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Analysis of the impact of population ageing and territorial factors on crosstown roads safety: the Spanish case study
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Transportation Research Procedia 00 (2018) 000–000
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Transportation Research Procedia 33 (2018) 283–290 www.elsevier.com/locate/procedia
XIII Conference on Transport Engineering, CIT2018 XIII Conference on Transport Engineering, CIT2018
Analysis of the impact of population ageing and territorial factors on Analysis ofcrosstown the impactroads of population andcase territorial safety: theageing Spanish study factors on crosstown roads safety: athe Spanish case study a Natalia Casado-Sanz *, Begoña Guirao Natalia Casado-Sanza *, Begoña Guiraoa Universidad Politécnica de Madrid, ETSI Caminos, Avda. Profesor Aranguren, s/n. 28040 Madrid, Spain
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Universidad Politécnica de Madrid, ETSI Caminos, Avda. Profesor Aranguren, s/n. 28040 Madrid, Spain
Abstract Abstract The recent spike in the accident rate of urban Spanish roads, after years of negative growth, has been accompanied by a serious increase in spike accidents in accident a specificrate type road:Spanish crosstown roads (called Spanish). in 2013, thereby was a 47% The recent in the of of urban roads, after years “travesías” of negativeingrowth, has Thus, been accompanied a serious increase in in accidents accidents inwith casualties overroads 2012(called data; in 2014, anin88% increase over previous yeara 47% and, increase a specific typeinof these road: routes crosstown “travesías” Spanish). Thus, in the 2013, there was although 2015 data reflect a slight decline (-3%), figures are still worrying. Moreover, these routes have always shown a higher increase in accidents with casualties in these routes over 2012 data; in 2014, an 88% increase over the previous year and, fatality thandata the reflect rest of aurban althoughrate 2015 slightroads. decline (-3%), figures are still worrying. Moreover, these routes have always shown a higher fatality rate than the rest of urban roads. The road safety analysis of these routes is complicated due to the diversity of the features, the dispersion of the data and the complete related literature. The main target of this the road of safety characterization of theseofspecific in The road lack safetyofanalysis of these routes is complicated duepaper to theisdiversity the features, the dispersion the dataroutes and the order to explain why the accidents in these routes happen, their severity and their relation with the ageing process in Spain, where complete lack of related literature. The main target of this paper is the road safety characterization of these specific routes in in 2012 the population 65 years old was 17%, this ratio even in smallwith cities. GeneralinDirectorate of order to explain why theover accidents in these routes happen, their being severity andhigher their relation theSpanish ageing process Spain, where Traffic providedover database (2006-2013) on accident andhigher the methodology was focused on cluster analysis, in 2012 (DGT) the population 65 years old was 17%, this ratio statistics being even in small cities. Spanish General Directorate of identifying 3 homogeneous groups (2006-2013) of crosstown on roads. With the final clusters, behaviour patterns on towards road safety Traffic (DGT) provided database accident statistics and the different methodology was focused cluster analysis, were modelled and analysed,groups payingofspecial attention to With “vulnerable road users” different (according to DGT patterns definition). Results revealed identifying 3 homogeneous crosstown roads. the final clusters, behaviour towards road safety the clear influence of the age variable in two of the clusters, but also some shortcomings in the database, which collects were modelled and analysed, paying special attention to “vulnerable road users” (according to DGT definition). Results revealed information on someof routes that do not fulfil the conditions to be considered “passing routes”. in the database, which collects the clear influence the age variable in two of the clusters, but also some shortcomings
information on some routes that do not fulfil the conditions to be considered “passing routes”. © 2018 The Authors. Published by Elsevier Ltd. © 2018 The Authors. by Elsevier Ltd. This is an open accessPublished article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) © 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the license scientific committee of the XIII Conference on Transport Engineering, This is an open access article under the CC BY-NC-ND license Selection and peer-review under responsibility of the scientific(https://creativecommons.org/licenses/by-nc-nd/4.0/) committee of the XIII Conference on Transport Engineering, CIT2018. Selection and peer-review under responsibility of the scientific committee of the XIII Conference on Transport Engineering, CIT2018. CIT2018. Keywords: road safety; crosstown roads; population ageing; territorial factors; cluster analysis Keywords: road safety; crosstown roads; population ageing; territorial factors; cluster analysis * Corresponding author. Tel.: +34-91-366-6784; fax: +34-91-366-6656. E-mail address: [email protected] * Corresponding author. Tel.: +34-91-366-6784; fax: +34-91-366-6656. E-mail address: [email protected]
2352-1465 © 2018 The Authors. Published by Elsevier Ltd. This is an open access under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) 2352-1465 © 2018 Thearticle Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of the scientific of the XIII Conference on Transport Engineering, This is an open access article under the CC BY-NC-ND licensecommittee (https://creativecommons.org/licenses/by-nc-nd/4.0/) CIT2018. Selection and peer-review under responsibility of the scientific committee of the XIII Conference on Transport Engineering, CIT2018.
