scholarly journals Biobjective Emergency Logistics Scheduling Model Based on Uncertain Traffic Conditions

2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Youqiang Sun ◽  
Yeqing Ren ◽  
Xingjuan Cai
Keyword(s):  
Cloud Model ◽  
Traffic Volume ◽  
One Dimension ◽  
Trajectory Data ◽  
Inference Procedure ◽  
Traffic Conditions ◽  
Mutation Operators ◽  
Scheduling Model ◽  
Emergency Logistics ◽  
Proposed Model

Emergency logistics scheduling appears more and more important in modern society because of frequent occurrence of unpredictable disasters. Most of the existing studies consider a certain emergency logistics scheduling model, and most of them are based on an ideal scenario. Considering the uncertain traffic condition and the real road condition, a biobjective emergency logistics scheduling model is proposed, which includes two objectives: transportation time and transportation cost. The uncertainty of the proposed model is reflected in two aspects: the occurrence time of emergencies and the traffic volume predicted by the cloud model. The numerical characteristics of traffic information are abstracted from the spatial-temporal trajectory data by the reverse cloud model, and the inference procedure of the one-dimension cloud model further predicts the uncertain traffic volume using the numerical characteristics. In addition, the crossover and mutation operators of multiobjective evolutionary algorithms are modified to solve the model. The experimental results show that the inference procedure of one-dimension cloud model can accurately predict the traffic volume at the departure time; and the proposed model is more reasonable than the existing scheduling models; at the same time, the improved NSGA-II can also provide superior schemes in different departure times and traffic conditions for decision makers.

scholarly journals Energy and Environmental Implications of Using Energy-Harvesting Speed Humps in Nablus City, Palestine

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 937
Author(s):  
Fady M. A. Hassouna ◽  
Mahmoud Assad ◽  
Islam Koa ◽  
Wesam Rabaya ◽  
Aya Aqhash ◽  
...  
Keyword(s):  
Energy Harvesting ◽  
Ghg Emissions ◽  
Traffic Volume ◽  
Environmental Implications ◽  
Traffic Conditions ◽  
National University ◽  
Energy Consuming ◽  
The Cost ◽  
Annual Amount ◽  
Speed Humps

Over the last three decades, transportation has become one of the main energy-consuming sectors around the world and, as a result, large amounts of emissions are produced, contributing to global warming, climate change, and health problems. Therefore, huge investments and efforts have been made by governments and international institutions to find new renewable and clean sources of energy. As a contribution to these efforts, this study determined the practical energy and environmental implications of replacing conventional speed humps with energy-harvesting speed humps in Nablus city, Palestine. The study was implemented using an energy-harvesting speed hump (EHSH) system developed in the laboratories at An-Najah National University and based on comprehensive traffic volume counts at all speed humps’ locations. In addition, a traffic volume prediction model was developed in order to determine the implications over the next 10 years. As a result of the study, the expected annual amount of generated energy was determined. Moreover, the expected reduction in greenhouse gas (GHG) emissions and the reduction in the cost of roadway network lighting were determined based on the current and future traffic conditions.

scholarly journals Let Trajectories Speak Out the Traffic Bottlenecks

2022 ◽  
Vol 13 (1) ◽  
pp. 1-21
Author(s):  
Hui Luo ◽  
Zhifeng Bao ◽  
Gao Cong ◽  
J. Shane Culpepper ◽  
Nguyen Lu Dang Khoa
Keyword(s):  
Traffic Volume ◽  
Trajectory Data ◽  
Trade Offs ◽  
Bottleneck Identification ◽  
Spread Model ◽  
Efficiency And Effectiveness ◽  
Historical Trajectory ◽  
Algorithmic Approaches ◽  
Compare And Contrast ◽  
Road Segments

Traffic bottlenecks are a set of road segments that have an unacceptable level of traffic caused by a poor balance between road capacity and traffic volume. A huge volume of trajectory data which captures realtime traffic conditions in road networks provides promising new opportunities to identify the traffic bottlenecks. In this paper, we define this problem as trajectory-driven traffic bottleneck identification : Given a road network R , a trajectory database T , find a representative set of seed edges of size K of traffic bottlenecks that influence the highest number of road segments not in the seed set. We show that this problem is NP-hard and propose a framework to find the traffic bottlenecks as follows. First, a traffic spread model is defined which represents changes in traffic volume for each road segment over time. Then, the traffic diffusion probability between two connected segments and the residual ratio of traffic volume for each segment can be computed using historical trajectory data. We then propose two different algorithmic approaches to solve the problem. The first one is a best-first algorithm BF , with an approximation ratio of 1-1/ e . To further accelerate the identification process in larger datasets, we also propose a sampling-based greedy algorithm SG . Finally, comprehensive experiments using three different datasets compare and contrast various solutions, and provide insights into important efficiency and effectiveness trade-offs among the respective methods.

