Safe work zones are very important to road authorities. The European Parliament emphasizes this and "Calls on the Commission to ensure that road work sites are made safer through guidelines for designing and equipping sites […]; calls for guidelines, which should include proper signing, removal of original road markings […]". The Flemish Agency for Roads & Traffic created different standard signalization schemes which ought to be used at road work sites. One of these schemes deals with the signalization of road works at a roundabout. Goal of this study was to test the comprehensibility of the proposed signalization by means of a driving simulator and to evaluate if drivers could reach the destination. Fifty participants drove seven different routes (3.5 km) in a randomized order fixed-base simulator (NADS MiniSim™). The scenarios consisted of a realistic Flemish road in which the signalization scheme was implemented. Drivers were instructed to drive as they normally do and to drive to one of four destinations. The western roundabout branch was closed because of road works and participants needed to follow a detour. The route choice behavior of the participants at two decision points was qualified as correct or incorrect. Across scenarios, 23% to 90% of the participants could reach the destination. Based on these results, several recommendations were provided. One important adaptation was recommended in the route where participants needed to use the roundabout clockwise (only 23% did this correctly). Drivers who did not comply to the signalization instructions in this situation, verbally gave the comment that the information at the advance direction sign in this route was not clear. Therefore, we suggest to modify the advance direction sign at this place. Another recommendation is to change the general temporary direction signs "detour" by specific temporary direction signs which state the municipality name. ; Part of this research was funded by grants from the Flemish Agency for Roads & Traffic. The authors thank Marc Geraerts for technical assistance and Judith Urlings for language revision.
In Belgium, traffic safety is currently one of the government's highest priorities. Identifying and profiling black spots and black zones in terms of accident related data and location characteristics must provide new insights into the complexity and causes of road accidents which, in turn, provide valuable input for government actions. In this paper, association rules are used to identify accident circumstances that frequently occur together at high frequency accident locations. Furthermore, these patterns are analysed and compared with frequently occurring accident characteristics at low frequency accident locations. The strength of this approach lies within the identification of relevant variables that make a strong contribution towards a better understanding of accident circumstances and the discerning of descriptive accident patterns from more discriminating accident circumstances to profile black spots and black zones. The use of this data mining algorithm is particularly useful in the context of large datasets on road accidents, since data mining can be described as the extraction of information from large amounts of data. Results show that human and behavioural aspects are of great importance when analysing frequently occurring accident patterns. These factors play an important role in identifying traffic safety problems in general. However, the most discriminating accident characteristics between high frequency accident locations and low frequency accident locations are mainly related to infrastructure and location characteristics.
Speed is one of the main risk factors in traffic safety, as it increases both the chances and the severity of a crash. In order to achieve improved traffic safety by influencing the speed of travel, road authorities may decide to lower the legally imposed speed limits. In 2001 the Flemish government decided to lower speed limits from 90 km/h (56mph) to 70 km/h (43mph) on a considerable number of highways. The present study examines the effectiveness of this measure by using a comparison group before- and after study to account for general trend effects in road safety. Sixty-one road sections with a total length of 116 km (72 miles) were included. The speed limits for those locations were restricted in 2001 and 2002. The comparison group consisted of 19 road sections with a total length of 53 km (33 miles) and an unchanged speed limit of 90 km/h (56mph) throughout the research period. Taking trend into account, the analyses showed a 5% decrease [0.88; 1.03] in the crash rates after the speed limit restriction. A greater effect was identified in the case of crashes involving serious injuries and fatalities, which showed a decrease of 33% [0.57; 0.79]. Separate analyses between crashes at intersections and at road sections showed a higher effectiveness at road sections. It can be concluded from this study that speed limit restrictions do have a favorable effect on traffic safety, especially on severe crashes. Future research should examine the cause for the difference in the effect between road sections and intersections that was identified, taking vehicle speeds into account.
