scholarly journals Assessing Driving Risk Using Internet of Vehicles Data: An Analysis Based on Generalized Linear Models

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2712 ◽  
Author(s):  
Shuai Sun ◽  
Jun Bi ◽  
Montserrat Guillen ◽  
Ana M. Pérez-Marín

With the major advances made in internet of vehicles (IoV) technology in recent years, usage-based insurance (UBI) products have emerged to meet market needs. Such products, however, critically depend on driving risk identification and driver classification. Here, ordinary least square and binary logistic regressions are used to calculate a driving risk score on short-term IoV data without accidents and claims. Specifically, the regression results reveal a positive relationship between driving speed, braking times, revolutions per minute and the position of the accelerator pedal. Different classes of risk drivers can thus be identified. This study stresses both the importance and feasibility of using sensor data for driving risk analysis and discusses the implications for traffic safety and motor insurance.

2021 ◽  
Vol 60 (4) ◽  
pp. 125-136
Author(s):  
Jiří Ambros ◽  
Zuzana Křivánková ◽  
Robert Zůvala ◽  
Kateřina Bucsuházy ◽  
Jindřich Frič

Traffic safety is influenced, among other factors, by characteristics of the roads, which include the width of the shoulder. Shoulder width was noted to have a large effect on crash frequency, as well as on traffic speed. In this paper, we focused on paved shoulders. Previous studies confirmed that increasing the width of the paved shoulder is associated with a decrease in crash frequency. However, wider shoulders may encourage higher driving speed, which is related to an increase of impact speed and crash severity – this issue was hypothesized, but not statistically investigated. Thus, conclusions based on crashes and speeds contradict each other, and there is no simple answer to the question of the safety impact of wide shoulders. To address this gap, we analyzed a sample of two most typical categories of Czech secondary roads, which differ only in the paved shoulder width (S9.5 roads with 0.75m-wide shoulder, and S11.5 roads with 1.75m-wide shoulder) and thus present a suitable example for studying the safety impact of paved shoulder width. We used generalized linear models of crash frequency, and multinomial logistic models of crash severity (separately for single-vehicle and multi-vehicle crashes), as well as a statistical test of differences in speed for the two road categories. The results showed that: Firstly, there were fewer crashes on S11.5 roads compared to S9.5 roads; this was true for both single-vehicle and multi-vehicle crashes. Secondly, single-vehicle crashes on S11.5 roads were more severe compared to S9.5 roads; the change of severity in multi-vehicle crashes was not statistically significant. Thirdly, driving speeds on S11.5 roads were approx. by 7 km/h higher compared to S9.5 roads. These findings support the hypothesis of an association between wider shoulders, higher speeds, and increased crash severity, especially in the case of single-vehicle crashes. As a practical solution, various speed management measures, including widening to a 2+1 road, may be recommended.


2014 ◽  
Vol 42 (1) ◽  
pp. 2-15
Author(s):  
Johannes Gültlinger ◽  
Frank Gauterin ◽  
Christian Brandau ◽  
Jan Schlittenhard ◽  
Burkhard Wies

ABSTRACT The use of studded tires has been a subject of controversy from the time they came into market. While studded tires contribute to traffic safety under severe winter conditions by increasing tire friction on icy roads, they also cause damage to the road surface when running on bare roads. Consequently, one of the main challenges in studded tire development is to reduce road wear while still ensuring a good grip on ice. Therefore, a research project was initiated to gain understanding about the mechanisms and influencing parameters involved in road wear by studded tires. A test method using the institute's internal drum test bench was developed. Furthermore, mechanisms causing road wear by studded tires were derived from basic analytical models. These mechanisms were used to identify the main parameters influencing road wear by studded tires. Using experimental results obtained with the test method developed, the expected influences were verified. Vehicle driving speed and stud mass were found to be major factors influencing road wear. This can be explained by the stud impact as a dominant mechanism. By means of the test method presented, quantified and comparable data for road wear caused by studded tires under controllable conditions can be obtained. The mechanisms allow predicting the influence of tire construction and variable operating conditions on road wear.


