Subjects -> HEALTH AND SAFETY (Total: 1464 journals)
    - CIVIL DEFENSE (22 journals)
    - DRUG ABUSE AND ALCOHOLISM (87 journals)
    - HEALTH AND SAFETY (686 journals)
    - HEALTH FACILITIES AND ADMINISTRATION (358 journals)
    - OCCUPATIONAL HEALTH AND SAFETY (112 journals)
    - PHYSICAL FITNESS AND HYGIENE (117 journals)
    - WOMEN'S HEALTH (82 journals)

HEALTH AND SAFETY (686 journals)

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Transportation Safety and Environment
Number of Followers: 1  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2631-4428
Published by Oxford University Press Homepage  [425 journals]
  • Pedestrian trajectory prediction method based on the Social-LSTM model for
           vehicle collision

    • First page: tdad044
      Abstract: AbstractTechniques for predicting the trajectory of vulnerable road users are important to the development of perception systems for autonomous vehicles to avoid accidents. The most effective trajectory prediction methods, such as Social-LSTM, are often used to predict pedestrian trajectories in normal passage scenarios. However, they can produce unsatisfactory prediction results and data redundancy, as well as difficulties in predicting trajectories using pixel-based coordinate systems in collision avoidance systems. There is also a lack of validations using real vehicle-to-pedestrian collisions. To address these issues, some insightful approaches to improve the trajectory prediction scheme of Social-LSTM were proposed, such methods included transforming pedestrian trajectory coordinates and converting image coordinates to world coordinates. The YOLOv5 detection model was introduced to reduce target loss and improve prediction accuracy. The DeepSORT algorithm was employed to reduce the number of target transformations in the tracking model. Image Perspective Transformation (IPT) and Direct Linear Transformation (DLT) theories were combined to transform the coordinates to world coordinates, identifying the collision location where the accident could occur. The performance of the proposed method was validated by training tests using MS COCO (Microsoft Common Objects in Context) and ETH/UCY datasets. The results showed that the target detection accuracy was more than 90% and the prediction loss tends to decrease with increasing training steps, with the final loss value less than 1%. The reliability and effectiveness of the improved method were demonstrated by benchmarking system performance to two video recordings of real pedestrian accidents with different lighting conditions.
      PubDate: Tue, 19 Dec 2023 00:00:00 GMT
      DOI: 10.1093/tse/tdad044
      Issue No: Vol. 6, No. 3 (2023)
       
  • A new targeted on-ramp control approach considering both efficiency and
           equity

    • First page: tdad040
      Abstract: AbstractOn-ramp control is an effective approach for alleviating traffic congestion on highways. However, there is still a lack of on-ramp control approaches applicable to large regional highway networks. Here, we develop a targeted on-ramp control approach applicable to regional highway networks by taking advantage of the vehicle source information, which pinpoints the on-ramps contributing major traffic flow to the highway bottleneck. Furthermore, a combined and tunable controlling index is proposed to enhance the equity of the generated traffic control scheme. The proposed on-ramp control approach is validated on an actual large highway network using actual travel demand data. Results indicate that the proposed approach can well mitigate the traffic congestion of highway bottleneck while at the same time enhancing the equity and practicability of the generated traffic control scheme.
      PubDate: Tue, 05 Dec 2023 00:00:00 GMT
      DOI: 10.1093/tse/tdad040
      Issue No: Vol. 6, No. 3 (2023)
       
  • Risk mapping of wildlife–vehicle collisions across the state of Montana,
           USA: a machine-learning approach for imbalanced data along rural roads

