• Title/Summary/Keyword: traffic conditions

Search Result 1,345, Processing Time 0.027 seconds

Prediction of Life Expectancy of Asphalt Road Pavement by Region (아스팔트 도로포장의 균열률에 대한 지역별 기대수명 추정)

  • Song, Hyun Yeop;Choi, Seung Hyun;Han, Dae Seok;Do, Myung Sik
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.41 no.4
    • /
    • pp.417-428
    • /
    • 2021
  • Since future maintenance cost estimation of infrastructure involves uncertainty, it is important to make use of a failure prediction model. However, it is difficult for local governments to develop accurate failure prediction models applicable to infrastructure due to a lack of budget and expertise. Therefore, this study estimated the life expectancy of asphalt road pavement of national highways using the Bayesian Markov Mixture Hazard model. In addition, in order to accurately estimate life expectancy, environmental variables such as traffic volume, ESAL (Equivalent Single Axle Loads), SNP (Structural Number of Pavement), meteorological conditions, and de-icing material usage were applied to retain reliability of the estimation results. As a result, life expectancy was estimated from at least 13.09 to 19.61 years by region. By using this approach, it is expected that it will be possible to estimate future maintenance cost considering local failure characteristics.

A Study of the Vehicle Allocation Planning System based on Transportation Cost (운송비 기반 배차계획 시스템에 관한 연구)

  • Kang, Hee-Yong;Kim, Jeong-Su;Shin, Yong-Tae;Kim, Jong-Bae
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2014.05a
    • /
    • pp.319-322
    • /
    • 2014
  • Due to the active use of the internet currently, the transportation volume of logistics firms is dramatically increasing, but it is not easy to secure available vehicles and vehicle suppliers, so it is the most important for logistics companies to streamline transportations management and process. For such reason, there have been a number of studies to deal with VRP and VSP for efficient vehicle allocation planning of vehicle suppliers and vehicles. But it is hard to reflect traffic situations changing everyday and detailed geographic conditions, and it requires big scale of database and huge calculation time consumption as increase number of depots, which is very inefficient. For solving the vehicle allocation planning problems of 3PL firms with various constraints due to the transportation cost, this paper suggest new vehicle allocation information system and an algorithm based transportation cost/income. Also this paper presents actual results applied to a logistics company. As a result, the transportation profit of vehicle suppliers increased by 11 percent in average, when the developed transportation cost-based vehicle allocation system applied.

  • PDF

An Evaluation of Moisture Sensitivity of Asphalt Concrete Pavement Due to Aging (노화에 따른 아스팔트 콘크리트 포장의 수분민감성 평가)

  • Kim, Kyungnam;Kim, Yooseok;Kim, Nakseok
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.39 no.4
    • /
    • pp.523-530
    • /
    • 2019
  • Pavement distress and traffic accidents are caused by pot-hole. In addition, direct and indirect damages of road users are increasing, such as loss of life due to personal injury and damage to vehicles. Generally, the asphalt concrete pavements are continuously aging from the production process to the terminal performance period. Aging causes stripping due to cracks and moisture penetration and weakening the pavement structure to induce pot-hole. In this study, adhesion performance and moisture sensitivity were evaluated according to aging degree in order to investigate the effect of aging on asphalt pavement. As a result of the study, the viscosity of the asphalt binder was increased with aging and the bond strength of the aged was increased 2~3 times than that of the unaged. The results of accelerated aging test showed an increases in indirect tensile strength and the increase in the TSR (Tensile Strength Ratio) by 4.2~8.9 %. As a result, it is noted that the anti-stripping and adhesion performances of the aged asphalt concrete are improved compared to the unaged one under the aging conditions of asphalt binder coated on aggregates.

A Batch Processing Algorithm for Moving k-Nearest Neighbor Queries in Dynamic Spatial Networks

  • Cho, Hyung-Ju
    • Journal of the Korea Society of Computer and Information
    • /
    • v.26 no.4
    • /
    • pp.63-74
    • /
    • 2021
  • Location-based services (LBSs) are expected to process a large number of spatial queries, such as shortest path and k-nearest neighbor queries that arrive simultaneously at peak periods. Deploying more LBS servers to process these simultaneous spatial queries is a potential solution. However, this significantly increases service operating costs. Recently, batch processing solutions have been proposed to process a set of queries using shareable computation. In this study, we investigate the problem of batch processing moving k-nearest neighbor (MkNN) queries in dynamic spatial networks, where the travel time of each road segment changes frequently based on the traffic conditions. LBS servers based on one-query-at-a-time processing often fail to process simultaneous MkNN queries because of the significant number of redundant computations. We aim to improve the efficiency algorithmically by processing MkNN queries in batches and reusing sharable computations. Extensive evaluation using real-world roadmaps shows the superiority of our solution compared with state-of-the-art methods.

