Infrastructure and Safety in a Collaborative World

Traffic safety is constantly increasing in Europe the last decade but not as much as planned and aimed at. This chapter introduces the major types of persistent driver errors and support needs as well as a methodology leading from problem recognition to proposing technical solution and implementation scenarios to avert them. The results of the other chapters of this book have been obtained working across the lines of this methodology, driving the IN-SAFETY project and beyond.

The basic aims of the IN-SAFETY project lied upon the principles of “forgiving” and “self-explanatory” road environments. As the overall aim of the project was “to use intelligent, intuitive and cost-efficient combinations of new technologies and traditional infrastructure best practice applications, in order to enhance the forgiving and self-explanatory nature of roads”, these two parameters were the main axes that defined the work of the project. The overall concept within which “forgiving” and “self-explanatory” roads lie, is this of sustainable safety, as part of the broader sense of sustainable development, which has been set as one of the major priorities of the EU policy towards achieving the goals of the White Paper of 2001 (COM 2001). In this chapter, the concept of sustainable safety is being discussed and special focus is put on technologies and implementation scenarios leading towards “forgiving” and “self explanatory” road environments.

This chapter briefly describes the basic principles of multi-criteria analysis (MCA) and cost–benefit analysis (CBA), in view of their application to the socio-economic evaluation of different scenarios for improving road safety. The specific scenarios for improving road safety by creating a more forgiving road (FOR) and self-explanatory road (SER) environment are, however, identified in subsequent chapters of this book. As regards MCA, the multi-actor MCA (or MAMCA), as well as the analytic hierarchy process (AHP), are discussed in more detail. As regard CBA, special attention is given to the definition of specific decision criteria. Special attention is also given to possible approaches to cope with lacking data on safety impacts. By the end of this chapter it should be very clear which are the different interpretations to be placed on the results of CBA and MCA, even in cases when these results are conflicting.

Still too many deaths and injuries are a result of road safety problems within Europe. Technologies based on combinations of infrastructural and in-vehicle system are expected to show the most cost-effective solutions. This chapter provides an overview of existing and emerging systems and a first evaluation of their safety effects, as the main “building blocks” in constructing scenarios to enhance traffic safety. Although not aiming at a thorough and exhaustive state of the art on such systems, the presented data allow the user to have a better understanding on the proposed and examined evaluation scenaria in other chapters of this book, as well as provide material for thoughts, to allow the reader (and especially any stakeholder) to imagine his/her own scenaria.

To cater to the needs of today’s road environment resp. road users, messages presented on roads must be optimized for early visual discrimination/legibility. This would provide more time for understanding and appropriate safe reaction of drivers to prevent accidents. Still, today’s road messages are not made that way– the Vienna Convention on Road Signs and Signals of 1968 was unable to foresee the developments on roads, resulting in much more and much faster cars, fostered by a large number of densely interconnected roads, supporting high speeds. Due to these factors, an increase in long distance travel has manifested, accompanied by unsolved issues of multilinguality. Until recently, these problems were attempted to be tackled by conventional signage, yielding a general increase of signs on the road. Variable message signs (VMS) seem sufficiently flexible to help overcome the narrowing bottleneck of road information we are facing today. As a principle, they are capable of delivering messages only when necessary, probably in several languages. Still, in the near future we will see a mixture of classic road signs and next generation displays, of varying capabilities to properly present road related information. Hence it is crucial to continue to build up improved means of signalisation, employing elements accounted for in terms of visual aspects and understanding, and able to be employed by any technology (from signs to displays), presenting road messages in a consistent way. The following rationale details the aspects of message optimisation, emphasizing the role and need of design-professionals in the process.

