Civil Engineering September 2021 | Vol 29 No 8

Civil Engineering September 2021 37 and the UK, STRg members published a study on “Pavement Quality Index Rating Strategy Using Fracture Energy Analysis for Implementing Smart Road Infrastructure” (available: https://doi. org/10.3390/s21124231 ) . A Pavement Quality Index rating for smart road infrastructure has been pro- posed, using smart pavement sensors. The sensors were used to collect and analyse pavement temperature and moisture saturation content, which led to an assess- ment of the quality and performance of pavements and the prediction of pavement failure within any specific timeframe in real time. That was undertaken using constitu- tive models within the Mechanistic- Empirical Pavement Design Guide syn- chronised with a Pavement Management System Model. For this purpose, a smart pavement instrumentation system was developed (Figure 1) to automatically and continuously collect real-time temperature and moisture content data under traffic loading (Figure 2). This assisted in outlining a Pavement Quality Index rating, using the smart sensor device to monitor the pavement structural health in real-time and analyse pavement responses under changing environmental conditions. The researchers argued that this system of pavement monitoring and analysis of pavement responses under changing environmental conditions would be a simple and less time-consuming alternative to the standard methods of practice. In another study, a novel multiphase model for traffic safety evaluation in South Africa (available: https://doi. org/10.1155/2021/5584599 ) was developed. The researchers developed a novel multiphase model to effectively evaluate and rank vulnerable roads for the occurrence of vehicular traffic ac- cidents. For this purpose, three important multi-criteria decision-making methods (MCDM) – such as CRiteria Importance through Intercriteria Correlation (CRITIC), Data Envelopment Analysis (DEA), and Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) – were integrated (Figure 3). The study offered a model to rank the vulnerability of the urban streets and prioritised them based on which road geometry and traffic-related interven- tion measures can be taken to improve road safety. Furthermore, the researchers have collaborated in the areas of developing MCDM models for ranking and selection of asphalt production plants (available: https://doi.org/10.3390/math9030269 ) . In this study, an original Interval Rough Number (IRN) MCDM model was devel- oped to rank and select asphalt plants for road maintenance works. This group decision-making model enables assessment, ranking and selection in the field of road construction in an objective way (Figure 4). Further, it can assist in the assessment of potential solu- tions regardless of uncertainties that exist in group decision-making. Based on the results the researchers believe that the model represents an improved MCDM methodology that can serve as a useful tool for managers in a decision-making process in the field of road construction manage- ment as well as other related areas of application. In an earlier study titled “Possible Challenges of Integrating ICTs into the Public Transportation System in the Free State Province, South Africa” (available: https://doi. org/10.1007/978-3-319-43696-8_7 ) , the group investigated the challenges likely to be faced by the different stakeholders at the various levels of integration of ICT into the public transportation system at the provincial level. The researchers argued that there is a need for ICT in the Free State public transportation system. However, for its successful implementation, information on the needs of the various stakeholders is required. Further, it is necessary to assess whether those needs can be fulfilled using ICT solutions. This study has significant importance in the South African context and has direct implications for the im- provement of public transportation at the provincial or regional level. FUTURE PERSPECTIVES STRg believes that smart transportation is the future and is expected to shape the transportation system going forward. This area of study is highly relevant and signifi- cant for developing countries, including South Africa. For this reason, STRg is currently focused on advanced and smart technologies and novel methodologies to solve complex problems, without under- mining the other areas of research in this field of study. In this context, STRg is open to new ideas for collaborative research and warmly invites researchers and organisations to contribute to the group and its progress. STRg is also open to collaboration and partnerships with willing organisations and institutions across the world. A complete research profile for the group is available at strg. ukzn.ac.za .   21 16 11 6 1 –4 A21 A20 A19 A18 A17 A16 A15 A14 A13 A12 A11 A10 A9 A8 A7 A6 A5 A4 A3 A2 A1 Figure 4 Ranking of the locations of asphalt plants through a comparative analysis of different IRN MCDM methods STRg believes that smart transportation is the future and is expected to shape the transportation system going forward. This area of study is highly relevant and significant for developing countries, including South Africa.