scholarly journals Community detection in large scale congested urban road networks

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0260201
Author(s):  
Seyed Arman Haghbayan ◽  
Nikolas Geroliminis ◽  
Meisam Akbarzadeh
Keyword(s):  
San Francisco ◽  
Community Detection ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Large Scale ◽  
Cost Effective ◽  
Computational Time ◽  
Management Tools ◽  
Traffic Condition ◽  
Urban Networks

Traffic congestion in large urban networks may take different shapes and propagates non-uniformly variations from day to day. Given the fact that congestion on a road segment is spatially correlated to adjacent roads and propagates spatiotemporally with finite speed, it is essential to describe the main pockets of congestion in a city with a small number of clusters. For example, the perimeter control with macroscopic fundamental diagrams is one of the effective traffic management tools. Perimeter control adjusts the inflow to pre-specified regions of a city through signal timing on the border of a region in order to optimize the traffic condition within the region. The precision of macroscopic fundamental diagrams depends on the homogeneity of traffic condition on road segments of the region. Hence, previous studies have defined the boundaries of the region under perimeter control subjected to the regional homogeneity. In this study, a cost-effective method is proposed for the mentioned problem that simultaneously considers homogeneity, contiguity and compactness of clusters and has a shorter computational time. Since it is necessary to control the cost and complexity of perimeter control in terms of the number of traffic signals, sparse parts of the network could be potential candidates for boundaries. Therefore, a community detection method (Infomap) is initially adopted and then those clusters are improved by refining the communities in relation to roads with the highest heterogeneity. The proposed method is applied to Shenzhen, China and San Francisco, USA and the outcomes are compared to previous studies. The results of comparison reveal that the proposed method is as effective as the best previous methods in detecting homogenous communities, but it outperforms them in contiguity. It is worth noting that this is the first method that guarantees the connectedness of clusters, which is a prerequisite of perimeter control.

Efficient Schedule of Energy-Constrained UAV Using Crowdsourced Buses in Last-Mile Parcel Delivery

2021 ◽  
Vol 5 (1) ◽  
pp. 1-23
Author(s):  
Yan Pan ◽  
Shining Li ◽  
Qianwu Chen ◽  
Nan Zhang ◽  
Tao Cheng ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Large Scale ◽  
Load Capacity ◽  
Scheduling Algorithm ◽  
Cost Effective ◽  
Promising Alternative ◽  
Logistics Industry ◽  
Last Mile ◽  
Delivery Scheduling ◽  
Schedule Approach

Stimulated by the dramatical service demand in the logistics industry, logistics trucks employed in last-mile parcel delivery bring critical public concerns, such as heavy cost burden, traffic congestion and air pollution. Unmanned Aerial Vehicles (UAVs) are a promising alternative tool in last-mile delivery, which is however limited by insufficient flight range and load capacity. This paper presents an innovative energy-limited logistics UAV schedule approach using crowdsourced buses. Specifically, when one UAV delivers a parcel, it first lands on a crowdsourced social bus to parcel destination, gets recharged by the wireless recharger deployed on the bus, and then flies from the bus to the parcel destination. This novel approach not only increases the delivery range and load capacity of battery-limited UAVs, but is also much more cost-effective and environment-friendly than traditional methods. New challenges therefore emerge as the buses with spatiotemporal mobility become the bottleneck during delivery. By landing on buses, an Energy-Neutral Flight Principle and a delivery scheduling algorithm are proposed for the UAVs. Using the Energy-Neutral Flight Principle, each UAV can plan a flying path without depleting energy given buses with uncertain velocities. Besides, the delivery scheduling algorithm optimizes the delivery time and number of delivered parcels given warehouse location, logistics UAVs, parcel locations and buses. Comprehensive evaluations using a large-scale bus dataset demonstrate the superiority of the innovative logistics UAV schedule approach.

scholarly journals A framework for IoT-enabled environment aware traffic management

2021 ◽  
Vol 11 (1) ◽  
pp. 518
Author(s):  
Mohamed Fazil Mohamed Firdhous ◽  
B. H. Sudantha ◽  
Naseer Ali Hussien
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Traffic Management ◽  
Fine Particles ◽  
Environment Pollution ◽  
Negative Effects ◽  
Traffic Condition ◽  
Pollution Levels ◽  
Transport Services ◽  
The Cost

