The role of traffic conflicts in roundabout safety evaluation: A review.

The roundabout is one type of at-grade intersection commonly seen in many countries. The evaluation of roundabout safety is usually counted on conflict analysis of the roundabout traffic due to random and limited records of real accidents. This paper surveyed published papers and reports that investigate the role of traffic conflicts in roundabout safety evaluation. It summarized the definitions and observation methods of roundabout conflicts and classified the attributing factors of roundabout conflicts and the countermeasures to control the conflicts. This study found that although unique traffic flow movements at roundabouts create special patterns of roundabout conflicts, the methods of roundabout conflict analysis used in most existing studies were inherited from the studies of highway or cross-intersection conflicts, including conflict definitions, conflict measurements, and thresholds of conflict severity. Special or improper designs of roundabout configurations or basic geometry elements could arouse roundabout conflicts. The most common vehicle-to-vehicle conflicts were entering-circulating conflicts, sideswipe conflicts, and exiting-circulating conflicts. The conflicts among vehicles and vulnerable road users (VRUs) easily evolved into serious collisions, but these conflicts did not get deserved attention in previous studies. Drivers' familiarity with roundabouts also affected road users' safety. Traffic signs and pavement markings were commonly used to control roundabout conflicts, while traffic signals were more effective methods for the roundabouts with uneven distribution of approaching traffic or high traffic volume. Based on the analysis of existing studies, this paper pointed out seven future directions of further research in term of conflict measurement, data collection, infrastructure and access management, geometry, drivers and VRUs, signal control, and vehicle control.

Spatial Distribution of Fine Particulate Matter in Underground Passageways.

The unfavorable locations of underground infrastructures and poor ventilation facilities can result in the deterioration of enclosed air quality. Some researchers have studied air quality and ventilation measures in different types of underground buildings. However, few studies have investigated the pollution in pedestrian passageways connecting underground structures. Hence, in this paper, we attempted to investigate the spatial distribution of fine particulate matter (PM2.5) in underground passageways. First, measurements were designed and conducted in a pedestrian passageway beneath the Shanghai South Railway Station, Shanghai, China. Second, numerical simulations were performed based on computational fluid dynamic (CFD) technology. Finally, the numerical simulations were extended to examine impacts of the ventilation measures on PM2.5 concentration with different inlet positions and air velocity in underground passageways. The simulation results showed good agreement with the experimental data, and the numerical model was validated to be an effective method to investigate the spatial distribution of PM2.5 in underground passageways. Results suggest that building additional entrances is an advisable method for improving air quality in the underground passageways of the Shanghai South Railway Station, while jet fans are not recommended. Findings of this study offer suggestions for mitigating PM2.5 pollution in underground passageways.

Three-dimensional investigation of ozone pollution in the lower troposphere using an unmanned aerial vehicle platform.

Potential utilities of instrumented lightweight unmanned aerial vehicles (UAVs) to quickly characterize tropospheric ozone pollution and meteorological factors including air temperature and relative humidity at three-dimensional scales are highlighted in this study. Both vertical and horizontal variations of ozone within the 1000 m lower troposphere at a local area of 4 × 4 km2 are investigated during summer and autumn times. Results from field measurements show that the UAV platform has a sufficient reliability and precision in capturing spatiotemporal variations of ozone and meteorological factors. The results also reveal that ozone vertical variation is mainly linked to the vertical distribution patterns of air temperature and the horizontal transport of air masses from other regions. In addition, significant horizontal variations of ozone are also observed at different levels. Without major exhaust sources, ozone horizontal variation has a strong correlation with the vertical convection intensity of air masses within the lower troposphere. Higher air temperatures are usually related to lower ozone horizontal variations at the localized area, whereas underlying surface diversity has a week influence. Three-dimensional ozone maps are obtained using an interpolation method based on UAV collected samples, which are capable of clearly demonstrating the diurnal evolution processes of ozone within the 1000 m lower troposphere.

Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes.

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.