A Study on Estimating Method of Vehicle Fuel Consumption Using GPS Data (GPS 데이터를 이용한 차량의 연료소모량 연산법 연구)

  • Ko, Kwang-Ho
    • Journal of the Korean Society of Industry Convergence
    • /
    • v.23 no.6_2
    • /
    • pp.949-956
    • /
    • 2020
  • It's important to measure fuel consumption of vehicles. It's possible to monitor green house gas from vehicles for various traffic conditions with the measured data. It's effective to eco-drive for drivers with fuel consumption data also. There's a display of fuel consumption in the modern vehicles, but it's not useful to get the data from the display. An estimating method for fuel consumption of a vehicle is suggested in the study. It's a simple but an effective method using GPS data. The GPS data(speed, acceleration, road slope) and vehicle data(weight, frontal area, model year, certified fuel economy) is necessary to estimate the fuel consumption for the method. It calculates driving resistance force to estimate engine power. Then it estimates the necessary fuel consumption to maintain the engine power with fuel-power conversion factor. The conversion factor is corrected with certified fuel economy, model year and rated power. The precision of the methods is checked with road test data. The test driving data was measured with GPS and OBD. The error of the estimated fuel consumption for the measured one is about 1.8%. But the error is large for the 1000 and 100 data number from the total data number of about 10,000. The error is from the larger change range of the GPS data than the one of the measured fuel consumption data. But the proposed estimating method is useful to percept the fuel consumption change for better fuel economy with simple gadget like smart phone or other GPS instruments.

Performance Analysis of Transport Time and Legal Stability through Smart OTP Access System for SMEs in Connected Industrial Parks

  • Kim, Ilgoun;Jeong, Jongpil
    • International Journal of Advanced Culture Technology
    • /
    • v.9 no.1
    • /
    • pp.224-241
    • /
    • 2021
  • According to data from the National Police Agency, 75.5 percent of dead traffic accidents in Korea are truck accidents. About 1,000 people die in cargo truck accidents in Korea every year, and two to three people die in cargo truck accidents every day. In the survey, Korean cargo workers answer poor working conditions as an important cause of constant truck accidents. COVID 19 is increasing demand for non-face-to-face logistics. The inefficiency of the Korean transportation system is leading to excessive work burden for small logistics The inefficiency of the Korean transportation system is causing excessive work burden for small individual carriers. The inefficiency of the Korean transportation system is also evidenced by the number of deaths from logistics industry disasters that have risen sharply since 2020. Small and medium-sized Korean Enterprises located in CIPs (Connected Industrial Parks) often do not have smart access certification systems. And as a result, a lot of transportation time is wasted at the final destination stage. In the logistics industry, time is the cost and time is the revenue. The logistics industry is the representative industry in which time becomes money. The smart access authentication system architecture proposed in this paper allows small logistics private carriers to improve legal stability, and SMEs (Small and Medium-sized Enterprises) in CIPs to reduce logistics transit time. The CIPs smart access system proposed in this paper utilizes the currently active Mobile OTP (One Time Password), which can significantly reduce system design costs, significantly reduce the data capacity burden on individual cell phone terminals, and improve the response speed of individual cell phone terminals. It is also compatible with the OTP system, which was previously used in various ways, and the system reliability through the long period of use of the OTP system is also high. User customers can understand OTP access systems more easily than other smart access systems.

Statistical Techniques to Derive Heavy Rain Impact Level Criteria Suitable for Use in Korea (통계적 기법을 활용한 한국형 호우영향도 기준 산정 연구)

  • Lee, Seung Woon;Kim, Byung Sik;Jung, Seung Kwon
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.40 no.6
    • /
    • pp.563-569
    • /
    • 2020
  • Presenting the impact of meteorological disasters departs from the traditional weather forecasting approach for meteorological phenomena. It is important to provide impact forecasts so that precautions against disruption and damage can be taken. Countries such as the United States, the U.K., and France already conduct impact forecasting for heavy rain, heavy snow, and cold weather. This study improves and applies forecasts of the impact of heavy rain among various weather phenomena in accordance with domestic conditions. A total of 33 impact factors for heavy rain were constructed per 1 km grids, and four impact levels (minimal, minor, significant, and severe) were calculated using standard normal distribution. Estimated criteria were used as indicators to estimate heavy rain risk impacts for 6 categories (residential, commercial, utility, community, agriculture, and transport) centered on people, facilities, and traffic.

