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Prediction models have been extensively used in the field of road safety. However, none of these models have yet been particularly applied to injuries related to zero-emission electric vehicles (EVs), which may lead to different outcomes due to their inaudible engines. Using an optimisable classification tree, the aim of this first-ever study was to predict the likelihood of personal injury severities stemming from EV-related crashes on Britain's roads. The prediction model was found to be capable of detecting significant and insignificant factors. These factors provide important insights into how the severity of injuries could be reduced in the future deployment of EVs. Although there was an increased risk for injuries classified as 'slight severity', particularly at lower urban speed limits, several predictors are suggesting that EVs do not pose more of a risk to a certain group. Contrary to popular belief, no convincing evidence was found to suggest that eco-friendly EVs are 'silent killers' for vulnerable road users. [ABSTRACT FROM AUTHOR]

The use of natural river silt treated as a 'waste material' has become the focus of research in the Yellow River flooded area, especially in the field of highway engineering. It is therefore of great significance to study the deformation and stiffness degradation of Yellow River silt (YRS) under long-term cyclic loads. To this end, a series of undrained cyclic triaxial tests on YRS for a large number of cycles (10 000) was carried out using a triaxial apparatus and the effects of confining pressure and cyclic stress ratio on the resilient strain of the YRS were explored. The critical cyclic stress and the critical cyclic stress ratio between the plastic shakedown state and incremental collapse state of the YRS were determined, and the modulus-softening behaviour of the YRS was assessed. The results of this study not only provide theoretical support for the long-term engineering performance of YRS, but also provide theoretical guidance for the cyclic response of all similar types of subgrade soils. [ABSTRACT FROM AUTHOR]

There have been limited efforts to investigate the potential of using detailed trajectory data obtained from connected vehicles and/or other sensors in deriving metrics for use in real-time assessment of traffic safety. This study investigated the use of disturbance metrics for this purpose. The disturbance metrics considered were the number of oscillations (NoO) and a measure of disturbance durations in terms of the time exposed time-to-collision index (TETIndex). The time exposed time-to-collision (TET) has been widely used as a safety surrogate measure, but there is no study on the identification of its thresholds to justify activating plans to mitigate unsafe conditions in real-time operations. This study found a TETIndex of 0.03 and NoO of 10% can be used to recognise unsafe conditions in the case study of this research. Since estimation of the TETIndex requires the location and speed of both leading and following vehicles and therefore cannot be measured accurately with low sample sizes of vehicle trajectories, a regression model was derived to estimate the TETIndex based on speed parameters. It was also found that the investigated disturbance metrics and associated models and thresholds are significantly related to crash occurrence and can thus be used in the activation of transportation management strategies to reduce the probability of unsafe traffic and ease traffic disturbances that have an adverse impact on traffic safety. [ABSTRACT FROM AUTHOR]

Sincere thanks are extended to the following people who reviewed manuscripts submitted to the I Journal of Performance of Constructed Facilities i during the period of July 1, 2021, to June 30, 2022. Hassan Abbasi I Islamic Azad University, South Tehran Branch i A. B. M. Abdullah I Arkansas Department of Transportation i Masato Abe I BMC Corporation i Michael Joseph Abrahams I WSP USA Corp. i Mehmet Ada I Usak University i Jose M. Adam I Universitat Politècnica de València i Süleyman Adanur I Karadeniz Technical University i Hamdy M. Afefy I Tanta University i Mohammad Aghababaei I Texas A&M University i Ihab El Aghoury I Ain Shams University i Emma Marinie Ahmad Zawawi I Universiti Teknologi MARA i Hüseyin Akay I Gazi Universitesi i Zülal Akbay Arama I Istanbul University-Cerrahpasa i Emre Akin I Adnan Menderes Universitesi i Ahmet Emin Aktan I Drexel University i Haluk Aktan I Western Michigan University i Ahmed Sh. [Extracted from the article]

• Trajectory data of road users bring about progresses in transportation research. • Wide-area trajectory data are continuous trajectories of vehicles along roadway. • Advances in sensing and computing make tracking at wide-area level possible. • This paper discusses research potentials of wide-area vehicle trajectory data. Trajectory data of road users play a crucial role in transportation engineering and traffic safety research. Previous vehicle trajectory data, including naturalistic driving data, trajectory data captured by drones and traffic cameras, have greatly promoted the research of traffic safety, traffic simulation, and other transportation engineering fields. However, existing technologies in collecting trajectory data are limited their detection range. With the development of the sensing and tracking technologies, it is possible to track the trajectory information of road users at the wide-area level, i.e., the real-time trajectory data of all road users on the entire road. Recently, we published our data sharing platform, Tongji Road Trajectory Sharing (TJRD TS, available online at https://tjrdts.com) Platform, providing our open wide-area vehicle trajectory data for researchers, academics, and road traffic professionals. Advanced vehicle tracking and trajectory splicing technologies, such as millimeter wave radar and edge computing technology, were employed to obtain such wide-area vehicle trajectory data. In this short communication article, we brainstorm ideas of using wide-area vehicle trajectory data in traffic safety research, traffic efficiency research, and connected and autonomous vehicle (CAV) application. We hope this short communication and our published data sharing platform can serve as the steppingstone for those who are interested in road transportation engineering and road safety research using such wide-area vehicle trajectory data. [ABSTRACT FROM AUTHOR]

• Studied the heat-reflective coating of asphalt pavement. • Systematically studied the durability of heat-reflective coating. • Investigated the effect of anti-skid particles on the cooling performance of coating. • Studied the optimal dosage of anti-skid particles. Reducing high temperature rutting on asphalt pavement is of great importance to improve the quality of pavement engineering and road traffic safety. In laboratory and field tests, this study investigates the cooling performance and optimal dosage of heat-reflective coatings. The temperature-change resistances, water stabilities, abrasion resistances, and skid resistances of six colored heat-reflective coatings were studied. Among the differently colored coatings, the red coating demonstrated the best cooling performance, with a maximum cooled temperature of 13.2 °C. The colored heat-reflective coatings showed good temperature-change resistance, water stability, and abrasion resistance. At dosages of 0.35 and 0.55 kg/m2, the heat-reflective coating met the specification requirements of skid resistance; meanwhile, the coating added at 0.75 kg/m2 achieved the highest cooling performance but failed to meet the required skid-resistance standards. After adding anti-skid particles, the skid resistance was improved while the cooling performance was hardly affected. The optimal dosage of anti-skip particles was 0.3 kg/m2. [ABSTRACT FROM AUTHOR]