Nutrients ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 548
Author(s):  
Chia-Wen Lu ◽  
Yi-Chen Lee ◽  
Chia-Sheng Kuo ◽  
Chien-Hsieh Chiang ◽  
Hao-Hsiang Chang ◽  
...  

The association between serum concentrations of zinc, copper, or iron and the risk of metabolic syndrome are inconclusive. Therefore, we conduct a case-control study to explore the relationship between serum levels of zinc, copper, or iron and metabolic syndrome as well as each metabolic factor and insulin resistance. We enrolled 1165 adults, aged ≥ 40 (65.8 ± 10) years in a hospital-based population to compare the serum levels of zinc, copper, and iron between subjects with and without metabolic syndrome by using multivariate logistic regression analyses. The least square means were computed by general linear models to compare serum concentrations of zinc, copper, and iron in relation to the number of metabolic factors. The mean serum concentrations of zinc, copper, and iron were 941.91 ± 333.63 μg/L, 1043.45 ± 306.36 μg/L, and 1246.83 ± 538.13 μg/L, respectively. The odds ratios (ORs) of metabolic syndrome for the highest versus the lowest quartile were 5.83 (95% CI: 3.35–10.12; p for trend < 0.001) for zinc, 2.02 (95% CI: 1.25–3.25; p for trend: 0.013) for copper, and 2.11 (95% CI: 1.24–3.62; p for trend: 0.021) for iron after adjusting for age, sex, personal habits, body mass index, and homeostatic model assessment insulin resistance. Additionally, the serum zinc, copper, and iron concentrations increased as the number of metabolic factors rose (p for trend < 0.001). This was the first study to clearly demonstrate that higher serum levels of zinc, copper, and iron were associated with the risk of metabolic syndrome and the number of metabolic factors independent of BMI and insulin resistance.


2013 ◽  
Vol 278-280 ◽  
pp. 1323-1326
Author(s):  
Yan Hua Yu ◽  
Li Xia Song ◽  
Kun Lun Zhang

Fuzzy linear regression has been extensively studied since its inception symbolized by the work of Tanaka et al. in 1982. As one of the main estimation methods, fuzzy least squares approach is appealing because it corresponds, to some extent, to the well known statistical regression analysis. In this article, a restricted least squares method is proposed to fit fuzzy linear models with crisp inputs and symmetric fuzzy output. The paper puts forward a kind of fuzzy linear regression model based on structured element, This model has precise input data and fuzzy output data, Gives the regression coefficient and the fuzzy degree function determination method by using the least square method, studies the imitation degree question between the observed value and the forecast value.


2020 ◽  
Vol 16 (3) ◽  
pp. 155014772091294
Author(s):  
Jing Wang ◽  
Huyin Zhang ◽  
Sheng Hao ◽  
Chuhao Fu

The Internet of vehicles is an essential component for building smart cities that can improve traffic safety and provide multimedia entertainment services. The cognitive radio–enabled Internet of vehicles was proposed to resolve the conflict between the increasing demand of Internet of vehicles applications and the limited spectrum resources. The multi-hop transmission is one of the most important issues in cognitive radio–enabled Internet of vehicles networks. Nevertheless, most existing forwarding solutions designed for the cognitive radio–enabled Internet of vehicles did not consider the urban expressway scenario, where primary base stations are densely installed with small coverage areas. In this case, it is difficult to ensure that the sender and the receiver of the same cognitive radio link have similar channel availability statistics, which makes cognitive radio links more likely to be interrupted. To address this challenge, we develop a multi-hop forwarding scheme to minimize the end-to-end delay for such networks. We first formulate the delay minimization problem as a non-linear integer optimization problem. Then, we propose an approach to select the relay candidates by jointly considering the high mobility of vehicles and the unique cognitive radio spectrum usage distributions in urban expressway scenarios. Finally, we propose the low-latency forwarding strategies by considering the channel availability and the delay cost of different situations of relay candidates. Simulations show the advantages of our proposed scheme, compared with state-of-art methods.


Metabolites ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 286
Author(s):  
Thijs T. Wingelaar ◽  
Paul Brinkman ◽  
Rianne de Vries ◽  
Pieter-Jan A.M. van Ooij ◽  
Rigo Hoencamp ◽  
...  