2352-1465 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of the XIII Conference on Transport Engineering, CIT2018. 10.1016/j.trpro.2018.10.104
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1. Introduction Currently, road traffic accidents represent a problem of great social and economic impact. The World Health Organization (2015) points out that about 1.25 million people die each year as a result of road traffic accidents. The progress taking place in recent years in road safety is evident, but not enough. Although they have reduced since 2007, they are still too high. These figures place the road accident rate as the eighth worldwide cause of death and if we do not take urgent measures, traffic accidents will become the fifth worldwide cause of death in the year 2030. In the European Union, 26,112 road fatalities were reported in 2015. This means 5,400 fewer deaths in 2015 than in 2010. The EU has the lowest fatality rate for any region in the world with 51 dead per million inhabitants (European Commission, 2015). Spain, with a current rate of 3.6 per 100,000 inhabitants, ranks sixth in the countries with the lowest fatality rate. It has already achieved its 2020 road safety target of less than 37 fatalities per million inhabitants. There were 1,689 road deaths in 2015, a 32% reduction from 2010. However, despite the fact that the number of fatalities has decreased in recent years, there are more accidents, with the consequent risk of accidents with fatalities. In relation to the type of road, the Trans-European Road Network (TEN-T), consisting mainly of motorways, is comparatively safe. Only around 8% of fatalities are caused on these roads (European Commission, 2015). Another 38% of all fatalities are inside urban areas. This share has slightly increased over time. The majority of accidents (54%) take place on inter-urban two-lane roads (European Commission, 2015). This is one of the greatest problems specific to Spain. In Spain, one type of road, which has one of the higher accident rates, is the crosstown road (called “travesía” in Spanish), which has a greater risk than the rest. In these kinds of roads, traffic conflicts are extremely significant. The path of the road through the urban core produces issues both for the population, which withstands environmental impacts and high levels of risk, as well as for through traffic, which is forced to follow highly congested itineraries. The fact that motorized vehicles coexist with pedestrians produces a very high accident rate (Instituto MAPFRE, 2004). Pedestrians are the most vulnerable group of road users, especially children and elderly people, so it is essential to take them into account in road planning. In the Spanish State Road Network there are more than 1,000 crosstown roads, with a total length of approximately 1,000 kilometres. They account for 2% of all fatalities and serious traffic injuries in Spain. Its lethality rate for the year 2015 was 2.1, while in the rest of urban roads it was 0.5. In 2015, there were 1,403 accidents, in which 41 people died, 167 were injured and hospitalised and 1,752 were injured and not hospitalised (DGT, 2015). These numbers represent reductions compared to 2014. However, they are still far from the figures reached in 2011 and 2012. The causes of the high accident rate in this type of roads are not yet clarified and understanding them is a fundamental step to reduce accidents. On the one hand, socioeconomic, population and territorial factors (together with infrastructure and mobility levels) are, in advance, the most decisive influencers in the accident rate of these roads. However, the lack of studies and literature published in that regard, demonstrates the necessity of a methodology of corroborated analysis. On the other hand, within the population factors ageing is especially important in the investigation of the possible causes of traffic accidents, since it is a key factor in the production of accidents. Additionally, population life expectancy is increasing year on year. This increase is associated with the ageing of the population, as well as a rise in the number of driving licenses among the elderly population group. People over 65 constitute the age group with the most fatalities. Their mortality rate is five times higher than the population average and their injury rate is two times higher than the rest. It is a fact that invites us to think about the influence of population ageing on the road accident rate. In order to describe the research as a whole, this paper has been divided into the following parts: first, an introduction with the context and the main aims of the paper while section 2 is a review of the literature. Section 3 provides details of the methodology used and section 4 describes the results and contains a discussion of the case studied. Finally, the main research conclusions are in section 5.
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2. Background: Segmentation of accidents and epidemiological studies As we have shown in the first section, road accidents and particularly urban accidents are one of the most important negative impacts produced by the act of travelling (Postorino and Sarnè, 2002). In recent years, economic improvement and the high level of urbanization have led to a substantial increase of the urban population and, as a result of this fact, journeys between urban and rural villages are increasing (Wu and Deng, 2013). This is a very important problem in many countries in the world, because the main fatality accidents occur between urban and rural areas. The Spanish General Directorate of Traffic (DGT), in its Road Safety Strategic Plan 2011-2020, underline the objective of reviewing the crosstown roads and developing specific technical recommendations to improve road safety for vulnerable users. At present, little research has been devoted to the study of accident causation in crosstown roads. Several research studies on road accident data analysis consist in using several methods such as statistical techniques, mathematical models, data mining and machine learning techniques (Kwon et al., 2015). Traffic accidents are unexpected events and analyzing them requires knowing the particularities that characterize them. Heterogeneity is one of the principal issues of accident data modelling procedures (Elias et al., 2006). If we do not keep this fact in mind during the analysis, we may not detect certain connections between data. Therefore, it is useful to reduce heterogeneity by segmenting the data (Depaire et al., 2008). For this reason, statistical clustering techniques or cluster analysis have been used successfully in the field of road safety, to help in the segmentation of traffic accidents. There are many examples of studies of this type that relate the attributes of traffic and the environment of a section or type of road with its road accident rate, although there is no known relation with crosstown roads. Pardillo-Mayora et al. (2010) have already used cluster techniques in the analysis of the accident rate of Spanish two-lane rural roads. In a recent study, genetic algorithms have been applied in a cluster analysis to a data set of the road traffic accidents recorded in Christchurch, New Zealand (Saharan and Baragona, 2017). In addition, latent class clustering has also been used to study the severity of traffic accidents (De Oña et al., 2017). This particular type of cluster analysis has some important advantages over other types of cluster analysis methods. It also provides several statistical criteria to help us decide the most appropriate number of clusters (Magidson and Vermunt, 2002). In relation to the accident location, conglomerate analysis has also been used to classify urban and suburban areas in order to analyze the influence of drivers’ age on accidents in the state of Indiana (Karlaftis and Tarko, 1998). Likewise, combining cluster analysis, geographic information systems and negative binomial distributions developed an algorithm to estimate the number of accidents and evaluate their risk in a specific area (Ng, Hung and Wong, 2002). In this same direction, another paper was published a year later where one and two-dimensional clustering techniques for road accidents were compared to define road-accident black zones within urban agglomerations. Afterwards, in a later study, Wong et al. (2004) proposed a technique to assess the consequence of a group of road safety strategies introduced in Hong Kong, using a cluster analysis to group the different programs into smaller groups. On the other hand, epidemiological studies have shown that road traffic accidents display different patterns according to gender, age, social group and risk area, revealing increased vulnerability for individuals and places (Spoerri et al., 2011). There are even examples of the application of cluster techniques in studies of accidents of pedestrians in the USA, in which age is revealed as a significant determining sociodemographic variable. Also police-reported accident data from North Carolina has been used to analyse age and pedestrian injury severity in motor vehicle accidents using a heteroskedastic logit analysis (Kim et al., 2008). In the province of Modena, the elderly and street safety have been analysed, obtaining as a result that the relationship between old people and road traffic seems to be worse in the small towns situated in hill/mountain areas (Ranzi et al., 2000).
