether
taken with respect to the initial conditions or with respect to the conditions at the onset of braking, the analyses revealed effective contributions
of IVD and RV of 56% and 44%, respectively, for the novice drivers, and
54% and 46%, respectively, for the experienced drivers.
As expected, the value of TTCi at the moment of first footbrake activation was found to depend at the same time on inter-vehicle distance and
approach speed. However, the relation identified did not result in a constant value of TTCi for all combinations of inter-vehicle distance and
approach speed. For a null inter-vehicle distance and approach speed, the
estimated TTCi value at the brake initiation was slightly above 3 s, whereas it should have been equal to zero according to the constant threshold
hypothesis. It is clear that additional information was taken into account
in determining the moment at which the footbrake was to be activated.
TOTAL
DURATION OF FOOTBRAKE ACTIVATION
As shown above, there are systematic relations between the time after
first vision of the obstacle or the time remaining until collision (TTC specified by t) at brake initiation, on the one hand, and the two variables of
inter-vehicle distance and approach speed, on the other hand. In order to
better understand the origin of these relations, we analyzed the total duration of footbrake activation as a function of inter-vehicle distance and
approach speed. This total duration T, resulting for one or more footbrake
activations, was analyzed for the scenarios with an elevated risk of collision (V→1/3V and V→0V). As can be seen from Table 2, the total duration of braking was systematically related to IVD and RV (0.98≤R2≤0.99).
For both novices and experienced drivers, the effective contributions
of IDV and RV were about 30% and 70%, respectively, when analysed
with respect to the initial conditions and 25% and 75%, respectively,
when analysed with respect to the conditions at the moment of brake initiation. Thus, the contribution of the RV to the total braking duration was
considerably larger than that of IDV: a larger approach speed gave rise to
more braking than a proportionally equally reduction in inter-vehicle
distance.
Recalling that the required minimal deceleration necessary to avoid
collision is related to inter-vehicle distance and the square of approach
speed, we re-analysed total braking duration (T) using a multi-component
power function of the form TT=r . (IVDp . RVq). With a Neperian logarithmic transformation, the procedure becomes a multiple linear regression of
the form ln(T)=ln(r)+p . ln(IVD)+q . ln(RV). Of interest are the p and q
coefficients determining the relative influence of the IVD and RV varia-
199
bles. As can be seen from Table 2, systematic relations between, on the
one hand, total braking duration T and, on the other hand, IVD and RV
were found (0.97≤R2≤0.99). Inter-vehicle distance contributed to total
brake duration with a power exponent of around –0.5, while relative velocity contributed with a power exponent of around 1.5.
TAU-DOT
DURING FOOT PEDAL BRAKING
Above we demonstrated that the total duration of braking depended
more heavily on approach speed than on the inter-vehicle distance. As drivers often used the footbrake several times, we analysed the evolution of
the informative optic variable ß over successive footbrake activations. In
particular, this analysis enabled us to follow the evolution of ß during braking. After all, in the end, the issue addressed in this study is the relation
between the value of ß signalling (in)sufficiency of current deceleration,
the activation of the footbrake and the goal of collision avoidance.
Figure 5 presents the values of ß just before, during and just after each
activation of the footbrake as a function of the (cumulative) duration of
activation, for both novice and experienced drivers, in the critical situations of imminent danger of collision (V→0V scenarios). The analyses
were based on 35 trials with a single footbrake activation (upper panel),
48 trials with two successive footbrake activations (middle panel) and
17 trials with three successive footbrake activations (lower panel). For
each activation of the footbrake pedal, we calculated the mean value of ß
at initiation of the brake depression, the mean value of maximum ß reached during braking and the mean value of ß when the brake was released.
In Figure 5, we report the mean duration for each brake activation and the
cumulative duration for successive activations.
