What drives the Acceptability of Intelligent Speed Assistance (ISA)? Modeling acceptability of ISA

6370 individuals responded in Belgium (Flanders region) and 1158 persons in The Netherlands on a web-survey about ISA. A model has been estimated, by using SEM, to find out which predefined indicators would be relevant to define the acceptability of ISA. Background factors, contextual issues, and ISA-device related factors were used as indicators to predict the level of acceptability. The factors that were used in the model were based on the methods used in past ISA trials, acceptance and accep-tability theories and models. The effectiveness of ISA (1), equity (2), effectiveness of ITS (3) and personal and social aims (4), were the four variables that had the largest total effect on the acceptability of ISA. Effectiveness was found a relevant predictor for acceptance in many trials (Morsink et al, 2006). The model showed that the willingness of drivers to adopt ISA increases if they experience the system in practice: if people are convinced that ISA will assist to maintain the legal speed in different speed zones, the acceptance will be higher (Van der Pas et al., 2008). Hence, trials seem a good way to demonstrate the effectiveness of ISA. However, trials typically do not allow many people to try out ISA. Therefore, communi-cation strategies that focus on the ISA-effectiveness would be helpful to convince people about the benefits of using such a system. Often when new driver support technologies are intro-duced – especially when it could restrict certain freedom in driving – a majority of the population is reluctant when it comes to ‘buy or use’ the system. In some studies (see Morsink et al., 2006; Marchau et al., 2010) the willingness to pay was reported to be a good predictor for acceptability. However, in the present study the effect of willing-ness to pay was very low or even absent; hence it may be as-sumed that better indicators are put in the model than the willing-ness to pay. With respect to context indicators, ‘personal and social aims’ seemed to be the variable with the highest influence on accep-tability. Drivers, who rate social aims above personal aims with respect to speed and speeding, will accept ISA more. Personal and social aims had also a high influence on most of the device spe-cific indicators. Furthermore, drivers who speed for their personal benefit were found to rather speed more often. Drivers who speed in high-speed zones would also be less inclined to accept ISA. This is in line with previous findings (e.g. Jamson et al., 2006), frequent speeders would support ISA less; those drivers who would benefit most of ISA would be less likely to use it. This is an important finding when considering the strategies for implementing ISA. Some studies (e.g. Morsink et al., 2006) indicated that to increase the acceptability, implementation strategies and campaigns could focus on other benefits of ISA (like reducing speeding tickets, emissions etc.). According to our study these secondary effects have rather small effects to increase acceptability. Drivers who like to speed would even care less for these secondary benefits of ISA. The youngest group of drivers (<25 years old) would influence responsibility awareness negatively. These younger drivers are also less convinced that certain behaviour or circumstances could cause accidents. Many studies indicated that young drivers over-estimate their own driving skills, drive faster and are less aware of accident causes (Shinar et al., 2001). For the implementation of ISA – although there is no direct relationship between younger age and acceptability – a different strategy is needed to convince this group of drivers. Awareness campaigns and communication should be deployed during their education, however, road safety education and training stops during secondary school or higher education (OECD, 2006). Drivers between 25 and 45 years old would also be less inclined to accept ISA, mainly considered out of indirect effects in the esti-mated model. This group of drivers may be labelled as one of the most active groups of drivers. Another aspect is that both of the "significant found age groups were influenced by social norms. This may be very important in implementation strate-gies. For instance, role models could be used in ISA driving. This strategy was also used in the Belgian trial to gain more publicity and attention. The positive image and the improved information communication of ISA as a possible measure in road-safety have led to several voted resolutions in the Belgian federal parliament and senate (Vlassenroot et al. 2007)

On the Feasibility of Social Network-based Pollution Sensing in ITSs

Intense vehicular traffic is recognized as a global societal problem, with a multifaceted influence on the quality of life of a person. Intelligent Transportation Systems (ITS) can play an important role in combating such problem, decreasing pollution levels and, consequently, their negative effects. One of the goals of ITSs, in fact, is that of controlling traffic flows, measuring traffic states, providing vehicles with routes that globally pursue low pollution conditions. How such systems measure and enforce given traffic states has been at the center of multiple research efforts in the past few years. Although many different solutions have been proposed, very limited effort has been devoted to exploring the potential of social network analysis in such context. Social networks, in general, provide direct feedback from people and, as such, potentially very valuable information. A post that tells, for example, how a person feels about pollution at a given time in a given location, could be put to good use by an environment aware ITS aiming at minimizing contaminant emissions in residential areas. This work verifies the feasibility of using pollution related social network feeds into ITS operations. In particular, it concentrates on understanding how reliable such information is, producing an analysis that confronts over 1,500,000 posts and pollution data obtained from on-the- field sensors over a one-year span.Comment: 10 pages, 15 figures, Transaction Forma