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Therefore, given the success of these studies and the application of cluster analysis techniques to explain and obtain a thorough knowledge of accident causation, this statistical procedure has been selected in order to group the accidents that have taken place in crosstown roads between the years 2006 and 2013 to find their origin and to establish strategies. 3. Data and methodology Due to the success of the application of statistical techniques of grouping based on the conglomerate analysis in the field of road safety, the hierarchical clustering method has been selected. This method has been useful to relate the attributes of traffic and the environment of a type of road with its road accident rate, as well as to obtain thorough knowledge of the accident casuistry. Cluster analysis is a multivariate technique whose main goal is to group objects forming conglomerates (Rodríguez and Mora, 2001; Aldenderfer and Blashfield, 1984). The methodology applied consisted, at first stage, in selecting the individuals under study, which in this case were the fatalities that happened in crosstown roads between 2006 and 2013. This data has been obtained from the Statistics Accident Database provided by the Spanish General Directorate of Traffic (DGT). It is based on the information collected in accident statistics questionnaires and structured in three groups: a first group referring to the general accident data; a second group related to the vehicle data; and finally, a third group associated with the data of the people involved in the accident. Each element of the sample is an accident which happened in a specific village. After this process, a total of five sociodemographic variables that characterized the sample were selected: the population size, the unemployment rate, the Gross Domestic Product (GDP) per capita, the number of inhabitants over 65 years old and the age of injured drivers. These variables were obtained from the National Institute of Statistics Database (INEbase), which contains statistics about demography, economy and Spanish society. In order to obtain more representative results and to make it easier to interpret them, it was necessary to encode the variables, so that all of them were on the same scale. The scale considered consists of five values (1, 2, 3, 4 and 5). Table 1 provides a characterization of the data used for this study. The sample was formed by 298 accidents. Table 1. Variables used and sample characterization Number
Variables
1
Population size
2
Unemployment rate
3
Per capita income
4
Inhabitants over 65
5
Age of injured drivers
Code 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
Value > 100,000 inhabitants 50,000-100,000 inhabitants 5,000-50,000 inhabitants 1,000-5,000 inhabitants < 1,000 inhabitants >25% 20-25% 15-20% 10-15% <10% > 40,000€ 30,000-40,000€ 20,000-30,000€ 10,000-20,000€ <10,000€ >35,000 inhabitants 20,000-35,000 inhabitants 5,000-20,000 inhabitants 1,000-5,000 inhabitants <1,000 inhabitants >65 years old 55-65 years old 40-54 years old 25-39 years old <25 years old
Total 42 28 125 101 2 35 39 100 63 61 4 13 189 92 0 5 28 55 102 108 59 35 59 89 56
Percentage of the sample 14.1% 9.4% 41.9% 33.9% 0.7% 11.7% 13.1% 33.6% 21.1% 20.5% 1.3% 4.4% 63.4% 30.9% 0.0% 1.7% 9.4% 18.5% 34.2% 36.2% 19.8% 11.7% 19.8% 29.9% 18.8%
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Prior to the application of the cluster analysis, a first assessment of the sample was carried out in order to characterize it. In relation to the spatial location of these accidents, it was noticed that there is a high concentration of accidents in Catalonia and Galicia, specifically along the coastline of both regions. Figure 1 shows the accident map of accidents with fatalities which happened between 2006 and 2013.
Fig. 1. Road accident map of accidents with fatalities occurred in Spanish crosstown roads in the period between 2006 and 2013.
As to the age of the deceased, there is a high percentage of victims over 65 (32%), while the percentage of the under-25 age group has been decreasing in recent years, reaching a minimum in the year 2013. Regarding the different types of users, the vast majority of the deceased were pedestrians and people over 65 years of age. In figure 2 we can observe the evolution of the average age of the people who died in this kind of routes.
Fig. 2. Evolution of the percentage of fatalities per age group in Spanish crosstown roads in the period between 2006 and 2013.