Recalling that the fixed-base simulator does not provide adequate vestibular and somesthetic information with respect to the deceleration
applied, participants were found to operate in an all-or-none mode: when
the footbrake was activated, depression was such that maximal deceleration was rapidly attained. Thus, if collision avoidance was at all possible,
footbrake activation invariably led to a deceleration largely sufficient to
bring the controlled vehicle to a stop before reaching the obstacle. During
braking, ß thus exceeded the critical value of –0.5 by a large degree (see
Figure 5), signalling participants that they could go easier on the brakes.
After releasing the footbrake, the vehicle had either come to a stop, decelerated sufficiently through supplementary engine braking or required
another bout of deceleration with the foot pedal. It is quite remarkable
that, even in the most critical situations, participants more often than not
chose to release the footbrake after an initial first activation, most likely to
allow an intermediate perceptual evaluation of the results obtained thus
far. By alternating between activation of the footbrake and perceptual evaluation of the situation reached, they were able to avoid collision while
minimizing the risk that a vehicle behind them would hit them because of
a too abrupt deceleration.
Fig. 5. — Mean value of magnitude of ß before, during, and after each activation of the
footbrake pedal, for V→0V scenarios, as a function of the mean duration of such activation. For
each mean value ß of a given event (start, plateau or end), the error bars represent variability. On
the abscissa, the mean duration of each activation and the cumulative duration are presented; for a
best dispersion on time axis, we scaled the successive activations on their cumulative durations.
Braking patterns with only one activation (upper panel) last less long than patterns with two
activations (middle panel) which again last less long than patterns with three activations. For
reasons of convenience ß is limited to a maximum of 20. As the last activation was sufficient to
bring the vehicle te a stop, ß after release is net provided.
Valeurs moyennes de ß avant, pendant et après chaque activation de la pédale de frein pour les
scénarios V→0V en fonction de la durée moyenne de l’activation. Pour chaque valeur moyenne de ß d’un
événement donné (avant, durant ou après), nous avons représenté sa variabilité (barres d’erreur). En
abscisse, nous avons reporté la durée moyenne de chaque activation ainsi que la durée cumulative des
activations; pour une meilleure dispersion sur l’axe des abscisses, nous avons placé les activations
successives sur une échelle représentant leur durée cumulée. Les patterns de freinage avec une seule
activation de la pédale (en haut) duraient moins longtemps que les patterns avec deux activations (au
milieu) qui duraient moins longtemps que les patterns avec trois activations (en bas). Pour des raisons de
lisibilité, la valeur maximale de ß est limitée à 20. Parce que la dernière action suffisait pour arrêter le
véhicule, la valeur finale de ß est infinie et non représentée.
201
DISCUSSION
Reducing speed when closing in on a vehicle moving at a lower speed
is a fundamental driving skill, with most drivers remaining unconscious of
the manner in which this complex action is realised. The time span available for the required manœuvres varies with the inter-vehicle distance
and the speed difference. An unnecessarily abrupt deceleration may
expose the driver to rear-end collisions with tailing vehicles. Thus, deceleration should be dosed so as to ensure that upcoming collision with the
preceding vehicle can be avoided without bringing a tailing driver in
difficulty.
Surprisingly, experimental studies on the perceptuo-motor strategies
used in regulating the speed of approach to an obstacle-vehicle are few
and far between. As pointed out by Boer et al. (2000), most work has
concentrated on vehicle-related state variables, rather than on drivercentred informational variables. While the former are typically studied in
the framework of understanding how an accident came to be, the latter
are better studied in the framework of natural behaviour when drivers are
confronted with potentially dangerous situations.
Because in real driving tasks, ethical considerations impose that all
danger for the driver be avoided, studies have typically used approach to a
designated stop line (e.g., Boer et al., 2000; Treffner et al., 2002) or to a
mock-up vehicle (e.g., Boer et al., 2000). Due to these constraints, such
studies have been limited to approach to a full stop. However, situations
involving a stationary obstacle are less frequently encountered during driving than situations involving a more slowly moving preceding vehicle.
