Sort:
Issue
International research progress on driving under the influence of drugs
Journal of Tsinghua University (Science and Technology) 2025, 65(1): 125-134
Published: 15 January 2025
Abstract PDF (3.4 MB) Collect
Downloads:1
Objective

Driving under the influence of drugs or drugged driving refers to operating a vehicle after consuming certain drugs, posing a significant risk to public safety. While international research on drugged driving is extensive, domestic studies are lacking. This paper aims to bridge this gap by reviewing international research progress and summarizing specific research directions and achievements to guide domestic research.

Methods

To thoroughly assess the research progress on drugged driving, data was collected from the Web of Science Core Collection Database. The search used keywords such as "drug (medicine) and drive (driving)", limiting the research direction to "transportation" and publication period from "1999 to 2023". Totally 264 research articles were gathered. The mapping knowledge domain (MKD) method was used to analyze the annual distribution, source publications, keyword co-occurrence, and other relevant literature aspects, providing specific insights into progress in drugged driving research.

Results

The results show that international research on drugged driving has been extensive and diverse since the 1990s. Qualitative and quantitative studies have explored various aspects of the issue, including the types of drugs affecting drivers, their impact on driving abilities, the risks associated with drugged driving, the prevalence of drugged, driver attitudes and perceptions, drug detection technologies, and relevant legislation. To promote governance and prevent drugged driving incidents in China, several projects need attention: classifying drugs that impair driving and understanding their pharmacological effects, developing drug detection technologies, conducting epidemiological investigations on the prevalence of drugged driving among drivers, and carrying out empirical analysis and legislative research on drugged driving cases.

Conclusions

This paper employs structured network analysis methods to comprehensively review international research achievements in drugged driving during the past 30 years. The analysis of annual publication distribution, source publications, and keyword co-occurrence supplements existing literature reviews. This study offers valuable guidance for future research and governance strategies related to drugged driving in the domestic domain.

Open Access Issue
Study of Driver’s Perception in Driving Tasks Based on Naturalistic Driving Experiments and fNIRS Measurement
Tsinghua Science and Technology 2025, 30(2): 796-812
Published: 09 December 2024
Abstract PDF (10.8 MB) Collect
Downloads:11

Understanding how drivers perceive and respond to external stimuli in driving tasks is important for the development of advanced driving technologies and human-computer interaction. In this paper, we conducted a temporal response analysis between driving data and cortical activation data measured by functional near-infrared spectroscopy (fNIRS), based on a naturalistic driving experiment. Temporal response function analysis indicates that stimuli, which elicit significant responses of drivers include distance, acceleration, time headway, and the velocity of the preceding vehicle. For these stimuli, the time lags and response patterns were further discussed. The influencing factors on drivers’ perception were also studied based on various driver characteristics. These conclusions can provide guidance for the construction of car-following models, the safety assessment of drivers and the improvement of advanced driving technologies.

Issue
A decision support model for crime investigation
Journal of Tsinghua University (Science and Technology) 2023, 63(10): 1598-1607
Published: 15 October 2023
Abstract PDF (3.5 MB) Collect
Downloads:2
Objective

Artificial intelligence and big data technologies have been used to solve many scientific problems, including crime analysis. The investigation of criminal cases has always been a critical and difficult point in the domain of crime analysis. The investigation stage of criminal cases primarily consists of evidence collection and evidence reasoning, and comprehensive and efficient collection and reasoning of evidence are critical to the rapid detection of cases. Simultaneously, the significance of the various pieces of evidence in the case varies. Evidence of high importance gathered during the investigation stage is critical for the accurate and efficient resolution of crime cases. However, existing research lacks the application of artificial intelligence methods to crime investigation decision support.

Methods

Aiming at the problem of crime investigation, this research proposes a decision support model based on the Bayesian network to help domain experts determine the direction of the investigation and reasoning the criminal facts. First, the Bayesian network is used to reason the hypothesis of criminal facts. Second, the weighted information entropy method is used to calculate the importance of criminal evidence. Four different types of weighted information entropy methods are employed to test the efficiency of the calculation method. The two methodologies are then combined to create the decision support model for crime investigation. Finally, the proposed model is applied to 420 crime cases to verify its accuracy, and the proposed model is also applied to a real case analysis to illustrate the application process of the model.