Additionally, in relation to the population size, most of the accidents took place in villages, which have a population size between 5,000 and 15,000 inhabitants. Furthermore, the existence of a fairly large group of towns of more than 100,000 inhabitants in which bypass roads have not yet been built (38 cases) is striking. These accidents took place in fully urban stretch of road, old crosstown roads that were not properly integrated into the urban fabric and remained with local utility after the branch off due to the construction of the bypass road, for which it is recommended to review the type of signalling present in them, the dimensions of the sidewalk, the current use of these streets, their traffic and their role in the city urban fabric. Once an initial analysis of the data was completed, the cluster techniques were applied. The software used for the development of the statistical analysis was the SPSS Statistics v24.0.0. The method selected was the hierarchical clustering analysis (HCA). This method was chosen because it is the most suitable when the number of clusters is not known in advance and the sample size is not very large. Euclidean distance squared was selected as a measure of proximity between individuals. As a result, three clearly distinguished accident groups were obtained.
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4. Results and discussion The first group obtained consists of 43 accidents and populations of 100,000 inhabitants. The number of victims amount to 87, most drivers. The unemployment rate ranged between 15% and 20% and the Gross Domestic Product (GDP) per capita between 20,000 and 30,000 euros. There is also a high number of people over 65 years old (between 20,000 and 35,000 inhabitants). In this group the victims that predominate are those between 40 and 54 years old. These are fully urban road stretches, old crosstown roads that have not been adequately fitted out after building the bypass road. Most of these accidents took place in the city of Barcelona and in the surrounding towns. This group of routes is not relevant to our study, although it is true that the DGT should review it and try to add this data to urban road data set and avoid being labeled as crosstown roads. In figure 3 we can see the accident map.
Fig. 3. Road accident map of Group 1 (left figure) and Group 2 (right figure)
The second group (group 2) is made up of 147 accidents and 294 victims. The size of the affected population was between 5,000 and 50,000 inhabitants, with an unemployment rate ranging between 10% and 20%. This group consists of young victims (53% of them are under 30 years old). These accidents are located geographically on the Spanish east, especially the part of Catalonia closest to the Mediterranean coast. These accidents may be due to the fact that in the Levante, the eastern region of the Iberian Peninsula, on the Spanish Mediterranean coast, there is a lot of youth night driving, with alcohol and drugs. Most of the victims are the drivers of the vehicles and 30% of the accidents took place between 10:00 p.m. and 5:00 a.m. Figure 3 shows the accident map of the second group. Finally, cluster 3 consists of 108 accidents and 216 fatalities. Accidents in this group have occurred in populations between 5,000 and 50,000 inhabitants, with an unemployment rate between 10% and 20%. In addition, 35% of the total victims are people over 65 years old. As well 23.2% of the victims were pedestrians. Most of the accidents happened in towns, which are in the interior of the Iberian Peninsula, and this is a very complex interpretation, since the causes of accidents in this case can be very diverse. In figure 4, the accident map is shown.
Fig. 4. Road accident map of Group 3 (cluster analysis).
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As we can observe in the results obtained, the most vulnerable users were those over 65 years old and the majority of them were pedestrians. As shown in Figure 5, keeping in mind all kind of users, we observe that the elderly group died more than the rest, for the period between 2006 and 2013.
Fig. 5. Age groups of fatalities in Spanish crosstown roads (all type of users: drivers, pedestrians and passengers). Absolute values.
Additionally, the most frequent types of accident in this age group were pedestrian accidents and front side collision (see Figure 6). Also the most frequent infraction made by drivers over 65 years of age was distracted driving, while the most frequent infringement by pedestrians was due to crossing the road not according to the rules.
Fig. 6. Most frequent type of accident in Spanish crosstown roads for the age group over 65 years old
5. Conclusions and recommendations To sum up, in the cluster analysis the high accident rate of two vulnerable groups of users was reflected: the elderly group and the young. Demographic growth of people over 65 years old has had a significant impact on the field of transport and road safety. This group often drives older vehicles and has cognitive, sensory or motor impairments that progressively modify their ability to drive. This fact places them at a disadvantage in case of collision, due to their physical fragility. In addition, the accident rate of those under 30 was principally due to alcohol and drugs. Likewise, it has been detected that accidents in fully urban road stretches, corresponding to old crosstown roads that have not been properly fitted out after constructing the bypass road. This particular group should be reviewed in order to avoid incorrectly classifying these routes. It would be advisable to create strategic action plans for each region that has been affected. This could be useful and would provide us with guidelines to act on them and integrate this kind of routes into the urban structure when it becomes obsolete, increasing road safety and reducing risk of accidents for both pedestrians and other road users.