In this chapter, the application of macro and micro traffic simulation modelling for the needs of road safety assessment and planning is dealt. The overall concept of traffic simulation modelling regarding safety is presented, together with a series of macro and micro simulation models (namely RuTSim, S-Paramics, SATURN and VISSIM) that are widely used and have been specifically applied for the needs of IN-SAFETY project. ITS and ADAS related scenarios defined within IN-SAFETY, aiming to enhance the road safety level, have been tested through specially developed applications of these models and their results indicate the influence of the use of such technologies, as well as the effectiveness of the selected models in simulating and evaluating their effects. Future enhancement in the models will provide the possibility of further using them in the context of road safety and the involvement of innovative technologies.

This chapter presents the background, along with some illustrated examples, of simulator applications for the needs of assessing novel systems and infrastructure interventions, in terms of enhancing the forgiving and self-explanatory nature of a road. The first two, “Active traffic management” and “Non-physical motorway segregation” are designed to ease congestion but also have implications for safety, the first leading towards a self-explanatory road environment (SER), whereas the second contributing towards a more forgiving road environment (FRE). The second two “Actively illuminated road studs” and “Psychological traffic calming” are FRE types of interventions, designed for rural roads specifically to improve safety, but these may also have unanticipated consequences. For example, delineation of a road at night by actively illuminated road studs offers the driver much greater visibility of the road ahead, but this could be exploited by drivers choosing to drive at higher speeds. Finally, the pilot testing of milled vs. “virtual” rumble strips as in-vehicle information is presented (another FRE measure), as tested within IN-SAFETY, following a testing methodology which brings together methods for collecting data on individual driver behaviour and traffic simulation, building upon the traffic safety related adaptations of microsimulation models.

In order to promote traffic safety one has to identify, analyse and, ultimately, manage the risk. More precisely, we need to determine what the actual traffic risks are; how any proposed measures will affect safety (enhance or – unfortunately – possibly reduce; alone or in combination); and finally which policies seem to be most effective. Risk analysis methods are appropriate to cover all above issues. The risk approach allows foreseeing future effects, as it works with probabilities. This chapter presents a new risk analysis methodology, called INsafety Risk Analysis Method (INRAM), which covers different parts and steps, which together allow an overall estimation of the safety effects of planned measures, even considering human behaviour and human errors. It is constituted by several sub-modules, namely: first, the ADVISORS method, which gives an appropriate framework to evaluate all sorts of risks; second, the Darmstadt Risk Analysis Method (DRAM) helps to analyse single risks in a more detailed way and third, some other tools, e.g. regression methods and network path algorithms, which help to obtain appropriate data.

In this chapter the issue of training drivers and operators regarding new technological achievements in the area of Intelligent Transport Systems is being dealt. As new technological achievements, both regarding in-vehicle as well as infrastructure-based systems, are rapidly entering the market, the road users and operators are asked to use or manage such systems in their everyday routine. However, the significant benefits of the use of these systems may become worthless, or even dangerous, if the systems are not used properly. Thus, the need for training becomes a necessity. In this perspective, several research initiatives have undertaken the task of designing and testing training schemes for drivers and/or operators, aiming at enhancing their knowledge on the use of new technologies and, at the same time, securing the road safety and efficiency benefits that their proper use may bring. In this chapter, indicative examples of such schemes are presented: the driver training MMT of HUMANIST NoE, the simulator training schemes of TRAIN-ALL STREP, the ADR drivers training MMT’s of INFORMED LdV project, the operators’ training manual and MMT of IN-SAFETY STREP and the infrastructure operators training schemes of GOOD ROUTE STREP.

Advanced Driver Assistance Systems (ADAS) are designed to assist the driver in his/her driving task and increase his/her comfort and safety. Various ADAS are nowadays available, in the lateral support category Lane Departure Warning Systems (LDWS) also known as Lane Keeping Systems (LKS) or Lane Drift Warning systems are the most known. They either warn the driver or intervene when he/she is about to drift unintentionally from his/her lane. A more detailed analysis on ADAS can be found in Chap. 4. In various field operational tests (FOTs) in the Netherlands, LDWS/LKS have been evaluated to explore the effects on driving behaviour and traffic flow, in terms of safety, throughput and environment. Relevant evaluation results are presented here, as a typical Forgiving Road Environment (FRE) application.