Characteristics of Road Weather Elements and Surface Information Change under the Influence of Synoptic High-Pressure Patterns in Winter (겨울철 고기압 영향에서 도로 위 기상요소와 노면정보 변화 특성에 관한 연구)

  • Kim, Baek-Jo;Nam, Hyounggu;Kim, Seon-Jeong;Kim, Geon-Tae;Kim, Jiwan;Lee, Yong Hee
    • Journal of Environmental Science International
    • /
    • v.31 no.4
    • /
    • pp.329-339
    • /
    • 2022
  • Better understanding the mechanism of black ice occurrence on the road in winter is necessary to reduce the socio-economic damage it causes. In this study, intensive observations of road weather elements and surface information under the influence of synoptic high-pressure patterns (22nd December, 2020 and 29th January, and 25th February, 2021) were carried out using a mobile observation vehicle. We found that temperature and road surface temperature change is significantly influenced by observation time, altitude and structure of the road, surrounding terrain, and traffic volume, especially in tunnels and bridges. In addition, even if the spatial distribution of temperature and road surface temperature for the entire observation route is similar, there is a difference between air and road surface temperatures due to the influence of current weather conditions. The observed road temperature, air temperature and air pressure in Nongong Bridge were significantly different to other fixed road weather observation points.

Neural network based numerical model updating and verification for a short span concrete culvert bridge by incorporating Monte Carlo simulations

  • Lin, S.T.K.;Lu, Y.;Alamdari, M.M.;Khoa, N.L.D.
    • Structural Engineering and Mechanics
    • /
    • v.81 no.3
    • /
    • pp.293-303
    • /
    • 2022
  • As infrastructure ages and traffic load increases, serious public concerns have arisen for the well-being of bridges. The current health monitoring practice focuses on large-scale bridges rather than short span bridges. However, it is critical that more attention should be given to these behind-the-scene bridges. The relevant information about the construction methods and as-built properties are most likely missing. Additionally, since the condition of a bridge has unavoidably changed during service, due to weathering and deterioration, the material properties and boundary conditions would also have changed since its construction. Therefore, it is not appropriate to continue using the design values of the bridge parameters when undertaking any analysis to evaluate bridge performance. It is imperative to update the model, using finite element (FE) analysis to reflect the current structural condition. In this study, a FE model is established to simulate a concrete culvert bridge in New South Wales, Australia. That model, however, contains a number of parameter uncertainties that would compromise the accuracy of analytical results. The model is therefore updated with a neural network (NN) optimisation algorithm incorporating Monte Carlo (MC) simulation to minimise the uncertainties in parameters. The modal frequency and strain responses produced by the updated FE model are compared with the frequency and strain values on-site measured by sensors. The outcome indicates that the NN model updating incorporating MC simulation is a feasible and robust optimisation method for updating numerical models so as to minimise the difference between numerical models and their real-world counterparts.

Moment-rotational analysis of soil during mining induced ground movements by hybrid machine learning assisted quantification models of ELM-SVM

  • Dai, Bibo;Xu, Zhijun;Zeng, Jie;Zandi, Yousef;Rahimi, Abouzar;Pourkhorshidi, Sara;Khadimallah, Mohamed Amine;Zhao, Xingdong;El-Arab, Islam Ezz
    • Steel and Composite Structures
    • /
    • v.41 no.6
    • /
    • pp.831-850
    • /
    • 2021
  • Surface subsidence caused by mining subsidence has an impact on neighboring structures and utilities. In other words, subsurface voids created by mining or tunneling activities induce soil movement, exposing buildings to physical and/or functional destruction. Soil-structure is evaluated employing probability distribution laws to account for their uncertainty and complexity to estimate structural vulnerability. In this study, to investigate the displacement field and surface settlement profile caused by mining subsidence, on the basis of a Winklersoil model, analytical equations for the moment-rotation response ofsoil during mining induced ground movements are developed. To define the full static moment-rotation response, an equation for the uplift-yield state is constructed and integrated with equations for the uplift- and yield-only conditions. The constructed model's findings reveal that the inverse of the factor of safety (x) has a considerable influence on the moment-rotation curve. The maximal moment-rotation response of the footing is defined by X = 0:6. Despite the use of Winkler model, the computed moment-rotation response results derived from the literature were analyzed through the ELM-SVM hybrid of Extreme Learning Machine (ELM) and Support Vector Machine (SVM). Also, Monte Carlo simulations are used to apply continuous random parameters to assess the transmission of ground motions to structures. Following the findings of RMSE and R2, the results show that the choice of probabilistic laws of input parameters has a substantial impact on the outcome of analysis performed.