Speed is a main risk factor in traffic safety, which increases both the chance and the severity of the crash. In order to work to a better traffic safety through influencing the travel speeds, road authorities may decide to lower the legally imposed speed limits. In 2001 the Flemish government decided to lower speed limits from 90 to 70 km/h at a considerable number of highways. Current study examines the effectiveness of this measure, through the application of a comparison group before-after study to account for general trend effects in road safety. Sixty-one road sections with a total length of 116 km were included. Those locations knew a restriction of the speed limit in 2001/2002. The comparison group consisted of 19 road sections with a total length of 53 km and an unchanged speed limit of 90km/h during the total research period. Taking trend into account, the analyses showed a 5% decrease [0.88; 1.03] in the crash rates after the speed limit restriction. A stronger effect was found for the crashes with serious injuries and fatalities, which showed a decrease of 33% [0.57; 0.79]. Separate analyses between crashes at intersections and at road sections showed a higher effectiveness at road sections. From this study can be concluded speed limit restrictions do have a favorable effect on traffic safety, especially on the severe crashes. Future research should examine the cause for the difference that was found in the effect between road sections and intersections, taking vehicle speeds into account.
These days, road safety has become a major concern in most modern societies. In this respect, the determination of road locations that are more dangerous than others (black spots or also called sites with promise) can help in better scheduling road safety policies. The present paper proposes a multivariate model to identify and rank sites according to their total expected cost to the society. Bayesian estimation of the model via a Markov Chain Monte Carlo approach is discussed in this paper. To illustrate the proposed model, accident data from 23,184 accident locations in Flanders (Belgium) are used and a cost function proposed by the European Transport Safety Council is adopted to illustrate the model. It is shown in the paper that the model produces insightful results that can help policy makers in prioritizing road infrastructure investments.
Background: The Flemish government is considering the implications of allowing the use of Longer and Heavier Vehicles (LHVs) for road freight transport. These megatrucks can measure up to 25.25m (instead of 18.75m) and weight up to 60 tons (instead of 44 tons). Such trucks are already in circulation in some of the EU Member States (e.g. Sweden, the Netherlands). This driving simulator study is part of a pilot project that's investigating the advantages and disadvantages of introducing LHVs in Flanders (Belgium). Objectives: To get more insight in the drivers' behavior when drivers are overtaking an LHV or when they are entering/exiting a highway in the presence of an LHV. Getting more insight in the behavior of the LHVs drivers is not the scope of this driving simulator study, but this is investigated in another subproject within the pilot project. Methodology: The experiment is conducted on a medium-fidelity STISIM driving simulator and the visual virtual environment is presented on a large 180° field of view seamless curved screen, with rear view and side-view mirror images. The driving simulator consists of a mock-up and is equipped with a faceLAB eye tracking system. Fifty participants are exposed to different conditions of entering/exiting the highway and overtaking maneuvers. Results & conclusions: We can conclude that there is little difference between the regular truck and LHV conditions in case of overtaking maneuvers on a secondary road or entering/exiting a highway. However, some important findings that road authorities should take into consideration are: Drivers need a longer distance to perform the overtaking maneuver on a secondary road in the LHV condition; Drivers tend to drive closer to the right side of the road after overtaking an LHV. Therefore, only allowing LHVs on roads with physically separated cycle lanes can be an option; Drivers need a longer distance to enter the highway safely in the presence of an LHV. Therefore, the merging lanes on highways might be provided with an emergency lane with a minimum length of 250m. Additionally, a warning sign at the backside of the LHV is very useful to inform the drivers that they are driving behind a truck with a length of up to 25.25 meters. ; This project was funded by the Ministry of the Flemish Community as a part of the Policy Research Centre for Traffic Safety. Furthermore, part of this research was funded by the European Regional Development Fund.
Road transport is vital to the economic development, trade and social integration. However, it is also responsible for the majority of negative impacts on environment and society. To achieve sustainable development, there is a growing need for a country to assess its undesirable costs so as to determine its road transport policy. In this study, total energy consumption, greenhouse gas emissions, as well as the number of fatalities in the European road transport are selected representing the level of sustainable development in each member state of the European Union (EU). With data from the period of 1995-2007, the extent to which the 27 EU countries have improved their 'productivity' on sustainable road transport is evaluated based on data envelopment analysis (DEA) and Malmquist productivity index, which measures the productivity change over time, and can be further decomposed into two components: the change in efficiency and the technical change. The results show a considerable progress towards the sustainable road transport in Europe during this period. The decomposition into the two components further revealed that the bulk of the improvement was attained through the adoption of productivity-enhancing new technologies throughout the road transport sector, rather than through the relatively inefficient countries catching up with those efficient ones. In addition, the growth in both two aspects slowed down in 2007, which implies the momentum of further improvement is in danger of being lost so that new impetus is needed.