Allowing for better experimental control than real driving tasks (Loomis
et al., 1999), driving simulators offer the possibility to confront drivers
with a variety of situations and thereby constitute a potentially powerful
tool for investigating driver behaviour.
Unfortunately, at the present time, simulators are seriously limited in
their capability of reproducing the pattern of stimulation experienced
during real driving. Significant progress has been made with respect to the
richness of visual and auditory stimulation, but problems remain with
reproducing the sensation of physical deceleration, involving not only the
visual system but also the vestibular and somesthetic sensory systems. In
fixed-base simulators, as the one used in the present experiments, taskrelated stimulation of the latter systems is totally absent. Dynamic simulators allowing for the translations of surge, sway, and heave and the rotations of pitch, roll, and tilt have been developed, but simulators must, on
average, remain in the same location and orientation. Because the abovementioned movements are necessarily only of limited range, stimulation
patterns produced by dynamic simulators do not fully correspond to reality. Stoffregen and Bardy (2001) suggested that the relevant information
for an active biological system is contained in the global array, that is in
the overall pattern of stimulation over all pertinent sensory systems. While
the absence of vestibular and somesthic information is quite obvious in
202
fixed-base simulators, the partial (but nevertheless unrealistic) stimulation
provided by dynamic simulators may create more of a problem than providing a better solution (Boer et al., 2000).
In the present study we examined how drivers, piloting a fixed-base
simulator, dealt with situations that varied in their degree of danger of
upcoming collision. Using a protocol involving a mask vehicle that overtook the driver and placed itself at a controlled distance ahead, we were
able to control the moment at which the potential danger of the situation
became perceptually available. With the mask vehicle also eliminating the
possibility of bypassing the obstacle vehicle, we forced participants to
regulate their approach speed when necessary. With no risk existing on
half the trials (V→1V scenarios), biased anticipatory reactions from participants were successfully avoided. Indeed, the results showed that in these
control trials, participants never changed gear and never touched the footbrake pedal. The situations in which they did have recourse to either one
(or both) of these actions can thus be taken to represent voluntary
(although perhaps unconscious) intervention, based on the perceived state
of affairs. With initial speeds of 60, 80, 100 and 120 km/h we examined a
large range of driver speeds. In line with earlier research on braking (Boer
et al., 2000 ; Siegler, Reymond, Kemeny, & Berthoz, 2001; Treffner et al.,
2002), we included a condition with a stationary obstacle, but we extended this protocol to include situations where the obstacle vehicle was
moving at one-third or two-thirds of the participant’s speed.
In line with the results reported by Treffner et al. (2002), braking to a
full stop from higher initial speeds resulted in longer braking distances.
The current results extend these earlier studies by showing that it is the
relative speed difference (between controlled and obstacle vehicles) that
determines the distance travelled until the speed of the preceding vehicle
is attained. Contrary to Treffner et al. (2002), who reported no differences
in the duration of the total braking manœuvre (from braking onset until
stopping the vehicle), our results demonstrate a dependence of manœuvre
duration on the relative speed between controlled and obstacle vehicles,
with larger relative speed being associated with longer manœuvre durations. Similar results were reported by Pinto, Cavallo, Ohlmann, Espié,
and Rogé (2004) on both fixed-base and dynamic-base simulators.