    • First page: tdad043
      Abstract: AbstractWildlife–vehicle collisions (WVCs) with large animals are estimated to cost the USA over 8 billion USD in property damage, tens of thousands of human injuries and nearly 200 human fatalities each year. Most WVCs occur on rural roads and are not collected evenly among road segments, leading to imbalanced data. There are a disproportionate number of analysis units that have zero WVC cases when investigating large geographic areas for collision risk. Analysis units with zero WVCs can reduce prediction accuracy and weaken the coefficient estimates of statistical learning models. This study demonstrates that the use of the synthetic minority over-sampling technique (SMOTE) to handle imbalanced WVC data in combination with statistical and machine-learning models improves the ability to determine seasonal WVC risk across the rural highway network in Montana, USA. An array of regularized variables describing landscape, road and traffic were used to develop negative binomial and random forest models to infer WVC rates per 100 million vehicle miles travelled. The random forest model is found to work particularly well with SMOTE-augmented data to improve the prediction accuracy of seasonal WVC risk. SMOTE-augmented data are found to improve accuracy when predicting crash risk across fine-grained grids while retaining the characteristics of the original dataset. The analyses suggest that SMOTE augmentation mitigates data imbalance that is encountered in seasonally divided WVC data. This research provides the basis for future risk-mapping models and can potentially be used to address the low rates of WVCs and other crash types along rural roads.
      PubDate: Thu, 30 Nov 2023 00:00:00 GMT
      DOI: 10.1093/tse/tdad043
      Issue No: Vol. 6, No. 3 (2023)
       
  • Evolutionary game analysis of shared parking market diffusion under
           government management

    • First page: tdad041
      Abstract: AbstractThe imbalance between supply and demand in urban settings poses a significant barrier to the sustainable advancement of urban transportation. Shared parking serves as a viable solution to mitigate these challenges. Nevertheless, for its sustained growth, a regulatory mechanism enforced by the government is imperative. To promote shared parking market diffusion, we construct an evolutionary game model that incorporates the government, enterprises and parking demanders. It explores stabilization strategies for these stakeholders and identifies multiple equilibrium states under different parameter conditions. The results show that the rate and stability of these evolutionary strategies are constrained by the mutual benefits derived by the three parties. Furthermore, such stakeholders are reciprocally influenced by their willingness to engage in shared parking to varying degrees. Government subsidies serve as a determining factor for the strategic choices made by both enterprises and demanders, albeit at different evolutionary rates. Demanders who have a higher value of time tend to park on-street, thereby influencing enterprise strategies. To foster the long-term growth of the shared parking market, the government must enact appropriate subsidy policies, maintain consistent regulations and advocate for increased subsidies for parking demanders to reduce the effect of temporal heterogeneity on parking behavioural choices.
      PubDate: Mon, 27 Nov 2023 00:00:00 GMT
      DOI: 10.1093/tse/tdad041
      Issue No: Vol. 6, No. 3 (2023)
       
  • The characteristics of driver lane-changing behaviour in congested road
           environments

    • First page: tdad039
      Abstract: AbstractLane-changing behaviour is one of the complex driving behaviours. The lane-changing behaviour of drivers may exacerbate congestion, however driver behavioural characteristics are difficult to accurately acquire and quantify, and thus tend to be simplified or ignored in existing lane-changing models. In this paper, the Bik-means clustering algorithm is used to analyse the urban road congestion state discrimination method. Then, simulated driving tests were conducted for different traffic congestion conditions. Through the force feedback system and infrared camera, the data of driver lane-changing behaviours at different traffic congestion levels are obtained separately, and the definitions of the start and end points of a vehicle changing lanes are determined. Furthermore, statistical analysis and discussion of key feature parameters including driver lane-changing behaviour data and visual data under different levels of traffic congestion were conducted. It is found that the average lane-change intention times in each congestion state are 2 s, 4 s, 6 s and 7 s, while the turn-signal duration and the number of rear-view mirror observations have similar patterns of change to the data on lane-changing intention duration. Moreover, drivers’ pupil diameters become smaller during the lane-changing intention phase, and then relatively enlarge during lane-changing; the range of pupil variation is roughly 3.5 mm to 4 mm. The frequency of observing the vehicle in front of the target lane increased as the level of congestion increased, and the frequency of observation in the driver's mirrors while changing lanes approximately doubled compared to driving straight ahead, and this ratio increased as the level of congestion increased.
      PubDate: Tue, 21 Nov 2023 00:00:00 GMT
      DOI: 10.1093/tse/tdad039
      Issue No: Vol. 6, No. 3 (2023)
       