Introduction: In this paper a sensitivity analysis is performed to investigate how big the impact would be on the current ranking of crash locations in Flanders (Belgium) when only taking into account the most serious injury per crash instead of all the injured occupants. Results: Results show that this would lead to a different selection of 23.8% of the 800 sites that are currently considered as dangerous. Conclusions: Considering this impact quantity the researchers want to sensitize government that giving weight to the severity of the crash can correct for the bias that occurs when the number of occupants of the vehicles are subject to coincidence. Additionally, probability plots are generated to provide policy makers with a scientific instrument with intuitive appeal to select dangerous road locations on a statistically sound basis. Impact on industry Considering the impact quantity of giving weight to the severity of the crash instead of to all the injured occupants of the vehicle on the ranking of crash sites, the authors want to sensitize government to carefully choose the criteria for ranking and selecting crash locations in order to achieve an enduring and successful traffic safety policy. Indeed, giving weight to the severity of the crash can correct for the bias that occurs when the number of occupants of the vehicles are subject to coincidence. However, it is up to the government to decide which priorities should be stressed in the traffic safety policy. Then, the appropriate weighting value combination can be chosen to rank and select the most dangerous crash locations. Additionally, the probability plots proposed in this paper can provide policy makers with a scientific instrument with intuitive appeal to select dangerous road locations on a statistically sound basis. Note that, in practice, one should not only rank the crash locations based on the benefits that can be achieved from tackling these locations. Future research is also needed to incorporate the costs of infrastructure measures and other actions that these crash sites require in order to enhance the safety on these locations. By balancing these costs and benefits against each other, the crash locations can then be ranked according to the order in which they should be prioritized.
In Flanders (Belgium), approximately 1014 accident locations are currently considered as 'dangerous'. These 'dangerous' accident sites are selected by means of historic accident records for the period 1997-1999. More specifically, a combination of weighing values, respectively 1 for each light injury, 3 for each serious injury and 5 for each deadly injury, is used to calculate the priority score for each accident location. In this paper, a sensitivity analysis is performed to investigate how big the impact is on the current ranking of accident sites when alternative ranking criteria are used. More specifically, we only take into account the most serious injury per accident and use a valuation of casualties based on direct costs, indirect costs and validation for human suffering to give weight to the accidents. This valuation results in the weighing values 1_7_33 when the most severe injury respectively concerns a light, serious or deadly injury. Additionally, we generate probability plots, based on estimates from a hierarchical Bayes model, in order to visualize the estimated probability that a location will be ranked as dangerous. Results showed that combining these ranking criteria will have a big impact on the selection and ranking of dangerous accident locations. In particular, when selecting from the 5326 accident locations with minimum 3 accidents, the 800 most dangerous accident sites using the 1_7_33 values, 40,6% of these locations will differ from the current selection. Considering this impact quantity, we want to sensitise government to carefully choose the criteria for ranking and selecting accident locations without stating that the criterion used in this paper should be preferred to the currently used ranking method.
In Flanders (Belgium), approximately 1014 accident locations are currently considered as 'dangerous'. These 'dangerous' accident sites are selected by means of historic accident records for the period 1997-1999. More specifically; a combination of weighting values, respectively 1 for each light injury, 3 for each serious injury and 5 for each deadly injury (1_3_5), is used to rank and select the most dangerous accident locations. In the first part of this paper a sensitivity analysis is performed to investigate the influence of the number of passengers on the ranking of the accident locations. Secondly, the use of Bayesian ranking plots in order to visualize the probability that a location will be ranked as dangerous, based on estimates from a hierarchical Bayes model is evaluated. Results show that giving weight to the severity of the accident instead of to all the injured occupants of the vehicle does have important consequences for the selection and ranking of dangerous accident locations. Government should therefore carefully decide whether to rank accident locations by means of the severity of the accident or the severity of the injured occupants. Secondly, probability plots can provide policy makers with an graphical instrument to select dangerous road locations on a statistically sound basis.