Results

The analysis of 420 crime cases reveals that calculations based on weighted information entropy are the best of all four methods. The top 3, 5, and 10 evidence pieces provided with the weighted information entropy method all have the highest coverage of importance, given any arbitrary evidence missing ratio. Meanwhile, when 50% of the evidence is missing, the output result's coverage of the top 3, 5, and 10 important pieces of evidence is greater than 50%, 65%, and 80%, respectively; when 90% of the evidence is missing, the coverage of the top 3, 5, and 10 evidence pieces is greater than 40%, 60% and 75%, respectively. These suggest that the model's detection recommendations are effective and can be used to assist in crime detection. Furthermore, the analysis of a real-world case also shows that the proposed model can generate effective investigation suggestions and provide decision support for evidence collection and reasoning during the investigation stage.

Conclusions

Finally, the proposed decision support model for crime investigation can analyze available case information and generate effective investigation suggestions and reasoning conclusions. However, it should be noted that the model developed in this study does not completely replace the role of professionals in the field of criminal investigations but rather provides analysis results to scientifically support the decisions of subsequent investigators in the initial stages of the investigation. Furthermore, this study focuses on the research of evidence collection and reasoning during the investigation stage of criminal cases but pays limited attention to the "evidence standard" involved in the process of evidence collection. Therefore, we can continue to investigate this aspect in the future to aid intelligence and standardization of evidence collection during the investigation stage.

Issue
Case reasoning model for the "beyond a reasonable doubt" standard
Journal of Tsinghua University (Science and Technology) 2023, 63(6): 951-959
Published: 15 June 2023
Abstract PDF (1.5 MB) Collect
Downloads:1
Objective

To maintain social justice and to prevent unjust cases, during the trial stage of social security cases, the criminal facts for case reasoning based on the "beyond a reasonable doubt" (BRD) standard must be determined. It is a crucial prerequisite for passing a judgment on whether the suspect is guilty under the principle of the presumption of innocence. BRD is an essential standard of proof in a criminal case, but its concept is relatively vague and abstract, which makes it challenging to implement in practice. Moreover, research regarding this issue is insufficient.

Methods

This study applies the chain rule and the Bayesian inference method to deeply analyze the BRD standard. The rationality of the causal logic is used to examine the rationality under the reverse causal logic and put forward the judgment rule of the rationality of the case facts. The rule states that the claim is reasonable given the evidence if and only if the claim is a priori reasonable and the claim can reasonably explain the evidence. Accordingly, the chain rule of evidence interpretation is proposed, which decomposes the interpretation of multiple pieces of evidence into the interpretation of a single piece of evidence, which can simplify the difficulty of analysis. Considering the above rules, a case reasoning model facing the BRD standard is proposed. The model exhibits the claims of the prosecution and defense in the case into a sequence of actions, defining the a priori reasonableness of the claims and the reasonable interpretation of the evidence. Moreover, the model further defines the independence between the evidence interpretation and the independent division of the evidence, and then the relationship between the independent division and the evidence can be reasonably explained.

Results

The proposed model is applied to two common criminal cases, vehicle collision and homicide. The prosecution and defense opinions of the cases are investigated through the reasoning model, and the model analysis results are compared with the actual case facts to verify the effectiveness of the model. The comparison between the analysis results and the facts shows that when the concerned case meets the BRD standard, the model can accurately determine the facts of the case, and the basis provided by the model is consistent with the reasons given in the actual trial. Furthermore, when the concerned case does not meet the BRD standard, the results obtained using the model inference are consistent with the actual trial results.

Conclusions

The results confirm that for the cases that meet the BRD standard and those that do not, the proposed models can provide the right judgment to assist in determining the facts of the case and the corresponding basis. The proposed model can provide robust help and support for professionals in the judicial field with the fact reasoning in the court trial.