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Further research into the cluster attributes and identified patterns is needed to investigate to a greater extent how these factors can be mitigated to reduce the risk of severe injuries. Also other variables related with infrastructure and mobility levels, such as the crosstown roads layout, the traffic intensity or the road consistency, might be considered. It would also be necessary to create new clusters with variables, as well as to make use of other methodologies (latent cluster, K-means clustering) to try to identify better solutions for improving safety. Finally, it should be noted that the numbers of fatalities in crosstown roads have reduced in recent years but they are still too high. Additionally, there is still a long way to reach the aim of zero accidents. The current conclusions of this study are only a starting point for a future line of research with the intention of investigating more thoroughly the causation of accidents which happen in crosstown roads with the purpose of achieving a reduction of accidents in this type of road. Acknowledgements This paper shows the first part of the results of a research sponsored and funded by the Spanish General Directorate of Traffic (DGT) as part of the Subsidy Programme for the development of research projects in the area of traffic, mobility and road safety for the year 2017. This project has been referenced with the administrative code SPIP2017-02199. The authors are also grateful to DGT for providing the data necessary for this research. References De Oña, J., López, G., Mujalli, R., Calvo, F. (2013). Analysis of traffic accidents on rural highways using Latent Class Clustering and Bayesian Networks. Accident Analysis & Prevention, 51, 1-10 Depaire, B., Wets, G., Vanhoof, K. (2008). 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XIII Conference on Transport Engineering, CIT2018 XIII Conference on Transport Engineering, CIT2018
Analysis of the impact of population ageing and territorial factors on Analysis ofcrosstown the impactroads of population andcase territorial safety: theageing Spanish study factors on crosstown roads safety: athe Spanish case study a Natalia Casado-Sanz *, Begoña Guirao Natalia Casado-Sanza *, Begoña Guiraoa Universidad Politécnica de Madrid, ETSI Caminos, Avda. Profesor Aranguren, s/n. 28040 Madrid, Spain
a a
Universidad Politécnica de Madrid, ETSI Caminos, Avda. Profesor Aranguren, s/n. 28040 Madrid, Spain
Abstract Abstract The recent spike in the accident rate of urban Spanish roads, after years of negative growth, has been accompanied by a serious increase in spike accidents in accident a specificrate type road:Spanish crosstown roads (called Spanish). in 2013, thereby was a 47% The recent in the of of urban roads, after years “travesías” of negativeingrowth, has Thus, been accompanied a serious increase in in accidents accidents inwith casualties overroads 2012(called data; in 2014, anin88% increase over previous yeara 47% and, increase a specific typeinof these road: routes crosstown “travesías” Spanish). Thus, in the 2013, there was although 2015 data reflect a slight decline (-3%), figures are still worrying. Moreover, these routes have always shown a higher increase in accidents with casualties in these routes over 2012 data; in 2014, an 88% increase over the previous year and, fatality thandata the reflect rest of aurban althoughrate 2015 slightroads. decline (-3%), figures are still worrying. Moreover, these routes have always shown a higher fatality rate than the rest of urban roads. The road safety analysis of these routes is complicated due to the diversity of the features, the dispersion of the data and the complete related literature. The main target of this the road of safety characterization of theseofspecific in The road lack safetyofanalysis of these routes is complicated duepaper to theisdiversity the features, the dispersion the dataroutes and the order to explain why the accidents in these routes happen, their severity and their relation with the ageing process in Spain, where complete lack of related literature. The main target of this paper is the road safety characterization of these specific routes in in 2012 the population 65 years old was 17%, this ratio even in smallwith cities. GeneralinDirectorate of order to explain why theover accidents in these routes happen, their being severity andhigher their relation theSpanish ageing process Spain, where Traffic providedover database (2006-2013) on accident andhigher the methodology was focused on cluster analysis, in 2012 (DGT) the population 65 years old was 17%, this ratio statistics being even in small cities. Spanish General Directorate of identifying 3 homogeneous groups (2006-2013) of crosstown on roads. With the final clusters, behaviour patterns on towards road safety Traffic (DGT) provided database accident statistics and the different methodology was focused cluster analysis, were modelled and analysed,groups payingofspecial attention to With “vulnerable road users” different (according to DGT patterns definition). Results revealed identifying 3 homogeneous crosstown roads. the final clusters, behaviour towards road safety the clear influence of the age variable in two of the clusters, but also some shortcomings in the database, which collects were modelled and analysed, paying special attention to “vulnerable road users” (according to DGT definition). Results revealed information on someof routes that do not fulfil the conditions to be considered “passing routes”. in the database, which collects the clear influence the age variable in two of the clusters, but also some shortcomings
information on some routes that do not fulfil the conditions to be considered “passing routes”. © 2018 The Authors. Published by Elsevier Ltd. © 2018 The Authors. by Elsevier Ltd. This is an open accessPublished article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) © 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the license scientific committee of the XIII Conference on Transport Engineering, This is an open access article under the CC BY-NC-ND license Selection and peer-review under responsibility of the scientific(https://creativecommons.org/licenses/by-nc-nd/4.0/) committee of the XIII Conference on Transport Engineering, CIT2018. Selection and peer-review under responsibility of the scientific committee of the XIII Conference on Transport Engineering, CIT2018. CIT2018. Keywords: road safety; crosstown roads; population ageing; territorial factors; cluster analysis Keywords: road safety; crosstown roads; population ageing; territorial factors; cluster analysis * Corresponding author. Tel.: +34-91-366-6784; fax: +34-91-366-6656. E-mail address: [email protected] * Corresponding author. Tel.: +34-91-366-6784; fax: +34-91-366-6656. E-mail address: [email protected]
2352-1465 © 2018 The Authors. Published by Elsevier Ltd. This is an open access under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) 2352-1465 © 2018 Thearticle Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of the scientific of the XIII Conference on Transport Engineering, This is an open access article under the CC BY-NC-ND licensecommittee (https://creativecommons.org/licenses/by-nc-nd/4.0/) CIT2018. Selection and peer-review under responsibility of the scientific committee of the XIII Conference on Transport Engineering, CIT2018.