Among all crashes involving cyclists, a motorist approaching a cyclist on a shared lane from behind is particularly dangerous and likely to result in serious injuries and fatalities. Previous research has highlighted that inadequate lateral distance and high vehicle speed are among the main contributing factors of crashes involving cars overtaking cyclists. Since new technology innovations offer the potential to increase safety and mobility, a driving simulator study was conducted to evaluate the safety effects of an advanced driver-assistance system (ADAS) for cyclist overtaking. The ADAS was composed by a multimodal human-machine interface (HMI) using a multistage collision warning system, informing drivers well in advance about the potential danger so that an imminent cyclist collision can be avoided. Three warning priority phases were defined: (1) normal, (2) danger, and (3) avoidable accident. Both visual and acoustic signals were used to warn drivers. A combination of Lateral Clearance (LC) and Time-To-Danger (TTD) parameters was used as ADAS activation criterion. A general linear model showed a positive effect on the lateral clearance of the following variables: presence of the ADAS system, familiarity with the system, male gender, driving experience as car driver, and driving experience as cyclist. A negative effect was associated with the following variables: cyclist manoeuvring from the edge of the lane to the centre of the lane, cyclists riding in parallel, driver's age, and self-reported aggressive driving. In conclusion, the drivers' characteristics affected the LC and the ADAS significantly increased LC, indicating a positive safety effect on cyclist overtaking by cars. No significant effect on speed during overtaking was observed between the condition with or without ADAS, although it was observed that men drove on average faster than women. ; Part of this work has received funding from the European Union's Horizon 2020 research and 411 innovation programme under grant agreement No 814761.
The Flemish government decided in 2001 to lower speed limits from 90 to 70 km/h at different regional roads. This study examines the effectiveness of this measure, through the application of a before-after study with a comparison group. A total of 61 road sections with a length of 116 km were included. At the majority of these road sections the speed limit was restricted in 2001 or 2002. The comparison group consisted of road sections with an unchanged speed limit of 90 km/h during the total research period. From this, 19 road sections were selected, with a total length of 53 km. Taking trend into account, the analyses show a 5 percent decrease in the crash rates after the speed restriction. This result is not significant, however upper bound is close to 1. Crashes with serious injuries and fatalities showed a decrease of 9%, also non-significant. Separate analyses were executed for crashes that occurred at intersection and at road sections. Those analyses showed a higher effectiveness of the speed restriction at road sections, both for injury crashes and more severe crashes. Also a higher effectiveness was found for the severe crashes compared to the injury crashes.
Road transport is vital to the economic development, trade and social integration. However, it is also responsible for the majority of negative impacts on environment and society. To achieve sustainable development, there is a growing need for a country to assess its undesirable costs so as to determine its road transport policy. In this study, total energy consumption, greenhouse gas emissions, as well as the number of fatalities in the European road transport are selected representing the level of sustainable development in each member state of the European Union (EU). With data from the period of 1995-2007, the extent to which the 27 EU countries have improved their 'productivity' on sustainable road transport is evaluated based on data envelopment analysis (DEA) and Malmquist productivity index, which measures the productivity change over time, and can be further decomposed into two components: the change in efficiency and the technical change. The results show a considerable progress towards the sustainable road transport in Europe during this period. The decomposition into the two components further revealed that the bulk of the improvement was attained through the adoption of productivity-enhancing new technologies throughout the road transport sector, rather than through the relatively inefficient countries catching up with those efficient ones. In addition, the growth in both two aspects slowed down in 2007, which implies the momentum of further improvement is in danger of being lost so that new impetus is needed.
