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Gas detection in enclosed cabins is a challenging concern in the industry to ensure the safety of cabin operations and personnel driving. There has been a growing development in the detection of safety in enclosed cabin operations based on volatile organic compounds, which have unique characteristics. The air pollution in closed cabins seriously affects the driver’s health, and the accuracy of the detection directly affects the operation safety of the cabin. However, until today, gas detection in enclosed cabins has relied on traditional methods that are expensive and time-consuming, and it cannot be detected in real time. This paper focuses on the potential and capability of electronic nose applications for gas detection in enclosed cabins. Since the electronic nose is a good substitute for the closed cabin, people’s attention to it has increased greatly. The characteristics of hazardous gas and warning gas in closed cabins are also discussed. In addition, this paper provides important insights into the challenges and future trends of the electronic nose, a low-cost, high-precision, and fast detection method, in more applications in closed compartments.

Driver behavior is considered one of the most important factors in the genesis of dilemma zones and the safety of driver-vehicle-environment systems. An accurate driver behavior model can improve the traffic signal control efficiency and decrease traffic accidents in signalized intersections. This paper uses a mathematical modeling method to study driver behavior in a dilemma zone based on stochastic model predictive control (SMPC), along with considering the dynamic characteristics of human cognition and execution, aiming to provide a feasible solution for modeling driver behavior more accurately and potentially improving the understanding of driver-vehicle-environment systems in dilemma zones. This paper explores the modeling framework of driver behavior, including the perception module, decision-making module, and operation module. The perception module is proposed to stimulate the ability to perceive uncertainty and select attention in the dilemma zone. An SMPC-based driver control modeling method is proposed to stimulate decision-making behavior in the dilemma zone. The operation module is proposed to stimulate the execution ability of the driver. Finally, CarSim, the well-known vehicle dynamics analysis software package, is used to verify the proposed models of this paper. The simulation results show that the SMPC-based driver behavior model can effectively and accurately reflect the vehicle motion and dynamics under driving in the dilemma zone.

Image mosaic is one of important technologies for image processing. It is normally used to make up a seamless and high resolution image. There are some algorithms that deal with the image mosaic. But the most make simply two or more images seamlessly form a large image for a holographic scenic display. The post-processing on the photo from a traffic accident scene is required to reflect and allow inspectors to accurately determine the actual distance between objects in the scene. Therefore the images taken from the traffic accident scene need to be corrected before being spliced to each other. The image correction allows the information on the scene to be correctly displayed. The splicing on the corrected images ensures a thorough view and complete information gain that covers the whole scene.

Road traffic system is an organic coupling system which is composed of four sub-systems, driver, vehicle, road and environment. Evaluating the safety of road traffic system is beneficial to identify the system risk and make more pointed safety measures. Although most existing evaluation models had been set up basing on classical geometry theory, which mainly use the evaluation index such as the vehicle operation information and traffic accidents data etc.. The evaluation result is difficult to reflect the relative safety among sub-systems and whole system directly. In order to overcome the problems above, this paper adopts the catastrophe theory and establishes the corresponding evaluation model of road traffic system based on catastrophe theory, in which the cusp catastrophe model, swallowtail catastrophe model and butterfly catastrophe model are available. Finally, the practicality and accuracy of model were verified through examples. The case study shows that the evaluation result is consistent with the actual situations, which indicates that it is scientific and reasonable to applying the analytical method to the safety evaluation of road traffic system.

In order to address the difficulty of arranging large calibration objects and the low measurement accuracy of small calibration objects in traffic accident scene photogrammetry, a photogrammetric method based on a composite of small calibration objects is proposed. Several small calibration objects are placed around the traffic accident scene, and the coordinate system of the composite calibration object is given based on one of them. By maintaining the relative position and coplanar relationship of the small calibration objects, the local coordinate system of each small calibration object is transformed into the coordinate system of the composite calibration object. The two-dimensional direct linear transformation method is improved based on minimizing the reprojection error of the calibration points of all objects. A rectified image is obtained using the nonlinear optimization method. The increased accuracy of traffic accident scene photogrammetry using a composite small calibration object is demonstrated through the analysis of field experiments and case studies. Language: en