2352-1465 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of the XIII Conference on Transport Engineering, CIT2018. 10.1016/j.trpro.2018.10.104
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1. Introduction Currently, road traffic accidents represent a problem of great social and economic impact. The World Health Organization (2015) points out that about 1.25 million people die each year as a result of road traffic accidents. The progress taking place in recent years in road safety is evident, but not enough. Although they have reduced since 2007, they are still too high. These figures place the road accident rate as the eighth worldwide cause of death and if we do not take urgent measures, traffic accidents will become the fifth worldwide cause of death in the year 2030. In the European Union, 26,112 road fatalities were reported in 2015. This means 5,400 fewer deaths in 2015 than in 2010. The EU has the lowest fatality rate for any region in the world with 51 dead per million inhabitants (European Commission, 2015). Spain, with a current rate of 3.6 per 100,000 inhabitants, ranks sixth in the countries with the lowest fatality rate. It has already achieved its 2020 road safety target of less than 37 fatalities per million inhabitants. There were 1,689 road deaths in 2015, a 32% reduction from 2010. However, despite the fact that the number of fatalities has decreased in recent years, there are more accidents, with the consequent risk of accidents with fatalities. In relation to the type of road, the Trans-European Road Network (TEN-T), consisting mainly of motorways, is comparatively safe. Only around 8% of fatalities are caused on these roads (European Commission, 2015). Another 38% of all fatalities are inside urban areas. This share has slightly increased over time. The majority of accidents (54%) take place on inter-urban two-lane roads (European Commission, 2015). This is one of the greatest problems specific to Spain. In Spain, one type of road, which has one of the higher accident rates, is the crosstown road (called “travesía” in Spanish), which has a greater risk than the rest. In these kinds of roads, traffic conflicts are extremely significant. The path of the road through the urban core produces issues both for the population, which withstands environmental impacts and high levels of risk, as well as for through traffic, which is forced to follow highly congested itineraries. The fact that motorized vehicles coexist with pedestrians produces a very high accident rate (Instituto MAPFRE, 2004). Pedestrians are the most vulnerable group of road users, especially children and elderly people, so it is essential to take them into account in road planning. In the Spanish State Road Network there are more than 1,000 crosstown roads, with a total length of approximately 1,000 kilometres. They account for 2% of all fatalities and serious traffic injuries in Spain. Its lethality rate for the year 2015 was 2.1, while in the rest of urban roads it was 0.5. In 2015, there were 1,403 accidents, in which 41 people died, 167 were injured and hospitalised and 1,752 were injured and not hospitalised (DGT, 2015). These numbers represent reductions compared to 2014. However, they are still far from the figures reached in 2011 and 2012. The causes of the high accident rate in this type of roads are not yet clarified and understanding them is a fundamental step to reduce accidents. On the one hand, socioeconomic, population and territorial factors (together with infrastructure and mobility levels) are, in advance, the most decisive influencers in the accident rate of these roads. However, the lack of studies and literature published in that regard, demonstrates the necessity of a methodology of corroborated analysis. On the other hand, within the population factors ageing is especially important in the investigation of the possible causes of traffic accidents, since it is a key factor in the production of accidents. Additionally, population life expectancy is increasing year on year. This increase is associated with the ageing of the population, as well as a rise in the number of driving licenses among the elderly population group. People over 65 constitute the age group with the most fatalities. Their mortality rate is five times higher than the population average and their injury rate is two times higher than the rest. It is a fact that invites us to think about the influence of population ageing on the road accident rate. In order to describe the research as a whole, this paper has been divided into the following parts: first, an introduction with the context and the main aims of the paper while section 2 is a review of the literature. Section 3 provides details of the methodology used and section 4 describes the results and contains a discussion of the case studied. Finally, the main research conclusions are in section 5.
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2. Background: Segmentation of accidents and epidemiological studies As we have shown in the first section, road accidents and particularly urban accidents are one of the most important negative impacts produced by the act of travelling (Postorino and Sarnè, 2002). In recent years, economic improvement and the high level of urbanization have led to a substantial increase of the urban population and, as a result of this fact, journeys between urban and rural villages are increasing (Wu and Deng, 2013). This is a very important problem in many countries in the world, because the main fatality accidents occur between urban and rural areas. The Spanish General Directorate of Traffic (DGT), in its Road Safety Strategic Plan 2011-2020, underline the objective of reviewing the crosstown roads and developing specific technical recommendations to improve road safety for vulnerable users. At present, little research has been devoted to the study of accident causation in crosstown roads. Several research studies on road accident data analysis consist in using several methods such as statistical techniques, mathematical models, data mining and machine learning techniques (Kwon et al., 2015). Traffic accidents are unexpected events and analyzing them requires knowing the particularities that characterize them. Heterogeneity is one of the principal issues of accident data modelling procedures (Elias et al., 2006). If we do not keep this fact in mind during the analysis, we may not detect certain connections between data. Therefore, it is useful to reduce heterogeneity by segmenting the data (Depaire et al., 2008). For this reason, statistical clustering techniques or cluster analysis have been used successfully in the field of road safety, to help in the segmentation of traffic accidents. There are many examples of studies of this type that relate the attributes of traffic and the environment of a section or type of road with its road accident rate, although there is no known relation with crosstown roads. Pardillo-Mayora et al. (2010) have already used cluster techniques in the analysis of the accident rate of Spanish two-lane rural roads. In a recent study, genetic algorithms have been applied in a cluster analysis to a data set of the road traffic accidents recorded in Christchurch, New Zealand (Saharan and Baragona, 2017). In addition, latent class clustering has also been used to study the severity of traffic accidents (De Oña et al., 2017). This particular type of cluster analysis has some important advantages over other types of cluster analysis methods. It also provides several statistical criteria to help us decide the most appropriate number of clusters (Magidson and Vermunt, 2002). In relation to the accident location, conglomerate analysis has also been used to classify urban and suburban areas in order to analyze the influence of drivers’ age on accidents in the state of Indiana (Karlaftis and Tarko, 1998). Likewise, combining cluster analysis, geographic information systems and negative binomial distributions developed an algorithm to estimate the number of accidents and evaluate their risk in a specific area (Ng, Hung and Wong, 2002). In this same direction, another paper was published a year later where one and two-dimensional clustering techniques for road accidents were compared to define road-accident black zones within urban agglomerations. Afterwards, in a later study, Wong et al. (2004) proposed a technique to assess the consequence of a group of road safety strategies introduced in Hong Kong, using a cluster analysis to group the different programs into smaller groups. On the other hand, epidemiological studies have shown that road traffic accidents display different patterns according to gender, age, social group and risk area, revealing increased vulnerability for individuals and places (Spoerri et al., 2011). There are even examples of the application of cluster techniques in studies of accidents of pedestrians in the USA, in which age is revealed as a significant determining sociodemographic variable. Also police-reported accident data from North Carolina has been used to analyse age and pedestrian injury severity in motor vehicle accidents using a heteroskedastic logit analysis (Kim et al., 2008). In the province of Modena, the elderly and street safety have been analysed, obtaining as a result that the relationship between old people and road traffic seems to be worse in the small towns situated in hill/mountain areas (Ranzi et al., 2000).