Vehicular traffic has increased across all over the world especially in urban areas due to many reasons including the reduction in the cost of vehicles, degradation of the quality of public transport services and increased wealth of people. The traffic congestion created by these vehicles causes many problems. Increased environment pollution is one of the most serious negative effects of traffic congestion. Noxious gases and fine particles emitted by vehicles affect people in different ways depending on their age and present health conditions. Professionals and policy makers have devised schemes for better managing traffic in congested areas. These schemes suffer from many shortcomings including the inability to adapt to dynamic changes of traffic patterns. With the development of technology, new applications like Google maps help drivers to select less congested routes. But, the identification of the best route takes only the present traffic condition on different road segments presently. In this paper the authors propose a system that helps drivers select routes based on the present and expected environment pollution levels at critical points in a given area.

Characteristic Parameters Identification of Macro Traffic Flow on Urban Expressway

2013 ◽  
Vol 409-410 ◽  
pp. 1209-1212
Author(s):  
Da Shan Chen
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Network ◽  
Large Scale ◽  
Characteristic Parameters ◽  
Traffic Demand ◽  
Urban Expressway ◽  
Back Ground ◽  
Control And Management

The macroscopic traffic flow parameters characteristic is an important research content in traffic flow theory. Urban expressway plays an important role in the urban road network. It is gradually shifting from large-scale infrastructure-oriented to refinement of traffic management. With the growing of traffic demand and much more traffic congestion and accidents, integrated active traffic management should be involved in urban expressway management on the back ground of car-road coordination. As the backbone road network, traffic flow characteristic parameters have great value for the control and management of urban expressway. Then the characteristic variables of the expressway traffic flow were identified which support meticulous management for urban expressway.

scholarly journals Toll and Traffic Management System for Express Highways

2020 ◽  
Vol 9 (5) ◽  
pp. 2109-2113
Keyword(s):  
Time Management ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Management System ◽  
Heavy Traffic ◽  
Cost Effective ◽  
Alert Message ◽  
Toll Collection ◽  
The Government ◽  
Toll Booth

Now a days, toll plazas at the highways are operated manually, where a vehicle comes near the toll booth and toll collector collects the cash and enter the vehicle data and provides a receipt. Manually operated Toll Plaza Systems leads to longer waiting time of vehicles and heavy traffic at the highways. To overcome this issue of traffic congestion and time management and to bring automation in the toll management system, we have introduced an innovative, optimized and revolutionary system. This paper is putting forward an efficient and cost-effective technique of automatic toll collection. The system is based on the mobile GPS network and will use various APIs for development. The cost to be paid at the toll gate is auto decided as per the government limits and the toll booth charges. System will use online payment gateways to collect those revenues. If the balance is low in the user’s account then it can be recharged at the booth itself. At the user’s end, If the toll tax payment is delayed by certain timeline then user will be informed by an alert message and if delay still exists then strict actions will be imposed along with proper penalty charges for the same. This system is the novelty to the existing toll system. It will have a wide impact on people's life as its scope will lead to safe and enhanced productivity through the use of advanced technologies. This will also minimize fraud and will provide user convenience. It will also enhance the operational efficiency of toll collector.

scholarly journals An A pproach to Smart Parking A lgorithm using a nt Colony Optimization and Decision Tree Algorithm

2021 ◽  
Vol 10 (12) ◽  
pp. 58-63
Author(s):  
Ankita Yadav ◽  
◽  
Mohammad Arif ◽  
Keyword(s):  
Decision Tree ◽  
Traffic Congestion ◽  
Large Scale ◽  
Cost Effective ◽  
Road Accidents ◽  
The Past ◽  
Parking Management ◽  
Smart Parking ◽  
Pros And Cons ◽  
Result Analysis

