Safety

The increasing in-vehicle information and safety systems tend to confuse and distract the
driver from his/her primary driving task. This paper develops algorithms for the real-time
supervision of the traffic and environmental scenario around the vehicle for the optimization
of the Human Machine Interaction. The proposed algorithms reconstruct the scenario using
stochastic motion models and Kalman filters, predict the intention of the driver using
Demspter-Shafer decision fusion and calculate the level of risk in using fuzzy logic. The
algorithms will be part of the Driver – Environment – vehicle state estimation in AIDE
Integrated project.

Institute of Communications and Computer Systems, I-SENSE Group

Presented at the 12th World Congress on Intelligent Transport Systems, November 6-10, 2005, San Francisco, California

The combination of new technologies, e.g. ADAS (Advanced Driver Assistance Systems)
and/or telematics, with existing infrastructure may lead to cost-efficient solutions for reducing
road traffic accidents. The paper explores innovative measures of ADAS/telematics and infrastructure
technologies, and assesses the possible impact on self-explanatory and forgiving
road environments. Based on the investigation of the functional relationships between ADAS
and infrastructure design, a set of implementation scenarios are proposed of infrastructure
based measures and ADAS based measures. Road traffic safety is analysed in terms two composing
factors, accident risk and accident consequence, and of the speed and conflict related
determinants of these factors. The paper presents a conceptual schema (model) for microscopic
safety assessment to enable comparison of the effectiveness of measures with different
nature. The model could be used to analyse the potential effects of and relationships between
the various scenarios. The application of the conceptual model is illustrated in a case study of
safety performance analysis in the Netherlands.

Radboud University Nijmegen

NAVTEQ B.V., Veldhoven, The Netherlands

Hellenic Institute of Transport

Presented at the 12th World Congress on Intelligent Transport Systems, November 6-10, 2005, San Francisco, California

Two of the main approaches to improve traffic safety are extensive redesign of the physical road
infrastructure and large-scale implementation of Advanced Driver Assistance Systems (ADAS).
These strategies are to a large extent substitutes, but also partly complementary. This paper determines
strategic road traffic safety scenarios, reviews some of the evaluation methods most commonly
used in transportation research, and presents Grey Relational Analysis (GRA). GRA is a
normalisation based method. It provides a simple and transparent calculation procedure from which
a clear-cut ranking order of strategies derives. The application of GRA to the evaluation problem is
addressed, and some preliminary results are reported, especially sensitivity analysis is discussed.

Radboud University Nijmegen

NAVTEQ B.V.

Delft University of Technology, The Netherlands

Presented at the 12th World Congress on Intelligent Transport Systems, November 6-10, 2005, San Francisco, California

Observations of overtaking manoeuvres on bi-directional rural roads were carried out to
enhance the understanding of driver behaviour prior to, during and after an overtaking
manoeuvre. Data were collected to serve as a basis for developments towards overtaking
assistance systems. An instrumented vehicle was used to record overtaking manoeuvres: this
vehicle drove in actual traffic and several speeds were chosen that led to other vehicles
overtaking the instrumented vehicle. In total, 48 manoeuvres were recorded and analysed
afterwards. The duration of the overtaking manoeuvres was analysed in relation to the applied
overtaking strategy and the speed of the instrumented vehicle. Only limited variation in the
overtaking duration was found, from which it is concluded that a single type of overtaking
assistance system can serve most drivers. Fairly short perception-reaction times were
observed, indicating that the decision to perform an overtaking manoeuvre is made before an
appropriate gap in the oncoming traffic stream is available. Overtaking assistance can
therefore only be valuable if it is able to assist prior to the emergence of such a gap, otherwise
valuable time is lost.

Delft University of Technology

Presented at the 12th World Congress on Intelligent Transport Systems, November 6-10, 2005, San Francisco, California

For probabilistic analysis, we used the system reliability engineering method to model
rear-end and right-turn collisions. This model integrates driver’s evasive reaction time to
dangerous events with fluctuating driving performance caused by state transition of driver
consciousness. Results show that the probability of a driver being inattentive can be estimated
quantitatively by analyzing the state transitions of consciousness. In dangerous situations, the
frequency of rear-end collisions caused by average drivers is about 6.7×10-5/h, and the
probability of right-turn collisions is about 3.7×10-6.

Japan Automobile Research Institute

Daido Institute of Technology

Tokyo University of Marine Science & Technology

Presented at the 12th World Congress on Intelligent Transport Systems, November 6-10, 2005, San Francisco, California