  • Effect of helmet-wearing regulation on electric-bike riders: a case study
           of two cities in China

    • First page: tdad038
      Abstract: AbstractObjectivesElectric bikes (e-bikes) are widely used for commuting and delivery in China. With the rapid increase in e-bikes on the road, related accidents have become crucial issues threatening the public. This research aims to explore the protective effect of helmet-wearing regulation and to investigate some factors influencing head injury with reference to two case cities in China, obtaining information to protect e-bike riders.MethodsThe traffic police-reported crash data cover the periods before and after the implementation of helmet-wearing regulations in Taizhou (with data from 2017 to 2019) and Nanning (with data in 2020) of China. Preliminary statistical analysis, logistic regression and chi-square test with a Bonferroni correction were applied in the research.ResultsA lack of helmets was common among victims in the context of a high helmet-wearing rate among general e-bike riders in Taizhou, indicating that fatality could be avoided to some extent by wearing helmets. Specifically, helmet wearing could reduce the probability of suffering fatal head injury by 6.4%. After the regulation implementation in Taizhou, the proportion of fatal head injuries decreased from 89% to 79%, remaining at a high level, which indicates that other measures in addition to helmet-wearing regulations should be taken. According to the results from Nanning, mandatory regulation worked more effectively than encouraged regulation in terms of reducing head injury.ConclusionsMandatory helmet-wearing regulations are highly recommended to policymakers to reduce head injury among e-bike riders. Measures in addition to helmet-wearing regulation, e.g. enhancing law-abiding awareness and improving road infrastructure, should be considered to further protect e-bike riders.
      PubDate: Thu, 26 Oct 2023 00:00:00 GMT
      DOI: 10.1093/tse/tdad038
      Issue No: Vol. 6, No. 3 (2023)
       
  • Research on the stability of virtual coupling train formation based on a
           PID controller under the influence of time delay

    • First page: tdad037
      Abstract: AbstractAs the latest research direction of train-to-train communication, virtual coupling train formation technology has attracted the attention of many scholars. This paper studies the influence of time delay on the formation of virtual coupled trains. We proposed a distributed PID controller, which means that trains can still form a stable fleet operation under the influence of communication delay and control delay. After modelling and analysis, the research uses Matlab to conduct simulation, involving two sets of experiments. Factors including speed, acceleration, position, position error, expected distance between adjacent trains and actual distance between adjacent trains are simulated. The results demonstrate that the distributed PID controller can effectively control the impact of time delay on the virtual coupling fleet.
      PubDate: Tue, 10 Oct 2023 00:00:00 GMT
      DOI: 10.1093/tse/tdad037
      Issue No: Vol. 6, No. 3 (2023)
       
  • BLE beacons for sample position estimation in a life science automation
           laboratory

    • First page: tdad033
      Abstract: AbstractEstimation of the sample position is essential for working process monitoring and management in the life science automation laboratory. Bluetooth low-energy (BLE) beacons have the advantages of low price, small size and low energy consumption, which make them a promising solution for sample position estimation in the automated laboratory. Several fingerprinting models have been proposed to achieve indoor localization with the received signal strength (RSS) data. However, most of the research depends on intensive beacon installation. Proximity estimation, which depends entirely on one beacon, is more suitable for sample position estimation in large automated laboratories. The complexity of the life science automation laboratory environment brings challenges to the traditional path loss model (PLM), which is a widely used radio wave propagation model-based proximity estimation method. In this paper, BLE sensing devices for sample position estimation are proposed. The BLE beacon-based proximity estimation is discussed in the framework of machine learning, in which the support vector regression (SVR) is utilized to model the nonlinear relationship between the RSS data and distance, and the Kalman filter is utilized to decrease the RSS data deviation. The experimental results over different environments indicate that the SVR outperforms the PLM significantly, and provides 1 m absolute errors for more than 95% of the testing samples. The Kalman filter brings benefits to stable distance predictions. Apart from proximity-based sample position estimation, the proposed framework turned out to be effective in position estimation between parallel workbenches and position estimation on an automated workstation.
      PubDate: Mon, 09 Oct 2023 00:00:00 GMT
      DOI: 10.1093/tse/tdad033
      Issue No: Vol. 6, No. 3 (2023)
       