This research is conducted in order to deal with the main problem of traffic congestion and road accidents that is basically caused because of the improper parking management. . Hence, it is important that cities have a well-managed parking system. In the past various researches has been done to design a suitable smart paring algorithm. However, each research had their own pros and cons. Our research leads to a smart algorithm that is secure and is convenient enough to develop a system that can be manage the available slots and can notify the users about the available parking slot beforehand to the client. The result analysis clearly shows that the algorithm proposed and designed is more accurate than other algorithms used in the past. The proposed algorithm is designed using ACO, decision tree, and GPS mapping. The idea of working on this research was to provide a solution that is cost effective, helps people on large scale and maintains the laws and order.

scholarly journals Community Detection for Air Traffic Networks and Its Application in Strategic Flight Planning

2021 ◽  
Vol 13 (16) ◽  
pp. 8924
Author(s):  
Silvia Zaoli ◽  
Giovanni Scaini ◽  
Lorenzo Castelli
Keyword(s):  
Community Detection ◽  
Traffic Management ◽  
Air Traffic ◽  
Computational Time ◽  
Acceptable Solution ◽  
Flight Planning ◽  
Detection Algorithms ◽  
Traffic Management System ◽  
Definition Of ◽  
The Cost

An environmentally and economically sustainable air traffic management system must rely on fast models to assess and compare various alternatives and decisions at the different flight planning levels. Due to the numerous interactions between flights, mathematical models to manage the traffic can be computationally time-consuming when considering a large number of flights to be optimised at the same time. Focusing on demand–capacity imbalances, this paper proposes an approach that permits to quickly obtain an approximate but acceptable solution of this problem. The approach consists in partitioning flights into subgroups that influence each other only weakly, solving the problem independently in each subgroup, and then aggregating the solutions. The core of the approach is a method to build a network representing the interactions among flights, and several options for the definition of an interaction are tested. The network is then partitioned with existing community detection algorithms. The results show that applying a strategic flight planning optimisation algorithm on each subgroup independently reduces significantly the computational time with respect to its application on the entire European air traffic network, at the cost of few and small violations of sector capacity constraints, much smaller than those actually observed on the day of operations.

scholarly journals Identify Optimal Traffic Condition and Speed Limit for Hard Shoulder Running Strategy

2021 ◽  
Vol 13 (4) ◽  
pp. 1822
Author(s):  
Fan Yang ◽  
Fan Wang ◽  
Fan Ding ◽  
Huachun Tan ◽  
Bin Ran
Keyword(s):  
Cellular Automata ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Clustering Algorithm ◽  
Mean Shift ◽  
Management Strategies ◽  
Speed Limit ◽  
Clustering Methods ◽  
Traffic Condition ◽  
Cellular Automata Model

Highway system is experiencing increasing traffic congestion with fast-growing number of vehicles in metropolitan areas. Implementing traffic management strategies such as utilizing the hard shoulder as an extra lane could increase highway capacity without extra construction work. This paper presents a method of determining an optimal traffic condition and speed limit of opening hard shoulder. Firstly, the traffic states are clustered using K-Means, mean shift, agglomerative and spectral clustering methods, and the optimal clustering algorithm is selected using indexes including the silhouette score, Davies-Bouldin Index and Caliski-Harabaz Score. The results suggested that the clustering effect of using K-Means method with three categories is optimal. Then, cellular automata model is used to simulate traffic conditions before and after the hard shoulder running strategy is applied. The parameters of the model, including the probabilities of random deceleration, slow start and lane change, are calibrated using real traffic data. Four indicators including the traffic volume, the average speed, the variance of speed, and the travel time of emergency rescue vehicles during traffic accident obtained using the cellular automata model are used to evaluate various hard shoulder running strategies. By using factor analysis and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods, the optimal traffic condition and speed limit of opening hard shoulder could be determined. This method could be applied to highway segments of various number of lanes and different speed limits to optimize the hard shoulder running strategy for highway management.

scholarly journals Authors: Yunhui Zeng ; Wenjuan Hu ; Hongfei Guo ; Shiyue Shen ; Li Huang ; Yiying Lou

2019 ◽  
pp. 57-66
Author(s):  
Yunhui Zeng ◽  
Wenjuan Hu ◽  
Hongfei Guo ◽  
Shiyue Shen ◽  
Li Huang ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Spline Interpolation ◽  
Road Construction ◽  
Traffic Condition ◽  
The Road ◽  
Traffic Capacity ◽  
Significant Difference ◽  
The Difference