Gedurende de voorbije decennia zijn er wereldwijd heel wat initiatieven ondernomen om de verkeersonveiligheid terug te dringen. Maar ondanks deze inspanningen blijft het aantal ongevallen en verkeersslachtoffers onverantwoord hoog. Om de verkeersveiligheid te verhogen worden daarom doelstellingen vooropgesteld en maatregelen genomen. De vooropgestelde reductie van het aantal verkeersongevallen en –slachtoffers binnen een bepaalde tijdspanne werkt vaak als een extra motivatie voor de betrokken partijen om nog bijkomende inspanningen te leveren en een concreet verkeersveiligheidsprogramma op te stellen en acties te ondernemen. Om de vooropgestelde doelstellingen in Vlaanderen te bereiken, heeft de Vlaamse overheid een Verkeersveiligheidsplan Vlaanderen (Departement Mobiliteit en Openbare Werken, 2008) opgesteld waarin 33 verkeersveiligheidsmaatregelen werden voorgesteld. Deze beleidsaanpak moet er voor zorgen dat het aantal doden en zwaargewonde verkeersslachtoffers teruggedrongen wordt tot een maximum van 250 doden en 2 000 zwaargewonden tegen 2015 (Departement Mobiliteit en Openbare Werken, 2008). In 2020 zouden deze aantallen nog verder gedaald moeten zijn tot 200 doden en 1 500 zwaargewonden (Vlaanderen in Actie, 2011). In dit onderzoek wordt een model voor Vlaanderen ontwikkeld dat ons in staat stelt om het effect op de verkeersveiligheid in Vlaanderen te kwantificeren wanneer we een set van regionale en lokale maatregelen doorrekenen. De methodologie draagt er toe bij dat enerzijds inzicht verkregen wordt in de mate waarin de voorgestelde maatregelen bijdragen tot het bereiken van de vooropgestelde verkeersveiligheidsdoelstellingen en dat anderzijds maatregelen tegenover elkaar kunnen afgewogen worden. Meer concreet worden in dit Vlaamse rekenmodel op een stapsgewijze manier de effecten van een maatregelenpakket doorgerekend. De toepassing richt zich op een set van zes verkeersveiligheidsmaatregelen uit het Verkeersveiligheidsplan Vlaanderen (Departement Mobiliteit en Openbare Werken, 2008) die op regionale of lokale schaal op wegvakken geïmplementeerd worden. Bovendien wordt er een uitsplitsing gemaakt naar drie wegtypes: autosnelwegen, gewestwegen en gemeentewegen. De methodologie bestaande uit 5 stappen is gebaseerd op Reurings et al. (2009). (1) In de eerste stap van het model wordt de verkeerssituatie en de verkeersveiligheidssituatie in het referentiejaar (2007) beschreven. (2) Daarna wordt de baselineprognose uitgewerkt waarin het aantal letselongevallen, doden, zwaar- en lichtgewonden berekend wordt voor de periode 2008 tot 2015 wanneer er enkel rekening wordt gehouden met de veranderingen van de verkeersprestatie en de autonome verandering van het risico. (3) In de maatregelprognose worden, naast deze twee aspecten, ook de effecten van het maatregelpakket in rekening gebracht. (4) Dit leidt tot een voorspelling van het aantal bespaarde letselongevallen, doden en zwaar- en lichtgewonde slachtoffers op wegvakken in Vlaanderen in 2015 berekend in geval een maatregelpakket (bestaande uit zes maatregelen) wordt geïmplementeerd tussen 2008 en 2015. (5) Op basis van de besparingen en de investeringskosten wordt een kosten-batenanalyse geïllustreerd. Graag willen we benadrukken dat de beschrijving van de methodologie en de inventarisatie van de datanoden de belangrijkste focus van deze studie is. Daarnaast wordt in dit rapport het model zo goed mogelijk geïmplementeerd aan de hand van een illustratie die gebaseerd is op de meest recente datasets die ter beschikking waren toen de studie van start ging (eind 2010). Omdat de resultaten van deze illustratieve doorrekening sterk beïnvloed worden door de vele aannames die (moeten) gebeuren doorheen het rekenproces, willen we extra benadrukken dat de bekomen resultaten enkel een richting aangeven en zeker geen enkele getalmatige waarde hebben. De illustratie is dus een 'proof of concept'. In het algemeen kunnen we besluiten dat dit rekenmodel veel mogelijkheden biedt voor beleidsmakers om hun beleid te optimaliseren en af te stemmen op de vooropgestelde verkeersveiligheidsdoelstellingen. Ondanks de relatief ver gevorderde uitwerking van het model zijn er enkele aspecten waarmee men rekening dient te houden bij toekomstig onderzoek en gebruik. Hierbij denken we aan het hoge detailniveau van de gebruikte datasets, de gedetailleerde beschrijving van de geplande maatregelen, de beperkte beschikbaarheid van (gedetailleerde) Vlaamse informatie over de effectiviteit van maatregelen en het ongevallenprofiel. Eén van de grote uitdagingen voor deze methodologie zou de implementatie zijn in een GIS-applicatie. ; In the last few decades, many initiatives were taken world-wide to reduce traffic unsafety. However, in spite of these efforts the number of accidents and traffic casualties remains inordinately high. Therefore targets are set and measures are taken to increase traffic safety. The aimed reduction of the number of traffic accidents and casualties within a certain time frame often constitutes an extra motivation for concerned parties to make additional efforts and draw up a concrete road safety plan and take action. To meet the targeted objectives in Flanders, the Flemish government has formulated the Road Safety Plan Flanders (Department Mobility and Public Works, 2008) in which 33 road safety measures were presented. This policy has to ensure that the number of fatalities and seriously injured are pushed back to a maximum of 250 fatalities and 2,000 seriously injured in 2015 (Department Mobility and Public Works, 2008). In 2020, these numbers have to be reduced even further to 200 fatalities and 1,500 seriously injured (Flanders in Action, 2011). In this research, a model for Flanders is developed which enables us to quantify the impact on traffic safety in Flanders when considering a set of regional and locational measures. On the one hand, the used methodology allows us to gain insight in the degree to which the planned measures will contribute to meet the targeted road safety objectives and on the other, it allows us to compare measures with each other. More specifically, in this Flemish computational model, the impact of a set of measures is calculated step by step. The application focuses on a set of six road safety measures from the Road Safety Plan Flanders (Department Mobility and Works, 2008) which are being implemented on road segments on a regional or locational scale. Moreover, a distinction is made between three road types: highways, secondary roads and local roads. The methodology, which consists of 5 steps, was based on Reurings et al. (2009). (1) In the first step of the model a description is given of the traffic situation and the traffic safety situation in the reference year (2007). (2) Subsequently, the baseline prognosis is made. In this prognosis the number of injury accidents, fatalities, and seriously and slightly injured casualties is calculated for the period from 2008 until 2015, only taking into account changes in the number of vehicle kilometres and the autonomous risk change. (3) In addition to these two aspects, the measure prognosis also takes into account the impact of the set of measures. (4) This leads to a prediction of the reduction of injury accidents, fatalities and seriously and slightly injured casualties on road segments in Flanders in 2015, calculated based on the implementation of a set of measures (consisting of six measures) between 2008 and 2015. (5) Based on savings and investment costs, a cost-benefit analysis is illustrated. We would like to emphasize that the main focus of this study lies in the description of the methodology and an inventory of data needs. In this report the model is moreover implemented as well as possible by means of an illustration based on the most recent data sets which were available at the start of the study (end of 2010). Since the results of this illustrative calculation are strongly influenced by the many assumptions that had to be taken throughout the computational process, we want to explicitly emphasize that the obtained results only indicate a direction and should by no means be taken literally. The illustration is therefore a 'proof of concept'. In general we can conclude that this computational model offers a lot of opportunities for policymakers to optimize and attune their policy to the targeted road safety objectives. Despite the relatively advanced development of the model, there are some aspects which have to be taken into account in future research and use. Examples are the high level of detail of the used data sets, the detailed description of the planned measures and the limited availability of (detailed) Flemish information on the effectiveness of measures and accident profiles. One of the big challenges for this methodology would be its implementation in a GIS-application.