Intelligent Speed Adaptation (ISA) involves an in-vehicle system, which supports the driver in not exceeding the speed limit. Inappropriate speed or speeding is a major cause of road traffic accidents and strongly relates to the outcome of an accident (research indicates that in Europe one third of all fatal accidents is caused by inappropriate speed). As such, ISA has the potential to substantially improve traffic safety and is recognized as a promising speed management policy. Over the past decades, a lot of research on ISA has been conducted across Europe. This research involved different ISA systems, ranging from simple information provision to keeping the car to the local speed limit, and a variety of different methodologies, ranging from pilots and trials, to driving simulator studies, computer simulations and expert elicitation of opinions. The central notion in this chapter is to describe which evolutions were found about ISA around the world to assess the effects of ISA on social, ecological, economical, political and technical level. By discussion and evaluation of some ISA studies and ISA developments, two main questions will be answered: what do we know and what is still do be done? This will result in an overview of barriers and issues that have been resolved and that still have to be resolved, to enable large-scale implementation.

One critical situation when a driver needs to have a high degree of awareness, to avoid critical situations or crashes, is when passing a school bus, stopped for boarding or de-boarding of children. With the help of an experiment in VTI’s moving base driving simulator, a scenario, using in-vehicle information before the bus was reached, was tested. The aim was to enhance drivers’ perception, in order to reduce the speed of vehicles passing by the stopped bus. Both alert and sleep deprived drivers were tested. The results showed a significant speed reduction thanks to the information given beforehand. Sleep deprivation did not seem to have an impact on speed reduction. This suggests that the warning signals are seen and followed, regardless the drivers’ state of alertness. Thus, it seems likely that this type of information may be useful as an Intelligent Transport System (ITS), to provide driver support about upcoming hazards. One step towards further research in this direction is performed within the EU project SAFEWAY2SCHOOL, the main objectives of which are presented at the end of this chapter.

This chapter presents the results of an iterative design and evaluation process relating to the cognitive and technical requirements on information to be displayed on variable message signs (VMS) and conventional road signs. It was carried out within the framework of the IN-SAFETY research project, as a set of proposed measures and implementation scenario to improve the self-explanatory nature of the road environment. In line with ISO 9186 “Test methods for judged comprehensibility and for comprehension”, a total of 2,977 symbol/pictogram variants were selected for submission to an iterative testing and redesign process. A series of four tests were conducted in the Czech Republic, Hungary, Spain and Austria and involved 2,667 test persons. A subsequent experiment was then carried out with 150 participants to evaluate the legibility of several widely used fonts. The evaluation results revealed several areas where improvement was needed. Based on the evaluation results, a new typeface for variable message sign displays was developed and optimized to address these shortcomings. The close cooperation between the designers and researchers throughout the process proved very effective in terms of integrating shortcomings and taking the study results into account. The evaluation of the fonts/pictograms leads to the “Proposal on unified pictograms, keywords, bilingual verbal messages and typefaces for VMS in the Trans European Road Network (TERN)” [P. Simlinger, S. Egger, C. Galinski, Proposal on unified pictograms, keywords, bilingual verbal messages and typefaces for VMS in the TERN. Deliverable 2.3, C.N. 506716, In-Safety project, January 2008, http://www.insafety-eu.org/documents/IN-SAFETY_Deliverable_2.3.pdf].