Boer et al. (2000) argued that drivers should be characterised as intermittent satisficing controllers (as opposed to continuous optimising controllers) and that driving should be understood as the process of maintaining a sufficiently large safety (or other driver-need related variable)
margin. Following up on the initial work of Gibson and Crooks (1938),
Lee (1976) also suggested that drivers monitor safety margins and initiate
intervention (such as braking) when a particular perceptual indicator
(notably, t specifying TTC) reached a threshold. Although subsequent
work has failed to provide experimental support in favour of the “initiatean-action-at-threshold” hypothesis (see Wann, 1996, and Bootsma et al.,
1997, for a discussion of these issues), this idea has never been totally abandoned. Indeed, Treffner et al. (2002) recently suggested that the initiation
of braking would occur at a constant value of TTC of about 5 s. Similar
results were reported by Pinto et al. (2004), with a constant TTC of around
203
5.5 s. In both studies, participants were asked to decelerate from a given
initial speed to a stop near a designated target line. In the current study, the
presence of a moving obstacle vehicle allowed using a considerably larger
range of approach conditions and analyses demonstrated that TTC at the
onset of braking was not constant. Regression analyses revealed that a
(theoretical) zero inter-vehicle distance and zero approach speed was associated with a baseline TTC of 3 s. This non-zero intercept indicates that, by
itself, the ratio of inter-vehicle distance over approach speed cannot
account for the moment of brake initiation: The respective weights of these
two constituent variables are not exactly equal to 50%. Similar results were
obtained by Grosz et al. (1995) in a study of landing an aircraft under
varying ILS (International Landing System) approach angles. The idea that
an action such as braking is initiated when TTC falls under a certain, fixed
threshold is simply too simplistic (Bootsma et al., 1997). This being said, it
is important to remember that TTC at onset of braking is nevertheless systematically related to inter-vehicle distance and approach speed (Figure 5),
indicating that the perceptual variable t plays an important role in the decision to begin braking. In line with the existing literature, our results indicate that this role cannot be reduced to “initiate-an-action-at-threshold”.
It is also important to remember that drivers have several options available for reducing their speed. In the present study we focused on two
such possibilities: engine braking by downshifting and use of the footbrake
pedal. When the degree of danger was moderate (V→2/3V scenarios),
participants tended to use the gearbox to increase the amount of engine
braking. In the grand majority of cases, this proved to be sufficient to
avoid future collision. When the potential danger increased (V→1/3V scenarios), participants increased their use of engine braking by downshifting
several times and also began using the footbrake. In critical situations
(V→0V scenarios), the use of the footbrake became indispensable.
Comparisons of braking behaviour during real and simulated driving
have pointed out noticeable differences between the two. During real driving, the deceleration pattern is unimodal (Van der Horst, 1991; Spurr,
1965) while it is often multi-modal when driving a simulator (Boer et al.,
2000; Siegler et al., 2001). Due to the absence of vestibular and somesthetic cues related to physical deceleration, the fixed-base simulator leads to
larger decelerations than those found in reality (Boer et al., 2000; Malaterre & Fréhaux, 2001). The present experiment confirmed these earlier
observations, with participants almost always reaching maximal decelerations plateaus of 8 m/s2. Nevertheless, this shortcoming of simulators to
reproduce the natural modulation of the amount of deceleration applied
allows the emergence of an alternative strategy, with a series of activations
of the footbrake. Recalling that the optic variable ß specifies whether current deceleration is sufficient to avoid upcoming collision, it is clear that
during the first (near maximal) activation of the footbrake a sufficient
deceleration is optically specified. Participants are thus “invited” to
release the brake. If they do so too early, ß specifies that ongoing engine
braking is not sufficient to avoid upcoming collision. Drivers must then
increase engine braking by downshifting the gearbox and/or activate the
footbrake once again. This iterative process is repeated until a safe situa-
204
tion is reached. The finding that, in general, drivers used repeated downshifting and repeated activation of the footbrake indicates that they choose
to visually monitor the adequacy of the actions undertaken, rather than
simply apply a single, exaggerated deceleration burst. Thus, this simulator-evoked multimodal braking strategy in fact suggests that during
approach to a preceding vehicle, drivers detect the sufficiency of current
deceleration and regulate their approach speed according to this information. As such, the present results reinforce those of Yilmaz and Warren
(1995) and Fajen (2005), with respect to the use of the information carried in the optic variable ß to regulate approach speed.