  • A novel multi-state bogie system reliability evaluation approach by
           extended d-MC model for high-speed trains

    • First page: tdad036
      Abstract: AbstractBogie is a pivotal system and plays a critical part in the safety and reliability management of high-speed rail. However, the available bogie system reliability analysis methods lack the consideration of multi-state characteristics, and the common multi-state reliability analysis methods, being an NP-hard problem, lead to low efficiency. In order to overcome these drawbacks, this paper proposes a novel multi-state rail train bogie system reliability analysis approach based on the extended d-MC model. Three different function interactions within the bogie system are considered to build the multi-state bogie system flow network model. Meanwhile, an extended d-MC model is established to remove unnecessary d-MC candidates and duplicates, which greatly enhances the computing efficiency. The bogie system reliability is calculated, and examples are provided. Numerical experiments are carried out for the different operational conditions of the bogie system and are used to test the practicability of the method proposed in this article; it is found that this method outperforms a newly developed method in solving multi-state reliability problems.
      PubDate: Fri, 22 Sep 2023 00:00:00 GMT
      DOI: 10.1093/tse/tdad036
      Issue No: Vol. 6, No. 3 (2023)
       
  • Decision-making method for high-speed rail early warning system in complex
           earthquake situations

    • First page: tdad034
      Abstract: AbstractTo address the shortcomings in decision-making methods for ground motion threshold warning models in high-speed rail earthquake early warning systems (HSREEWs), we propose a dual judgement method and corresponding early warning process for earthquake early warning decisions based on joint peak ground acceleration (PGA) and complex earthquake environmental risk evaluation (ERE) values. First, we analyse the characteristics of four complex earthquake environments based on the characteristics of high-speed rail (HSR) operating environments. Second, we establish an earthquake environmental risk evaluation index system and propose an adversarial interpretive structure modelling method-based complex earthquake situation evaluation model (AISM-based ESEM). The AISM method firstly evaluates the proximity by the TOPSIS (technique for order preference by similarity to an ideal solution) method, then effectively rank targets with fuzzy attributes through opposite hierarchical extraction rules without sacrificing system functionality. Since PGA can reflect the current size of earthquake energy, combining PGA thresholds with ESEM-derived values of ERE can effectively determine the risk status of each train and make decisions on the most appropriate alarm form and control measures for that status. Finally, case analysis results under the background of Wenchuan Earthquake show that the new early warning decision-making method accurately assesses environmental risks in affected areas and provides corresponding warning levels as a supplement to existing HSREEWs warning models.
      PubDate: Fri, 15 Sep 2023 00:00:00 GMT
      DOI: 10.1093/tse/tdad034
      Issue No: Vol. 6, No. 3 (2023)
       
  • Analysis of rail–bridge interaction of a high-speed railway suspension
           bridge under near-fault pulse-type earthquakes

    • First page: tdad032
      Abstract: AbstractDue to the limitations of railway route selection, some high-speed railways are inevitably built near or across fault zones. To study the distribution of rail–bridge interaction under different load history states of suspension bridges under three types of near-fault pulse-type earthquakes, this paper takes China's longest high-speed railway suspension bridge—Wufengshan Yangtze River Bridge—as the background and establishes a spatial model of the rail–bridge interaction of a suspension bridge. The results show that: under the constant load state, the distribution of additional force under three types of pulse-type earthquakes is generally consistent, and pulse-type earthquakes produce more significant responses than non-pulse-type earthquakes; with fling-step pulse being the largest, it is advised to specifically consider the influence of the fling-step pulse in the calculation. Under the initial condition of the main beam temperature loading history, all rail-bridge additional forces increase significantly, particularly affecting the steel rail system. The value of the rail–bridge interaction additional force under the near-fault earthquake in the initial state of the suspension bridge when the train deflection load is loaded from the tower to the mid-span is more significant and particularly unfavourable. The initial effect of the braking load will weaken the effect of the deflection load loading history. The results of the study indicate that the effect of the initial state of suspension bridges is an important factor influencing the rail–bridge interaction under near-fault pulse-type earthquakes, which needs to be considered in future seismic design.
      PubDate: Fri, 30 Jun 2023 00:00:00 GMT
      DOI: 10.1093/tse/tdad032
      Issue No: Vol. 6, No. 3 (2023)
       