A key issue towards SER and FRE is personalization, as explicitly advocated in Chap. 4. Within the concept of the IN-SAFETY project, two pilots have taken place, in Greece and Italy respectively, aiming to test a personalized system for in-vehicle transmission of traffic related information provided by Variable Message Signs (VMS). The design and development of the system tested in the Greek pilot is presented in the present chapter. To come up with the final system, four architectures were originally proposed; among these one (which was using Bluetooth technology) was finally abandoned for technical reasons and its presentation is outside the scopes of this chapter, whereas for the other three – finally selected – solutions (i.e. WLAN, GPS with GPRS) the theoretical and practical design are thoroughly described. Moreover, the issue of human–machine interface (HMI) is particularly looked into, with the target to provide the information to the drivers in a self-explaining and user-friendly manner, thus avoiding driver distraction and/or overload. After developing the system, technical verification tests have been performed on site to examine if the system is meeting the original expectations, as well as to identify shortcomings and ways to overcome them. The technical tests were followed by the full pilot tests, for assessing the proposed system with real drivers, whose results are presented here along with respective conclusions.

In this chapter different scenarios for improving road safety by creating a more forgiving road (FOR) and self-explaining road (SER) environment are selected and submitted to a multi-actor multi-criteria analysis (MAMCA), introduced in Chap. 3. The aim of this MCA is to allow various stakeholders with an interest in improving road safety (in particular public policy makers, but also users and manufacturers) to assess to which extent the future scenarios for creating a more FOR and SER environment contribute to their specific objectives. A separate MCA is, therefore, performed for each of these stakeholders, taking into account the specific objectives considered relevant by them, as measured by criteria. Analysing the differences in preferences among stakeholders, and using the highest expected “added-value” from the community of stakeholders in its entirety on various FOR and SER environments, uncovers useful information on the chances of successful implementation.

This chapter provides the results of a limited cost–benefit analysis (CBA) on selected implementation scenarios. A main challenge for CBA of ITS-based safety measures is the limited quantifiable estimates of their effects on road fatalities and injuries. As a proxy to estimating such effects, an error-based approach is applied. That is, particular ITS-based measures are assumed to help drivers avoid errors that are known to be related to particular types of accidents; the target accidents of the technologies. Such an approach to measuring benefits inevitably requires strong assumptions for quantifying the fatality/injury effects. In addition, there is also lack of empirical knowledge on the indirect effects of ITS-based safety measures; the possible impact on time use and emissions. Since such possible indirect impacts are not included in this CBA, the analysis can be considered as only partial. Even if the quantified safety effects are on the optimistic side, the resulting benefit–cost ratios are still fairly low, because of the technology costs. However, future costs are assumed to decrease, and some of the technologies might be standard equipment in more and more car models.

In this chapter the main policy implications from the IN-SAFETY project are drawn. These policy recommendations are structured along the primary stakeholders in the area and were built up by following a structured approach towards policy formulation. On the basis of the six main policy measures and the results of the Multi Actor Multi Criteria Analysis procedure (MAMCA), the main policy issues are put forward. Next to the ranking of the different measures, these policy recommendations show a clear need for a uniform information presentation to the driver. Following the project’s structure, the recommendations are classified as follows: Recommendations from application guidelines and further research issues Recommendation on pictograms and verbal messages, horizontal and vertical signing Recommendations for application of traffic simulation and risk modelling Lessons learnt from pilot tests Recommendations for application of the operators manual Recommendations from MCA-AHP and CBA assessment of selected systems and functions

Road safety research has been a priority in Europe during the last decade. Especially after the publication of the White Paper on Transport in 2001 (European Communities, 2001, White Paper, “European transport policy for 2010: time to decide”) and its mid-term review in 2006, there where specific targets put for the enhancement of road safety, with the most prominent one being the halving of road accident fatalities in the EU by 2010. The statistics show that there have been significant steps realized towards this direction. However, reaching the deadline of the time horizon, it is evident that the target has not been reached. In the meantime, new research priorities have emerged in Europe, as well as worldwide, such as the environmental protection, which are highly linked to road safety research, especially within the concept of sustainable safety. In this chapter, it is elaborated how road safety has evolved in the latest years, as well as how and why safety research should proceed in the following years, as a priority research area in the EU.