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The main objective of this paper was to analyse the roadway, environmental, and driver-related factors associated with an overrepresentation of frequency and severity of run-off-the-road (ROR) crashes. The data used in this study refer to the 6167 crashes occurred in the section Naples-Candela of A16 motorway, Italy in the period from 2001 to 2011. The analysis was carried out using the rule discovery technique due to its ability of extracting knowledge from large amounts of data previously unknown and indistinguishable by investigating patterns that occur together in a given event. The rules were filtered by support, confidence, lift, and validated by the lift increase criterion. A two-step analysis was carried out. In the first step, rules discovering factors contributing to ROR crashes were identified. In the second step, studying only ROR crashes, rules discovering factors contributing to severe and fatal injury (KSI) crashes were identified. As a result, 94 significant rules for ROR crashes and 129 significant rules for KSI crashes were identified. These rules represent several combinations of geometric design, roadside, barrier performance, crash dynamic, vehicle, environmental and drivers' characteristics associated with an overrepresentation of frequency and severity of ROR crashes. From the methodological point of view, study results show that the a priori algorithm was effective in providing new information which was previously hidden in the data. Finally, several countermeasures to solve or mitigate the safety issues identified in this study were discussed. It is worthwhile to observe that the study showed a combination of factors contributing to the overrepresentation of frequency and severity of ROR crashes. Consequently, the implementation of a combination of countermeasures is recommended., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Objective: Given the strong relationship between road accident and traffic speed, the evaluation and prediction of this latter have always been considered as a critical issue for road safety analysis and for the evaluation of road network safety improvements. Prediction models developed to date mainly focused on spot speed in a rural environment or on running speed in an urban one. Very few analyze the speed estimation in "transition" areas. The objective of this paper is to develop a generalized speed estimation model able to predict mean speed in urban, rural, and "transition" environment as a function of road layout characteristics. It is believed that the proposed estimation tool can be effectively employed by road engineers in the road safety design and retrofitting stage., Methods: The basic idea of the paper is to shed some light on this issue by making use of a hybrid estimation approach able to combine the information gathered from both previously mentioned models within a generalized speed adaptation framework that reflects road user behavior. The calibration and validation of the generalized estimation model have been carried out following a collection of Floating Car Data (FCD) on several candidate sites., Results: Preliminary results seem to indicate that the methodology proposed may be effective in estimating the spot speed in two-lane rural and urban arterials., Conclusions: FCD data can be useful to develop more efficient estimation models to better manage the safety of urban and rural roads.

Aim of the study was to investigate, by means of a driving simulator experiment, drivers' behaviour in terms of speed, deceleration, and lateral position on major approaches of rural intersections in relation to different perceptual cues. In the experiment, ten different design conditions with and without speed-reducing treatments along the approach to the intersection were tested. Twenty-three drivers drove a test route two times and data from the second drive were used for comparison. The order of the ten design conditions was counterbalanced for all the drivers to minimize the presentation order effect. Three different data analysis techniques were used: (a) cluster analysis of speed and lateral position data, (b) statistical tests of speed and lateral position data, and (c) categorical analysis of deceleration behaviour patterns. The most effective treatments were the dragon teeth markings (based on the principle of optical road narrowing), the colored intersection area (based on the principle of intersection highlighting), and the raised median island (based on the principle of physical road narrowing). These measures, in comparison to the base intersection, produced: (1) a significant speed reduction starting from 250 m before the intersection in the range between 13 and 23 km/h, (2) a significant change in the deceleration behaviour with a reduction in the proportion of drivers which did not decelerate, and (3) a shift away from the intersection of the deceleration beginning. Given the significant effects on drivers' behaviour, the dragon teeth markings, the colored intersection area, and the raised median island are strongly recommended for real world implementation., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

The paper investigated drivers' speed behaviour in a section of a rural highway crossing a small urban community in the existing scenario without any traffic calming device and in two different design scenarios with traffic calming in the urban community. Two gateways and four integrative traffic calming devices along the route within the urban area were tested. The gateways were aimed at slowing down the vehicles entering in the built-up area, while the traffic calming devices were aimed at complementing the gateway effect inside the built-up area. Two design options were tested: first option (alt1) is a combination of low cost measures, whereas the second option (alt2) is more expensive as includes a chicane and requires land acquisition. Drivers' behaviour was investigated by means of a driving simulator experiment. The VERA dynamic-driving simulator operating at the TEST Road Safety Laboratory located in Naples (Italy) was used. Simulation results were validated by the comparison of speed behaviour in the real world and in the driving simulator, in the scenario without traffic calming. Analysis of the driving simulator experiment results was performed using two different approaches: (a) explorative description of data by cluster analysis; (b) inferential procedures about population using statistical tests. Cluster analysis was carried out in order to test if the drivers' speed behaviour in the different design alternatives was substantially different. Statistical tests were performed in order to verify if speeds in specific sections were significantly different. Cluster analysis looked at speed profiles, whereas statistical tests looked at speed data in specific points. The obtained results showed a different behaviour of drivers approaching the urban community in the existing scenario and in the design scenarios. In the south direction, mean speed reduction ranging between 16 and 17 km/h, with 5% level of significance, was observed. In the north direction, mean speed reduction equal to 11 km/h, with 10% level of significance, was observed. Differences between the two design alternatives were not statistically significant. Along the urban community, a statistically significant mean speed reduction ranging between 9 and 15 km/h was observed in the south direction. In the north direction, speed reduction was not statistically significant. Overall, combined results of cluster analysis and statistical tests showed that the treatments were more effective in the direction with higher speeds in the base scenario., (2010 Elsevier Ltd. All rights reserved.)