  • A review of traffic behaviour and intelligent driving at roundabouts based
           on a microscopic perspective

    • First page: tdad031
      Abstract: AbstractThe contradiction between increasing traffic and the relatively poor roundabout infrastructure is getting stronger. The control and optimization of the macroscopic traffic flow needs to be improved to resolve congestion and safety problems at roundabouts and the connected road network. In order to better understand the gaps and trends in this field, we have systematically reviewed the main research and developments in traffic phenomena, driving behaviour, autonomous vehicles (AVs), intelligent connected vehicles and real vehicle trajectory data sets at roundabouts. The study is based on 388 papers about roundabouts, selected through a comprehensive literature search. The review demonstrates that based on a microscopic perspective, sensing, prediction, decision-making, planning and control aspects of AVs and intelligent connected vehicles can be designed and optimized to fundamentally and significantly improve traffic capacity and driving safety at roundabouts. However, the generation mechanism of traffic conflicts among traffic participants at roundabouts is complex, which is a tremendous challenge for the systematic design of AVs. Therefore, based on naturalistic driving data and machine learning theory, it is an important research direction to build driver models by learning and imitating human driver decision-making and driving behaviours.
      PubDate: Tue, 13 Jun 2023 00:00:00 GMT
      DOI: 10.1093/tse/tdad031
      Issue No: Vol. 6, No. 3 (2023)
       
  • A flexible model-free tram signal priority method with a large
           coordination scope in China

    • First page: tdad027
      Abstract: AbstractTram systems with the advantages of reliable operation, comfort, low emissions and moderate capacity have been quite popular in recent years in China. However, there are still problems with tram signal control (e.g. evaluation model, signal control strategies). In-depth analysis on existing operational issues of trams, calculation of two evaluation indexes, as well as a flexible model-free tram signal priority method were developed to deal with tram problems. Empirical research in Songjiang District, Shanghai shows that: (1) The function of the green extension strategy is limited with c.a. 10% tram priority improvement, while the optimal one can reach to 85% higher on average. (2) A scheme with a benefit for trams and with no negative impact, and even benefits, for general traffic can be realized. (3) The optimal solution is beneficial for intersections with a maximum c.a. 70% amelioration with delay decreasing from 132.7 s/vehicle to 40.89 s/vehicle, or from 104.77 s/capita to 22.31 s/capita. This paper has great significance for the signal optimization and safety of tram systems, even the development of a comprehensive transportation system for a city.
      PubDate: Sat, 27 May 2023 00:00:00 GMT
      DOI: 10.1093/tse/tdad027
      Issue No: Vol. 6, No. 3 (2023)
       
 
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  Subjects -> HEALTH AND SAFETY (Total: 1464 journals)
    - CIVIL DEFENSE (22 journals)
    - DRUG ABUSE AND ALCOHOLISM (87 journals)
    - HEALTH AND SAFETY (686 journals)
    - HEALTH FACILITIES AND ADMINISTRATION (358 journals)
    - OCCUPATIONAL HEALTH AND SAFETY (112 journals)
    - PHYSICAL FITNESS AND HYGIENE (117 journals)
    - WOMEN'S HEALTH (82 journals)

HEALTH AND SAFETY (686 journals)

We no longer collect new content from this publisher because the publisher has forbidden systematic access to its RSS feeds.
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JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


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