ITS and their users: classification and behavior Chapter | 6 83• protect VRUs, while improving the diffusion of new technologies; and
achieving a consistently high level of road safety for VRUs, with efficient
use of limited financial resources.
• impose transparency and monitoring of infrastructure security management
procedures;
• introduce a road-network assessment, a systematic, and proactive risk map-
ping process for assessing intrinsic road safety;
• lay down general performance requirements for road marking and road sig-
naling to facilitate the development of collaborative, connected, and auto-
mated mobility systems for VRUs.
• establish the obligation to systematically take account of VRUs in all road
safety management procedures.
Several ITS solutions that have been designed for drivers’ assistance have a
positive effect on the safety of VRUs, since they attack the same factors that in-
crease the safety risk for the driver and the passengers. Such factors that impact
the number and severity of car crashes and consequently the risk for vulnerable
user groups include— (1) increased driving speed, (2) consumption of alcohol,
(3) the inability to early notice the VRU that is in danger, and consequently (4)
the slow reflexes of the driver in case of emergency (Phan et al., 2010).
Several technological solutions can provide many safety benefits for the
VRUs, including among others—(1) smart speed and cruise control, (2) igni-
tion interlock when alcohol is detected, (3) systems that detect pedestrians and
VRUs in blind spots and early notify the vehicle and its Emergency Braking
(EBR) system. Finally, there are many more applications that have a signifi-
cant potential to improve safety and comfort including: (1) adaptive lighting
and sensor systems for night vision, systems that provide blind-spot vision, co-
operative warning systems for intersection safety, smart signals for pedestrian
traffic, which adapt to pedestrian presence and notify vehicles at the same time.
The emphasis of ITSs in drivers, passengers, and people's safety has resulted
in several applications that assist drivers in their driving tasks and consequently
influence their overall behavior. The directly recognizable positive effects that
relate to safety and comfort are balances in several cases from adverse effects
that come from the facilitation that technology offers. For example, when the
partially automated-vehicle takes control of the driving, the driver's attention
and awareness decreases and this may have a negative impact on safety. Train-
ing a machine learning algorithm is usually performed in simulation environ-
ments and using prototypes and control conditions that do not always match to
the conditions that drivers’ face in practice, and does not provide a permanent
solution, since the driver interaction with his/her environment is dynamic and
evolves over time. As a result, it is important to continuously collect and ana-
lyze traffic, condition and driver's behavioral data in order to have a more ac-
curate and updated model of driver's behavior. The large-scale collection and
analysis of traffic and accident data will improve the performance of automated