The application of infrared camera-related technology is a trending research topic. By reviewing the development of infrared thermal imagers, this paper introduces several main processing technologies of infrared thermal imagers, expounds the image nonuniformity correction, noise removal, and image pseudo color enhancement of infrared thermal imagers, and briefly analyzes some main algorithms used in image processing. The technologies of blind element detection and compensation, temperature measurement, target detection, and tracking of infrared thermal imager are described. By analyzing the main algorithms of infrared temperature measurement, target detection, and tracking, the advantages and disadvantages of these technologies are put forward. At the same time, the development of multi/hyperspectral infrared remote sensing technology and its application are also introduced. The analysis shows that infrared thermal imager processing technology is widely used in many fields, especially in the direction of autonomous driving, and this review helps to expand the reader’s research ideas and research methods.

Vehicle-pedestrian conflicts have been the major concern for traffic safety. Surrogate safety measures are widely applied for pedestrian safety evaluation. However, how to quickly identify the vehicle-pedestrian surrogate safety measures at the individual site is challenging due to the difficulty of obtaining the high-resolution trajectories of road users. This paper presented an effective method to generate the high-resolution traffic trajectories from the roadside deployed Light Detection and Ranging (LiDAR) sensor. The vehicle-pedestrian conflicts can then be identified from the trajectories simply using the speed-distance profile (SDP) of the vehicles. The SDP can be used to develop a rule-based method for vehicle-pedestrian identification. The events can be divided into different risk levels based on the spatial distribution of the SDP. The case study shows that the rule-based method can detect vehicle-pedestrian near-crash events effectively. The other indicators, such as widely used time-to-collision (TTC) or deceleration rate to avoid a crash (DRAC), can be also obtained from the SDP. The engineers can also adjust the thresholds in the rule-based method to meet the specific requirements at different sites. The proposed method can be extended to identify vehicle-vehicle conflicts or vehicle-bicycle conflicts in future studies.

High frequency of distracted driving behavior is considered a high potential risk for traffic safety. Right-turn drivers’ distracted driving behavior can dramatically increase the crash risk considering the complex procedures required by the right-turn movements at intersections. This paper analyzed the influence of several factors including road geometry, environmental factors, and traffic conditions on the occurrence of right-turn drivers’ distracted driving activities. The data were collected through the Naturalistic Driving Study (NDS). A total of 581 events including 208 events with distracted driving and 373 events without distracted driving (baseline events) were extracted from the Strategic Highway Research Program 2 (SHRP 2) NDS database. The logistic model and random forest (RF) were applied for regression analysis. It was found that Vehicle Lane Occupied and Traffic Control are significantly correlated to distracted driving behavior in both models. The analysis of odds ratios indicated that dedicated right-turn lane design and adding yield sign at intersections can reduce the probability of having distracted driving behavior. Traffic density and driving time may also play important roles in the occurrence of distracted driving activities. Countermeasures are recommended to reduce distracted driving in this paper. The findings of this paper can help engineers and researchers better understand the dominant factors affecting drivers’ distraction. This research can also provide theoretical support for the distraction detection function in the advanced driver-assistance systems (ADAS).

Roadside sensor data fusion is an essential component of the vehicle-road cooperation system, effectively enhancing the interactive perception level among road targets. However, due to the complex road environment, occlusion, and other problems, the single sensor has low accuracy in the process of target tracking. How to realize the fusion of multi-sensor trajectory tracking data is the main problem to be solved at present. Therefore, a new multi-sensor data fusion method for roadside camera, LiDAR, and millimeter wave (MMW) radar is proposed in this study. According to the change of reflection intensity caused by the shift of LiDAR point cloud with the change of distance, and the detection accuracy of MMW radar used in this paper, the weight parameters of LiDAR and MMW radar in the fusion process are determined. Finally, the target missed detection rate and trajectory disconnected repair rate were customized, and experimental tests were conducted in five natural environments to verify the robustness of the proposed method.

Distributed optical fiber sensing (DOFS) is an advanced tool for structural health monitoring (SHM), offering high precision, wide measurement range, and real-time as well as long-term monitoring capabilities. It enables real-time monitoring of both temperature and strain information along the entire optical fiber line, providing a novel approach for safety monitoring and structural health assessment in transportation engineering. This paper first introduces the fundamental principles and classifications of DOFS technology and then systematically reviews the current research progress on Brillouin scattering-based DOFS. By analyzing the monitoring requirements of various types of transportation infrastructure, this paper discusses the applications and challenges of this technology in SHM and damage detection for roads, bridges, tunnels, and other infrastructure, particularly in identifying and tracking cracks, deformations, and localized damage. This review highlights the significant potential and promising prospects of Brillouin scattering technology in transportation engineering. Nevertheless, further research is needed to optimize sensing system performance and promote its widespread application in this field. These findings provide valuable references for future research and technological development.