Traffic calming measures, such as speed bumps and elevated crossing points, are used to reduce speed, to prevent overtaking and generally contribute to a safer traffic situation. However, they might also cause increased response times for rescue vehicles (e.g. ambulances or fire trucks). An alternative to the conventional traffic calming measures is so-called smart traffic calming measures. These can determine when a vehicle approaches, whose journey should not be hindered, and adjust to allow for free passage for this vehicle.

This report gives an overview of the problem, and some examples of smart  traffic calming measures are discussed. Special focus is put on the wireless communication necessary to detect emergency vehicles. Furthermore, existing challenges and possible solutions for traffic calming measures and the communication needed to make them smart are discussed.

A strong monitoring system of road safety in a city is necessary to ensure that the strategies implemented will meet stated targets at city and national levels. Although road safety performance is a result of many key indicators, only a few of these indicators are generally considered in monitoring the performance of road safety in a city and in comparison to other cities. A number of monitoring systems are already being developed and used in road safety and they range from relatively simple models to highly complex ones depending on the number of indicators involved, details of data and complexity of methods used in calculations and analysis. In road safety, there are three main types of monitoring that are generally used, which are: Process Monitoring, Outcome Monitoring and Target Monitoring. The aim of this paper is to provide the importance and usefulness of having a fourth type of monitoring, so-called Integrated Monitoring, that links process, outcome and targets together. The paper also provides a conceptual overview, and illustrations that are used in the construction of the integrated monitoring system.

A strong monitoring system of road safety in a city is necessary to ensure that the strategies implemented will meet stated targets at city and national levels. Although road safety performance is a result of many key indicators, only a few of these indicators are generally considered in monitoring the performance of road safety in a city and in comparison to other cities. A number of monitoring systems are already being developed and used in road safety and they range from relatively simple models to highly complex ones depending on the number of indicators involved, details of data and complexity of methods used in calculations and analysis. In road safety, there are three main types of monitoring that are generally used, which are: Process Monitoring, Outcome Monitoring and Target Monitoring. The aim of this paper is to provide the importance and usefulness of having a fourth type of monitoring, so-called Integrated Monitoring, that links process, outcome and targets together. The paper also provides a conceptual overview, and illustrations that are used in the construction of the integrated monitoring system. © 2011 WIT Press.

This dissertation develops, presents and tests a new international tool, the so-called Road Safety Development Index (RSDI), which indicates in a comprehensive and easy way the severity of the road safety situation in a specific country and/or in comparison with other countries. There are three pillars of outcomes involved in the framework of RSDI. One pillar is the People focus (road user behaviour). The second is the System focus (safer vehicles, safer roads, enforcement, management, etc). The third is the Product focus in terms of accident death rates. This thesis analyses each of these pillars. In addition, RSDI links the key national practices of road safety to each other and to the end-results (accident death rates). The study suggests a master-list of performance indicators to be implemented for assessing road safety level in a country and for RSDI building. Based on the “master-list”, a short key list of performance indicators is chosen and classified into two primary categories that correspond to two groups of countries: LMCs “Less Motorised Countries” and HMCs “Highly Motorised Countries”. RSDI aggregates the key performance indicators into one single quantitative value (composite index). Four main objective and subjective approaches are used to calculate RSDI and determine which one is the best. One approach uses equal weights for all indicators and countries, whereas the other approaches give different weights depending on the importance of indicators. Two empirical studies were carried out, in different parts of the world, to determine the applicability of this tool in real world applications. The first empirical study comes from eight European countries (HMCs). The second empirical study comes from five Southeast Asian countries (LMCs). The RSDI results from this study indicate a remarkable difference between the selected countries even at the same level of motorisation and/or with close accident death rates. The unavailability of comparable and useful data are problems for deeper analysis of RSDI, especially the index should be as relevant as possible for different parts of the world. The empirical and theoretical assessments prove that RSDI can give a broader picture of the whole road safety situation in a country compared to the traditional models and can offer a simple and easily understandable tool to national policy makers and public.

Aim. This study suggests a set of methodologies to combine different indicators of road safety into a single index. The RSDI is a simple and quick composite index, which may become a significant measurement in comparing, ranking and determining road safety levels in different countries and regions worldwide. Design. One particular concern in designing a Road Safety Development Index (RSDI) is to come up with a comprehensive set of exposure and risk indicators which includes as far as possible the main parameters in road safety related to human-vehicle-road and country patterns instead of considering few and isolated indicators such as accident rates. The RSDI gives a broad picture compared to the traditional models in road safety.

 Challenges. The differences in definitions, non-collection of data, no reliability of data and underreporting are problems for the construction of RSDI. In addition, the index should be as relevant as possible for different countries of the world, especially in developing countries.

Empirical study. This study empirically compares the road safety situation and trends between ten Southeast Asian countries and Sweden for the period 1994- 2003. Methodologies. Eleven indicators are chosen in RSDI, which have been categorised in nine dimensions. Four main approaches (objective and subjective) are used to calculate RSDI and determine which one is the best. One approach uses equal weights for all indicators and countries, whereas the other approaches give different weights depending on the importance of indicators.

Findings. The thesis examines the RSDI for the ten ASEAN countries and Sweden in 2003. The results from this study indicate a remarkable difference between ASEAN countries even at the same level of motorisation. Singapore and Brunei seem to have the best RSDI record among the ASEAN countries according to the indicators used, while Laos, Cambodia and Vietnam show lower RSDI records. Conclusions. The RSDI results seem very promising and worth testing further applications with bigger samples of countries and from different parts of the world.