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Therefore, given the success of these studies and the application of cluster analysis techniques to explain and obtain a thorough knowledge of accident causation, this statistical procedure has been selected in order to group the accidents that have taken place in crosstown roads between the years 2006 and 2013 to find their origin and to establish strategies. 3. Data and methodology Due to the success of the application of statistical techniques of grouping based on the conglomerate analysis in the field of road safety, the hierarchical clustering method has been selected. This method has been useful to relate the attributes of traffic and the environment of a type of road with its road accident rate, as well as to obtain thorough knowledge of the accident casuistry. Cluster analysis is a multivariate technique whose main goal is to group objects forming conglomerates (Rodríguez and Mora, 2001; Aldenderfer and Blashfield, 1984). The methodology applied consisted, at first stage, in selecting the individuals under study, which in this case were the fatalities that happened in crosstown roads between 2006 and 2013. This data has been obtained from the Statistics Accident Database provided by the Spanish General Directorate of Traffic (DGT). It is based on the information collected in accident statistics questionnaires and structured in three groups: a first group referring to the general accident data; a second group related to the vehicle data; and finally, a third group associated with the data of the people involved in the accident. Each element of the sample is an accident which happened in a specific village. After this process, a total of five sociodemographic variables that characterized the sample were selected: the population size, the unemployment rate, the Gross Domestic Product (GDP) per capita, the number of inhabitants over 65 years old and the age of injured drivers. These variables were obtained from the National Institute of Statistics Database (INEbase), which contains statistics about demography, economy and Spanish society. In order to obtain more representative results and to make it easier to interpret them, it was necessary to encode the variables, so that all of them were on the same scale. The scale considered consists of five values (1, 2, 3, 4 and 5). Table 1 provides a characterization of the data used for this study. The sample was formed by 298 accidents. Table 1. Variables used and sample characterization Number
Variables
1
Population size
2
Unemployment rate
3
Per capita income
4
Inhabitants over 65
5
Age of injured drivers
Code 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
Value > 100,000 inhabitants 50,000-100,000 inhabitants 5,000-50,000 inhabitants 1,000-5,000 inhabitants < 1,000 inhabitants >25% 20-25% 15-20% 10-15% <10% > 40,000€ 30,000-40,000€ 20,000-30,000€ 10,000-20,000€ <10,000€ >35,000 inhabitants 20,000-35,000 inhabitants 5,000-20,000 inhabitants 1,000-5,000 inhabitants <1,000 inhabitants >65 years old 55-65 years old 40-54 years old 25-39 years old <25 years old
Total 42 28 125 101 2 35 39 100 63 61 4 13 189 92 0 5 28 55 102 108 59 35 59 89 56
Percentage of the sample 14.1% 9.4% 41.9% 33.9% 0.7% 11.7% 13.1% 33.6% 21.1% 20.5% 1.3% 4.4% 63.4% 30.9% 0.0% 1.7% 9.4% 18.5% 34.2% 36.2% 19.8% 11.7% 19.8% 29.9% 18.8%
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Prior to the application of the cluster analysis, a first assessment of the sample was carried out in order to characterize it. In relation to the spatial location of these accidents, it was noticed that there is a high concentration of accidents in Catalonia and Galicia, specifically along the coastline of both regions. Figure 1 shows the accident map of accidents with fatalities which happened between 2006 and 2013.
Fig. 1. Road accident map of accidents with fatalities occurred in Spanish crosstown roads in the period between 2006 and 2013.
As to the age of the deceased, there is a high percentage of victims over 65 (32%), while the percentage of the under-25 age group has been decreasing in recent years, reaching a minimum in the year 2013. Regarding the different types of users, the vast majority of the deceased were pedestrians and people over 65 years of age. In figure 2 we can observe the evolution of the average age of the people who died in this kind of routes.
Fig. 2. Evolution of the percentage of fatalities per age group in Spanish crosstown roads in the period between 2006 and 2013.
Additionally, in relation to the population size, most of the accidents took place in villages, which have a population size between 5,000 and 15,000 inhabitants. Furthermore, the existence of a fairly large group of towns of more than 100,000 inhabitants in which bypass roads have not yet been built (38 cases) is striking. These accidents took place in fully urban stretch of road, old crosstown roads that were not properly integrated into the urban fabric and remained with local utility after the branch off due to the construction of the bypass road, for which it is recommended to review the type of signalling present in them, the dimensions of the sidewalk, the current use of these streets, their traffic and their role in the city urban fabric. Once an initial analysis of the data was completed, the cluster techniques were applied. The software used for the development of the statistical analysis was the SPSS Statistics v24.0.0. The method selected was the hierarchical clustering analysis (HCA). This method was chosen because it is the most suitable when the number of clusters is not known in advance and the sample size is not very large. Euclidean distance squared was selected as a measure of proximity between individuals. As a result, three clearly distinguished accident groups were obtained.
