Estimation of Vehicle Emission on Mainline Freeway Under Isolated and Integrated Ramp Metering Strategies

Du, Jian; Li, Qing; Qiao, Fengxiang; Yu, Lei

doi:10.30638/eemj.2018.123

Cited by 37 publications

(24 citation statements)

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“…As an industry that recently stood on the cusp of the era of the Internet of Things (IoT) and consumerism, the fresh ecommerce business has gained increasing attention [1][2][3][4][5]. Of all the critical factors that play a role in the production and operation management of a fresh ecommerce business, cold chain logistics has been proved to be the key process that determines its profitability and competitiveness [6,7]. Since the construction of the cold chain logistics infrastructure network in the fresh ecommerce industry is still nascent, there are problems that business managers cannot ignore.…”

Section: Introductionmentioning

confidence: 99%

Applying catastrophe progression method to evaluate the service quality of cold chain logistics

Zhang

Shi

Qiu

2020

Complex Intell. Syst.

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Logistics service quality (LSQ) is one of the key influential factors in the success of an ecommerce business. In view of the complexity of the topic, this paper proposes a novel model for fresh ecommerce cold chain LSQ evaluation based on the catastrophe progression method. In the proposed methodology, first an index system for evaluating the fresh ecommerce cold chain LSQ is established from the perspective of service recipients. Then, the comprehensive weight of each evaluation index is determined using a combination weighting approach based on maximizing deviations and fuzzy set theory. The priority weights and the ranking of the indices are determined using the catastrophe progression method. Finally, the model is applied in a case study of two representative enterprises. The study demonstrates the validity and practical applicability of the proposed model. Also, based on the evaluation results and findings, some improvement suggestions are made for improving the cold chain LSQ of similar kinds of fresh ecommerce companies.

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Section: Introductionmentioning

confidence: 99%

Applying catastrophe progression method to evaluate the service quality of cold chain logistics

Zhang

Shi

Qiu

2020

Complex Intell. Syst.

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“…Other scholars combined Bayesian network methods to study the selection of green suppliers in agricultural production [5]. In one study, an integrated metring strategy was adopted to estimate instant vehicle emissions by measuring the speed and acceleration of vehicles on slopes, thus improving the study on the impact of ramp metring on the environment [6]. In another study, scholars applied an improved whale optimization algorithm and proposed an algorithm framework for the location model of electric vehicle charging stations based on the calculation of a large number of examples [7].…”

Section: Introductionmentioning

confidence: 99%

An XGBoost Algorithm for Predicting Purchasing Behaviour on E-Commerce Platforms

Song

Liu

2020

Teh. vjesn.

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To improve and enhance the predictive ability of consumer purchasing behaviours on e-commerce platforms, a new method of predicting purchasing behaviour on e-commerce platforms is created in this paper. This study introduced the basic principles of the XGBoost algorithm, analysed the historical data of an e-commerce platform, pre-processed the original data and constructed an e-commerce platform consumer purchase prediction model based on the XGBoost algorithm. By using the traditional random forest algorithm for comparative analysis, the K-fold cross-validation method was further used, combined with model performance indicators such as accuracy rate, precision rate, recall rate and F1-score to evaluate the classification accuracy of the model. The characteristics of the importance of the results were found through visual analysis. The results indicated that using the XGBoost algorithm to predict the purchasing behaviours of e-commerce platform consumers can improve the performance of the method and obtain a better prediction effect. This study provides a reference for improving the accuracy of e-commerce platform consumers' purchasing behaviours prediction, and has important practical significance for the efficient operation of e-commerce platforms.

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“…Bae et al [7] adopted ramp metering to evaluate the changes in traffic flow and CO 2 emission variations, which suggested that ramp metering makes a great contribution to the reduction of CO 2 emissions. Du et al [8,9] found that the isolated and integrated ramp metering approaches can improve mobility and reduce travel delay. However, relevant studies are limited and emissions vary with vehicle type.…”

Section: Introductionmentioning

confidence: 99%

Observed Characteristics and Modeled Emissions of Transit Buses on Ramps

et al. 2020

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On-ramps and off-ramps that serve as connections between high-speed facilities and arterials are potential hotspots for vehicle emissions. The engine load associated with grade and acceleration on uphill ramps can lead to significant emissions of criteria pollutants and greenhouse gases (GHGs) over a short distance. This study explores transit bus operations and emissions at ramps using Global Positioning System (GPS) data collected from Detroit transit buses. Ramp-associated operating data are extracted from the vehicle traces using ArcGIS and assigned to the applicable United States Environmental Protection Agency’s emission rates, i.e., EPA’s Motor Vehicle Emission Simulator (MOVES). The results show that transit bus emission rates for on-ramp operations at 40 mph (64.37 km/h) are about double the average emission rate on the MOVES highway cycles. For lower on-ramp speeds (< 64.37 km/h), as average speeds decrease, on-ramp emission rates drop roughly to the highway emission rates given the less aggressive acceleration noted in the data. Off-ramp emission rates are approximately half of the highway emission rates. The study also finds that post-ramp acceleration, right after buses enter the highway from the on-ramp, contributes to high emissions, because of the high-speed and high-power operations. This is true for the loop on-ramp, where the bus emission rate after entering the highway is higher than the emissions associated with driving on the ramp. On-ramp emissions are found to vary across a wide range of conditions, indicating that further study and more data are needed to explore the overall impacts of on-ramp and post-ramp activity in emissions modeling. A sensitivity analysis of ramp grade effect on emission indicates that ramp grade should be specifically considered in project-level analyses. The research results are useful for understanding ramp driving characteristics, the potential impacts of ramp grade on emissions, and the ramp hotspot analysis.

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Estimation of Vehicle Emission on Mainline Freeway Under Isolated and Integrated Ramp Metering Strategies

Cited by 37 publications

References 0 publications

Applying catastrophe progression method to evaluate the service quality of cold chain logistics

Applying catastrophe progression method to evaluate the service quality of cold chain logistics

An XGBoost Algorithm for Predicting Purchasing Behaviour on E-Commerce Platforms

Observed Characteristics and Modeled Emissions of Transit Buses on Ramps

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