A final aspect of the present study was the comparison of the perceptuo-motor strategies of two groups of subjects, qualified as “novice” (less
than three years of driving experience) and “experienced” drivers (more
than five years of driving experience). The first group is known to have an
increased risk of being involved in an accident with bodily harm relative to
the second group (Cerelli, 1992) and one of our goals was to evaluate
whether this increased risk was in any way associated with a fundamental
driving skill such as that of reducing speed when closing on a more slowly
moving preceding vehicle. Although one should always be careful with
interpreting an absence of (statistically significant) differences, the results
of the present study suggest that both groups of drivers used similar strategies (also see Barbet et al., in press). The hypothesis that driving experience was not useful at all because the task of driving a fixed-base simulator was completely novel to all does not seem to fit with the finding that
both groups of drivers were able to deal adequately with the different
types of scenario presented. We therefore interpret the fact that we could
not detect any (statistically significant) differences on the variables analysed as suggesting that the fundamental perceptuo-motor skill of regulating
approach velocity so as to avoid collision is sufficiently mastered by both
novice and experienced drivers.
ACKNOWLEDGEMENTS
This research was supported by PREDIT, ARCOS project (National Consortium: Action de recherche pour une conduite sécurisée). We thank
S. Durand for his technical assistance on the simulator, and F. Vienne
(MSIS-CIR, INRETS) for scenario construction. We also thank Jean-Michel
Hoc, Jacques Droulez and an anonymous reviewer for helpful suggestions.
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Paper received: April 2005.
Accepted by J.-M. Hoc in modified form: November 2005.
SUMMARY
The aim of this study was to identify the perceptual and motor strategies used
by car drivers to prospectively regulate the speed of approach to a preceding
vehicle so as to avoid collision. In order to evaluate the possible effects of driving
experience, two groups of participants were tested. The first group consisted of
13 participants with less than three years of driving experience (mean age
20.5 years) and the second group consisted of 13 participants with more than
five years of driving experience (mean age 26.5 years). All participants were tested on a fixed-base simulator (INRETS SIM2) under 16 different experimental
conditions, combining different initial speeds and different preceding vehicle
speeds. In each condition, just before the driver reached a designated goal speed
(60, 80, 100 or 120 km/h), another car, serving as a mask, overtook the controlled vehicle, placed itself at a 2 s distance ahead and adopted the participant’s
speed. After a variable time period, the mask vehicle changed lanes, revealing
an obstacle vehicle (positioned at stopping distance from the mask) moving at a
207
speed equal to 100, 67, 33 or 0% of the driver’s car. Thus, situations ranged
from no danger (preceding vehicle at the same speed) to imminent danger (stationary obstacle).
Overall, less-experienced and experienced drivers showed similar behavioural
patterns, that were both functional (allowing collision to be avoided) and adapted to the situation at hand, with more change intervening more rapidly for the
more urgent situations. Varying systematically with the degree of emergency of
the situation, drivers both changed gear and activated the footbrake once or
several times. In critical situations, drivers initiated braking after a time period
that depended on both inter-vehicle distance and on relative speed. The analyses
of the duration of braking activity revealed that braking itself seems to depend on
a complex relation between inter-vehicle distance and relative speed. Braking
intervened as a systematic function of the information carried in the pattern of
optic expansion of the obstacle (i.e., t and its rate of change over time ß), indicating the role of dynamic visual information in the regulation of approach
speed. In order to avoid upcoming collision, drivers seemed to use informational
patterns contained in the optic flow emerging from the evolving inter-vehicle distance and relative speed to regulate the velocity of their vehicle. The means used
to decelerate (engine braking and/or foot braking) was linked to the degree of
emergency perceived.
Key words: Information, Perception, Collision, Braking.
Dans la suite de ce numéro spécial, l’article suivant paraîtra dans le volume 69/3
Effects of driving experience and age on the detection of upcoming collision
I. Barbet, M. Meskali, C. Berthelon, D. Mottet & R. J. Bootsma.
Le Directeur de la publication : M. PRIGENT

Perceptual and motor strategies of car drivers in regulating speed of

Transcription

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