scholarly journals Optimal Staffing for Vessel Traffic Service Operators: A Case Study of Yeosu VTS

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8004
Author(s):  
Sang-Lok Yoo ◽  
Kwang-Il Kim
Keyword(s):  
Statistical Data ◽  
Optimal Number ◽  
Traffic Volume ◽  
Near Miss ◽  
Trajectory Data ◽  
Staffing Level ◽  
Microscopic Approach ◽  
Marine Accidents ◽  
Traffic Organization

Vessel traffic volume and vessel traffic service (VTS) operator workloads are increasing with the expansion of global maritime trade, contributing to marine accidents by causing difficulties in providing timely services. Therefore, it is essential to have sufficient VTS operators considering the vessel traffic volume and near-miss cases. However, no quantitative method for determining the optimal number of workstations, which is necessary for calculating the VTS operator staffing level, has yet been proposed. This paper proposes a new, microscopic approach for calculating the number of workstations from vessel trajectories and voice recording communication data between VTS operators and navigators. The vessel trajectory data are preprocessed to interpolate different intervals. The proposed method consists of three modules: Information services, navigational assistance services, and traffic organization service. The developed model was applied to the Yeosu VTS in Korea. Another workstation should be added to the current workstation based on the proposed method. The results showed that even without annual statistical data, a reasonable VTS operator staffing level could be calculated. The proposed approach helps prevent vessel accidents by providing timely services even if the vessel traffic is congested if VTS operators are deployed to a sufficient number of workstations.

scholarly journals The Development of a Concept Model of All-Weather Safe Winter Tires

2019 ◽  
pp. 3-11
Author(s):  
I.V. Balabin ◽  
O.I. Balabin ◽  
I.S. Chabunin
Keyword(s):  
Conceptual Model ◽  
Russian Federation ◽  
Road Safety ◽  
Road Network ◽  
Winter Temperature ◽  
The Road ◽  
Concept Model ◽  
Traffic Conditions ◽  
Proposed Model ◽  
The Russian Federation

The article presents issues related to improving safety and efficiency of operation of mobile machines in the constantly changing, winter temperature and traffic conditions. The authors develop a conceptual model of winter all-weather tires able to adapt to various road conditions such as when the road is covered with a layer of ice or compacted snow, or when the road is free from snow and ice. The use of such winter all weather tires will improve the road safety by contributing to increasing the life of tires and preserving the road network. The proposed model has no foreign analogues and is protected by a patent of the Russian Federation.

scholarly journals QUANTUM FOG CLOUD MODEL IN INTERNET OF THINGS WITH ANALYSIS OF GREEN COMPUTING

2017 ◽  
Vol 5 (1) ◽  
pp. 230-238
Author(s):  
Sayantan Gupta
Keyword(s):  
Internet Of Things ◽  
Cloud Model ◽  
Modern Society ◽  
Green Computing ◽  
Modern World ◽  
Security Issues ◽  
Proposed Model ◽  
Implementation Techniques ◽  
The Many ◽  
The Internet Of Things

The technology of Quantum Green Computing has been discussed in this paper. It also discusses the need of the many implementation techniques and approaches in relation with Fog-Cloud Computing. Moreover, we would like to introduce the latest algorithms like Stack Algorithm, Address Algorithm and many others which will help in the analysis of Green-Quantum Computing Technology in the modern society and would create a technological revolution. With the Internet of Things rising in the modern world time, new security issues have also been developed. So, our proposed Model the Fog-Things Model will help us to determine the security issues and indeed secure the entire IoT network.

scholarly journals ANALYSIS OF DRIVER BEHAVIOR IN VEHICLE FOLLOWING AND LANE CHANGING PARAMETERS ON URBAN MID BLOCK SECTIONS

2021 ◽  
Vol 9 (2) ◽  
pp. 1169-1177
Author(s):  
Sowjanya, Et. al.
Keyword(s):  
Road Traffic ◽  
Driver Behavior ◽  
Video Data ◽  
Heterogeneous Traffic ◽  
Heterogeneous Environments ◽  
Trajectory Data ◽  
Lateral Direction ◽  
Lane Changing ◽  
Traffic Conditions ◽  
Road Section