Focused on the lane occupancy phenomenon, this paper analyzes the roads during two different accidents to the evacuation period. Firstly, according to the statistical data, this paper calculated the correction coefficients under the road traffic condition, and then obtained the actual traffic capacity result at each moment of the road when combining the function model of the actual traffic capacity corrected by the running speed and the road traffic condition. Next the actual traffic capacity results are fitted to the Smooth spline interpolation, and then the actual traffic capacity is further verified by the traffic congestion situation. The actual traffic capacity of the road during the accident to evacuation is summarized as follows: the actual traffic capacity shows a nonlinear trend, that is, ascending-attenuating-recovering and gradually stabilizing. Finally, using Mann-Whitney U test to carry out the difference test on the actual traffic capacity, it is found that there is significant difference between the two groups of data, and the actual traffic capacity of the second case is stronger than that of the first one, and the reasons for the difference are analyzed as follows: the ratio of the steering traffic volume at the downstream intersection is different; this road section includes the community intersection and there are vehicles entering and leaving; meanwhile the speed of each lane is different and there are buildings near the lane. The above conclusions will provide theoretical basis for the traffic management department to correctly guide the vehicle driving, approve the road construction, design the road channelization plan, set the roadside parking space and the non-port-type bus stations.

Large-scale spatial network models: An application to modeling information diffusion through the homeless population of San Francisco

2018 ◽  
Vol 47 (3) ◽  
pp. 523-540 ◽  
Author(s):  
Zack W Almquist
Keyword(s):  
San Francisco ◽  
Information Diffusion ◽  
Large Scale ◽  
Homeless Youth ◽  
Network Models ◽  
Cost Effective ◽  
Homeless Population ◽  
Small Scale ◽  
Government Organizations ◽  
Available Information

To address the effects of increasing homeless populations, planners must understand the size and distribution of their homeless populations, as well as how information and resources are diffused throughout homeless communities. Currently, there is limited publicly available information on the homeless population, e.g. the estimates of the homeless, gathered annually by the US Housing & Urban Development point in time survey. While it is theorized in the literature that the networks of homeless individuals provide access to important information for planners in areas such as health (e.g. needle exchanges) or access (e.g. information diffusion about the location of new shelters), it is almost never measured, and if measured, only at a very small scale. This research addresses the question of how planners can leverage publicly available data on the homeless to better understand their own homeless networks (e.g. relations among the homeless themselves) in a cost-effective and reliable way. To this end, we provide a method for simulating realistic networks of a social relation among the homeless population and perform a diffusion analysis over the resultant homeless-to-homeless networks, and also over a simulated homeless youth Facebook network. We validate the former through novel use of historical data, while the latter is based on recent work that demonstrated that the homeless youth have similar size Facebook networks and usage. We see much stronger spatial hopping and quicker diffusion over the youth network, i.e. we expect information to pass among the youth network much faster than the homeless-to-homeless network. This finding implies that non-government organizations and public health efforts that seek to provide information, goods or services to the homeless should start with the homeless youth, given the potential for faster diffusion when homeless youth are the initial transmitters. Overall, these methods and analysis provide a unique opportunity for visualizing, characterizing and inferring information for large-scale and hard to measure social networks.

scholarly journals Collaborative and Infrastructure-less Vehicular Traffic Rerouting for Intelligent Transportation Systems

2020 ◽  
Author(s):  
Ademar Takeo Akabane ◽  
Edmundo Roberto Mauro Madeira ◽  
Leandro Aparecido Villas
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Management System ◽  
Cost Effective ◽  
Intelligent Transportation ◽  
Good Alternative ◽  
Transportation Systems ◽  
Vehicular Traffic ◽  
Traffic Management System

This extended abstract provides an at-a-glance view of the main contributions of my Ph.D. work. The work aims to investigate and develop cutting-edge an infrastructure-less vehicular traffic management system in order to minimize vehicular traffic congestion and advance the state-of-the-art in intelligent transportation systems. The proposed solutions were widely compared with other literature solutions on different performance evaluation metrics. The evaluation results show that the proposed vehicle traffic management system is efficient, scalable, and cost-effective, which may be a good alternative to mitigate urban mobility problems.

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