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4. Results and discussion The first group obtained consists of 43 accidents and populations of 100,000 inhabitants. The number of victims amount to 87, most drivers. The unemployment rate ranged between 15% and 20% and the Gross Domestic Product (GDP) per capita between 20,000 and 30,000 euros. There is also a high number of people over 65 years old (between 20,000 and 35,000 inhabitants). In this group the victims that predominate are those between 40 and 54 years old. These are fully urban road stretches, old crosstown roads that have not been adequately fitted out after building the bypass road. Most of these accidents took place in the city of Barcelona and in the surrounding towns. This group of routes is not relevant to our study, although it is true that the DGT should review it and try to add this data to urban road data set and avoid being labeled as crosstown roads. In figure 3 we can see the accident map.
Fig. 3. Road accident map of Group 1 (left figure) and Group 2 (right figure)
The second group (group 2) is made up of 147 accidents and 294 victims. The size of the affected population was between 5,000 and 50,000 inhabitants, with an unemployment rate ranging between 10% and 20%. This group consists of young victims (53% of them are under 30 years old). These accidents are located geographically on the Spanish east, especially the part of Catalonia closest to the Mediterranean coast. These accidents may be due to the fact that in the Levante, the eastern region of the Iberian Peninsula, on the Spanish Mediterranean coast, there is a lot of youth night driving, with alcohol and drugs. Most of the victims are the drivers of the vehicles and 30% of the accidents took place between 10:00 p.m. and 5:00 a.m. Figure 3 shows the accident map of the second group. Finally, cluster 3 consists of 108 accidents and 216 fatalities. Accidents in this group have occurred in populations between 5,000 and 50,000 inhabitants, with an unemployment rate between 10% and 20%. In addition, 35% of the total victims are people over 65 years old. As well 23.2% of the victims were pedestrians. Most of the accidents happened in towns, which are in the interior of the Iberian Peninsula, and this is a very complex interpretation, since the causes of accidents in this case can be very diverse. In figure 4, the accident map is shown.
Fig. 4. Road accident map of Group 3 (cluster analysis).
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As we can observe in the results obtained, the most vulnerable users were those over 65 years old and the majority of them were pedestrians. As shown in Figure 5, keeping in mind all kind of users, we observe that the elderly group died more than the rest, for the period between 2006 and 2013.
Fig. 5. Age groups of fatalities in Spanish crosstown roads (all type of users: drivers, pedestrians and passengers). Absolute values.
Additionally, the most frequent types of accident in this age group were pedestrian accidents and front side collision (see Figure 6). Also the most frequent infraction made by drivers over 65 years of age was distracted driving, while the most frequent infringement by pedestrians was due to crossing the road not according to the rules.
Fig. 6. Most frequent type of accident in Spanish crosstown roads for the age group over 65 years old
5. Conclusions and recommendations To sum up, in the cluster analysis the high accident rate of two vulnerable groups of users was reflected: the elderly group and the young. Demographic growth of people over 65 years old has had a significant impact on the field of transport and road safety. This group often drives older vehicles and has cognitive, sensory or motor impairments that progressively modify their ability to drive. This fact places them at a disadvantage in case of collision, due to their physical fragility. In addition, the accident rate of those under 30 was principally due to alcohol and drugs. Likewise, it has been detected that accidents in fully urban road stretches, corresponding to old crosstown roads that have not been properly fitted out after constructing the bypass road. This particular group should be reviewed in order to avoid incorrectly classifying these routes. It would be advisable to create strategic action plans for each region that has been affected. This could be useful and would provide us with guidelines to act on them and integrate this kind of routes into the urban structure when it becomes obsolete, increasing road safety and reducing risk of accidents for both pedestrians and other road users.
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Further research into the cluster attributes and identified patterns is needed to investigate to a greater extent how these factors can be mitigated to reduce the risk of severe injuries. Also other variables related with infrastructure and mobility levels, such as the crosstown roads layout, the traffic intensity or the road consistency, might be considered. It would also be necessary to create new clusters with variables, as well as to make use of other methodologies (latent cluster, K-means clustering) to try to identify better solutions for improving safety. Finally, it should be noted that the numbers of fatalities in crosstown roads have reduced in recent years but they are still too high. Additionally, there is still a long way to reach the aim of zero accidents. The current conclusions of this study are only a starting point for a future line of research with the intention of investigating more thoroughly the causation of accidents which happen in crosstown roads with the purpose of achieving a reduction of accidents in this type of road. Acknowledgements This paper shows the first part of the results of a research sponsored and funded by the Spanish General Directorate of Traffic (DGT) as part of the Subsidy Programme for the development of research projects in the area of traffic, mobility and road safety for the year 2017. This project has been referenced with the administrative code SPIP2017-02199. The authors are also grateful to DGT for providing the data necessary for this research. References De Oña, J., López, G., Mujalli, R., Calvo, F. (2013). Analysis of traffic accidents on rural highways using Latent Class Clustering and Bayesian Networks. Accident Analysis & Prevention, 51, 1-10 Depaire, B., Wets, G., Vanhoof, K. (2008). 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