In mixed traffic situations, there is weak or no lane behavior of the driver much more complicated where vehicle and driver behavior show a huge difference between them. Road traffic driving behavior on urban midblock sections is one of the most complex phenomena to be examined particularly in heterogeneous traffic conditions. This is often attributed to the capacity of the road section and the traffic flow features at the macroscopic and microscopic level of a road section. Very few researchers have attempted to investigate these features in heterogeneous environments because of the lack of adequate information gathering methods and the amount of complexity involved. In this background, an access controlled mid block road section was selected for video data collection. The main objectives of this study include developing vehicular trajectory data and analyzing the lane changing and vehicle following behavior of driver on the mid block section considering the relative velocities and relative spacing between various types of vehicles under heterogeneous traffic conditions.  The videos were collected from urban roadway in the Kurnool district of Andhra Pradesh. The length of the stretch is 120m and the width is 7.0 m. The data was extracted to know the variations in terms of longitudinal and lateral speeds, velocities, vehicle following and lane changing behavior of the drivers. The data extracted was smoothened by moving average method to minimize the human errors. Lateral amplitude of the vehicles of various types was analyzed. The study revealed that vehicles in the mixed stream, in general and in particular, Bikes and Autos particularly move substantially in the lateral direction.

scholarly journals Timetable Design for Urban Rail Line with Capacity Constraints

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Yu-Ting Zhu ◽  
Bao-Hua Mao ◽  
Lu Liu ◽  
Ming-Gao Li
Keyword(s):  
Solution Method ◽  
Operating Cost ◽  
Capacity Constraints ◽  
Scheduling Model ◽  
Urban Rail ◽  
Proposed Model ◽  
Rail Line ◽  
First Come First Serve ◽  
Waiting Cost ◽  
Simulation Results

To design an efficient and economical timetable for a heavily congested urban rail corridor, a scheduling model is proposed in this paper. The objective of the proposed model is to find the departure time of trains at the start terminal to minimize the system cost, which includes passenger waiting cost and operating cost. To evaluate the performance of the timetable, a simulation model is developed to simulate the detailed movements of passengers and trains with strict constraints of station and train capacities. It assumes that passengers who arrive early will have more chances to access a station and board a train. The accessing and boarding processes of passengers are all based on a first-come-first-serve basis. When a station is full, passengers unable to access must wait outside until the number of waiting passengers at platform falls below a given value. When a train is full, passengers unable to board must wait at the platform for the next train to arrive. Then, based on the simulation results, a two-stage genetic algorithm is introduced to find the best timetable. Finally, a numerical example is given to demonstrate the effectiveness of the proposed model and solution method.

scholarly journals Group Scheduling Problems with Time-Dependent and Position-Dependent DeJong’s Learning Effect

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Li Sun ◽  
Lei Ning ◽  
Jia-zhen Huo
Keyword(s):  
Polynomial Time ◽  
Completion Time ◽  
Learning Effect ◽  
Time Dependent ◽  
Total Weighted Completion Time ◽  
Group Scheduling ◽  
Scheduling Problems ◽  
Scheduling Model ◽  
Proposed Model ◽  
Weighted Completion Time

In this paper, we introduce a group scheduling model with time-dependent and position-dependent DeJong’s learning effect. The objectives of scheduling problems are to minimize makespan, the total completion time, and the total weighted completion time, respectively. We show that the problems remain solvable in polynomial time under the proposed model.

Citywide Traffic Volume Estimation Using Trajectory Data

2017 ◽  
Vol 29 (2) ◽  
pp. 272-285 ◽  
Author(s):  
Xianyuan Zhan ◽  
Yu Zheng ◽  
Xiuwen Yi ◽  
Satish V. Ukkusuri
Keyword(s):  
Traffic Volume ◽  
Volume Estimation ◽  
Trajectory Data ◽  
Traffic Volume Estimation

Empirical Analysis on Time to Collision at Urban Expressway

2014 ◽  
Vol 505-506 ◽  
pp. 1127-1132 ◽  
Author(s):  
Cheng Xu ◽  
Zhao Wei Qu
Keyword(s):  
Empirical Analysis ◽  
Traffic Safety ◽  
Traffic Volume ◽  
T Test ◽  
Descriptive Statistics ◽  
Traffic Condition ◽  
Time To Collision ◽  
Traffic Conditions ◽  
Urban Expressway ◽  
Traffic Conflicts

Traffic safety is of great significance, especially at urban expressway where traffic volume is large and traffic conflicts are highlighted. But little research up to date has discussed in detail how these factors impact the TTC characteristics. In this paper, field Beijing expressway data were collected by video with different locations, lanes, traffic conditions and following vehicle types. Accordingly, some basic descriptive statistics of total TTC samples were shown and analyzed. We then used T-test to analyze the effect of road environments, traffic conditions, and vehicle types on TTC statistically. The results implied three main findings. Firstly, TTC was found to change according to road environments (i.e. TTC on weaving segment is smaller than other locations), secondly, some evidence supported this hypothesis that traffic conditions (especially uncongested traffic condition) affect TTC significantly, and lastly, little correlation was found between TTC means and vehicle types.

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