Issue
Heat and moisture transfer model of heated clothing for human thermal response calculation
Journal of Tsinghua University (Science and Technology) 2023, 63(6): 900-909
Published: 15 June 2023
Abstract PDF (1.3 MB) Collect
Downloads:4
Objective

Numerical heat and moisture transfer model of clothing is a crucial tool for evaluating clothing protective performance, calculating body-environment heat and moisture transfer, and assessing human safety during cold exposure. Existing models primarily concentrate on conventional passive protective clothing (PPC). However, actively-heated clothing (AHC) remains poorly understood, with fiber research being the primary focus in previous studies, which cannot simulate dressing conditions of the human body. In this study, we developed a multilayer heat and moisture transfer model of AHC, which can be coupled with a human thermal response model.

Methods

First, based on a published model of PPC, the heat production and transfer mechanism of active heating technologies, including electrical heating, phase change material (PCM), and moisture-absorption heating, were considered. Accordingly, we developed a general model for AHC. Particularly, the heat production of electrical heating was calculated using system voltage, current, and efficiency, and that of PCM was calculated using the phase change speed ratio and enthalpy. For moisture-absorption heating, the heat production was obtained using the moisture-absorption and heat-generation curves of the fabric, calculated by applying the specific heat and temperature change ratio. Second, we specifically considered electrically-heated clothing (EHC), which is the most widely used in practical applications. Further, the model was improved for EHC considering the clothing's detailed layer structure and radiative and horizontal heat transfer. The clothing layer containing the heating pad was further divided into interlining, pad, and fabric layers to establish more realistic heat-transfer equations. The radiative heat transfer between two clothing layers was derived using the Stefan-Boltzmann law, as heat radiation is significant in EHC systems. The body segment containing the heat area was further divided into heated and nonheated zones, in which horizontal heat transfer was modeled to accurately calculate the local skin temperature.

Results

The model coupled with a published human thermal response model was validated with existing experiments with air temperatures ranging from -20 ℃ to 8 ℃. Moreover, the general model was validated with data from an EHC experiment at 8 ℃ and a PCM clothing experiment at 5 ℃. The errors of mean skin, core, and microclimate temperatures did not exceed 0.58 ℃, 0.16 ℃ and 1.59 ℃, respectively. The improved EHC model was validated with data from a series of experiments with air temperatures ranging from -20 ℃ to 0 ℃ and air velocities from 0 to 5 m/s. Considering the thermal response prediction, the errors of mean skin, local skin, and core temperatures did not surpass 0.20 ℃, 0.47 ℃, and 0.14 ℃, respectively. Moreover, considering clothing evaluation, the error of effective heating power was ~0.10 W.

Conclusions

The proposed model can be used to assess human thermal safety and clothing protective performance in cold exposure cases with AHC and serve as a reference for personal protection, emergency management, and protective equipment research in the field of public safety and environmental ergonomics.

Issue
Experimental study of thermo-physiological responses of exercising subjects in -10 ℃5 ℃ cold environments
Journal of Tsinghua University (Science and Technology) 2022, 62(6): 1059-1066
Published: 15 June 2022
Abstract PDF (2.5 MB) Collect
Downloads:8

Human thermo-physiological responses to cold environments need to be accurately known to assess human thermal safety and thermal comfort in cold environments. Existing studies have mainly concentrated on people at low exercise intensity, with little consideration of exercising people. Human subject experiments were conducted in a climate chamber to study the thermo-physiological responses and the factors influencing the responses of people exercising in cold environments. The thermo-physiological parameters, including the skin temperature, core temperature and thermal sensation, were measured from six young men for various ambient temperatures of 5, 0, -5 and -10 ℃ and two clothing with 2.57 and 1.34 clo. The results show that the mean skin temperature and the local skin temperature are linearly related to the ambient temperature with the slope decreasing with additional thermal clothing insulation. The rate of change of the core temperature is linearly related to the body's heat accumulation rate with the slope increasing with additional thermal insulation. Thermal sensation is affected by the ambient temperature and clothing at low and medium exercise intensities, but is not significantly affected at high intensities. The thermal sensation of the exercising people shows no correlation with physiological temperature. The results lead to suggestions to the choice of clothing for exercising people in cold environments. This research provides reference for assessing the thermal safety, thermal comfort, exercise capability and clothing needs for exercising people.

Total 6