Exposure to oxygen under increased atmospheric pressures can induce pulmonary oxygen toxicity (POT). Exhaled breath analysis using gas chromatography–mass spectrometry (GC–MS) has revealed that volatile organic compounds (VOCs) are associated with inflammation and lipoperoxidation after hyperbaric–hyperoxic exposure. Electronic nose (eNose) technology would be more suited for the detection of POT, since it is less time and resource consuming. However, it is unknown whether eNose technology can detect POT and whether eNose sensor data can be associated with VOCs of interest. In this randomized cross-over trial, the exhaled breath from divers who had made two dives of 1 h to 192.5 kPa (a depth of 9 m) with either 100% oxygen or compressed air was analyzed, at several time points, using GC–MS and eNose. We used a partial least square discriminant analysis, eNose discriminated oxygen and air dives at 30 min post dive with an area under the receiver operating characteristics curve of 79.9% (95%CI: 61.1–98.6; p = 0.003). A two-way orthogonal partial least square regression (O2PLS) model analysis revealed an R² of 0.50 between targeted VOCs obtained by GC–MS and eNose sensor data. The contribution of each sensor to the detection of targeted VOCs was also assessed using O2PLS. When all GC–MS fragments were included in the O2PLS model, this resulted in an R² of 0.08. Thus, eNose could detect POT 30 min post dive, and the correlation between targeted VOCs and eNose data could be assessed using O2PLS.


Safety ◽  
2020 ◽  
Vol 6 (2) ◽  
pp. 24 ◽  
Author(s):  
Darko Babić ◽  
Dario Babić ◽  
Hrvoje Cajner ◽  
Ana Sruk ◽  
Mario Fiolić

The study investigates how the presence of traffic signalling elements (road markings and traffic signs) affects the behaviour of young drivers in night-time conditions. Statistics show that young drivers (≤30 years old) are often involved in road accidents, especially those that occur in night-time conditions. Among other factors, this is due to lack of experience, overestimation of their ability or the desire to prove themselves. A driving simulator scenario was developed for the purpose of the research and 32 young drivers took two runs using it: (a) one containing no road markings and traffic signs and (b) one containing road markings and traffic signs. In addition to the driving simulator, eye tracking glasses were used to track eye movement and an electrocardiograph was used to monitor the heart rate and to determine the level of stress during the runs. The results show statistically significant differences (dependent samples t-test) between the two runs concerning driving speed, lateral position of the vehicle, and visual scanning of the environment. The results prove that road markings and traffic signs provide the drivers with timely and relevant information related to the upcoming situation, thus enabling them to adjust their driving accordingly. The results are valuable to road authorities and provide an explicit confirmation of the importance of traffic signalling for the behaviour of young drivers in night-time conditions, and thus for the overall traffic safety.


Author(s):  
Albert Albers ◽  
Sascha Ott ◽  
Jiangang Wang

This paper proposes a method that is based on ANN for monitoring of the vehicle behavior. Considering the control loop of driver-vehicle-environment a driver should perceive the environment and the vehicle behavior by processing received information from the environment and feedback from the vehicle. The precession of the driver’s percipience is the critical element in such case. In this study, an ANN is applied for perception and prediction of the vehicle dynamic performance. Several relevant parameters from the vehicle and the environment, such as accelerator pedal travel and road grade, serve as information for the prediction. After training of the network with the measured data from a test vehicle, the network will be used for prediction of the driving speed. The comparison of the measured driving speed with the predicted speed can indicate the actual performance of the vehicle, see Figure 1.


2011 ◽  
Vol 320 ◽  
pp. 647-650
Author(s):  
Chan Yuan Liu

A method of optimal idea, in the paper, is used to process geomagnetic sensor data. The curve fitting by use of the method is more convenient than least square method (LSM). It adapts especially to process nonlinear curve fitting. Circular curve equation is fitted depending on a set of geomagnetic sensor data. It proves that the way is convenient and feasible


Sign in / Sign up

Export Citation Format

Share Document