scholarly journals Environmental and Social Problems and Countermeasures in Transportation System under Resource Constraints

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Qianyuan Li ◽  
Shaoying Tian
Keyword(s):  
Optimization Problem ◽  
Social Problems ◽  
Resource Constraints ◽  
Rapid Development ◽  
Transportation System ◽  
Urban Traffic ◽  
Route Optimization ◽  
Planning Problem ◽  
Selection Scheme ◽  
The Impact

With the rapid development of urban economy and the acceleration of urbanization, the demand for urban traffic is increasing rapidly. The single traffic-oriented planning does not take into account the requirements of traffic development on resources and the impact on the environment. The traffic construction of most cities can not fully meet the standard of ecotype. In this paper, the vehicle distribution route optimization problem under multiresource constraints such as vehicle energy capacity and vehicle loading capacity is studied, and the static and dynamic models of distribution route optimization under multiresource constraints are established. In the static distribution route optimization model, the distribution route optimization problem with subloops is solved by modifying the network structure and adding virtual resource points. In the dynamic model, the spatiotemporal network model is used to avoid the generation of subloops, and the description of the vehicle distribution route planning problem is more intuitive and accurate. The model enriches the vehicle distribution route selection scheme at the cost of expanding the model scale. And it can solve the time when the vehicle arrives and leaves the customer point. This paper provides a good countermeasure for solving the environmental and social problems in the transportation system under the condition of resource constraints.

Application research of urban subway traffic mode based on behavior entropy in the background of big data

2021 ◽  
pp. 1-14
Author(s):  
Wanxin Hu ◽  
Fen Cheng
Keyword(s):  
Big Data ◽  
Large Scale ◽  
Transportation Networks ◽  
Transportation Network ◽  
Rapid Development ◽  
Urban Transportation ◽  
Transportation System ◽  
Urban Traffic ◽  
Time Optimization ◽  
The City

With the development of society and the Internet and the advent of the cloud era, people began to pay attention to big data. The background of big data brings opportunities and challenges to the research of urban intelligent transportation networks. Urban transportation system is one of the important foundations for maintaining urban operation. The rapid development of the city has brought tremendous pressure on the traffic, and the congestion of urban traffic has restricted the healthy development of the city. Therefore, how to improve the urban transportation network model and improve transportation and transportation has become an urgent problem to be solved in urban development. Specific patterns hidden in large-scale crowd movements can be studied through transportation networks such as subway networks to explore urban subway transportation modes to support corresponding decisions in urban planning, transportation planning, public health, social networks, and so on. Research on urban subway traffic patterns is crucial. At the same time, a correct understanding of the behavior patterns and laws of residents’ travel is a key factor in solving urban traffic problems. Therefore, this paper takes the metro operation big data as the background, takes the passenger travel behavior in the urban subway transportation system as the research object, uses the behavior entropy to measure the human behavior, and actively explores the urban subway traffic mode based on the metro passenger behavior entropy in the context of big data. At the same time, the congestion degree of the subway station is analyzed, and the redundancy time optimization model of the subway train stop is established to improve the efficiency of the subway operation, so as to provide important and objective data and theoretical support for the traveler, planner and decision maker. Compared to the operation graph without redundant time, the total travel time optimization effect of passengers is 7.74%, and the waiting time optimization effect of passengers is 6.583%.

scholarly journals Introducing a Navigation Algorithm for Reducing the Spread of Diseases in Public Transport Networks

2021 ◽  
Author(s):  
Jens Klinker ◽  
Mohamed Hechem Selmi ◽  
Mariana Avezum ◽  
Stephan Jonas
Keyword(s):  
Travel Time ◽  
Public Transport ◽  
Public Transportation ◽  
Urban Traffic ◽  
Planning Problem ◽  
Navigation Algorithm ◽  
Urban Public Transport ◽  
Flow Through ◽  
The Impact ◽  
The City

Reducing passenger flow through highly frequented bottlenecks in public transportation networks is a well-known urban planning problem. This issue has become even more relevant since the outbreak of the SARS-CoV-2 pandemic and the necessity for minimum distances between passengers. We propose an approach that allows to dynamically navigate passengers around dangerously crowded stations to better distribute the passenger load across an entire urban public transport network. This is achieved through the introduction of new constraints into routing requests, that enable the avoidance of specific nodes in a network. These requests consider walks, bikes, metros, subways, trams and buses as possible modes of transportation. An implementation of the approach is provided in cooperation with the Munich Travel Corporation (MVG) for the city of Munich, to simulate the effects on a real city’s urban traffic flow. Among other factors, the impact on the travel time was simulated given that the two major exchange points in the network were to be avoided. With an increase from 26.5 to 26.8 minutes on the average travel time, the simulation suggests that the time penalty might be worth the safety benefits.

scholarly journals Fuzzy Comprehensive Evaluation Model for Road Capacity of Open Neighborhood -- Based on Improved NS Cellular Automata

2018 ◽  
Vol 12 (7) ◽  
pp. 144
Author(s):  
XiaoYan Cao ◽  
Bing-Qian Liu ◽  
Jian Cao ◽  
Yuan-Biao Zhang
Keyword(s):  
Cellular Automata ◽  
Evaluation System ◽  
Comprehensive Evaluation ◽  
Rapid Development ◽  
Fuzzy Comprehensive Evaluation ◽  
Gated Communities ◽  
Urban Traffic ◽  
Urban District ◽  
Road Capacity ◽  
The Impact

With the rapid development of motorization in our country, gated communities have become the obstacle of the development of urban traffic network. In this paper, focusing on the impact of gated communities on the traffic situation in surrounding area before and after it is opened, we firstly establish a comprehensive evaluation system by fuzzy comprehensive evaluation method and then build up the improved NS model based on Cellular Automata, which put forward the concept of internal road sharing rate in communities. Finally, we select the urban district of different types and surrounding roads in Shanghai as a case, and through simulation and evaluation, we found that the opening of communities is feasible. What’s more, compared with gated communities, the two-way 2-lane urban opening communities have the most optimal effect on improving road capacity.

Intelligent Optimization of Urban Real-Time Traffic Route Based on DNA Non-Dominated Sorting Genetic Algorithm

2015 ◽  
Vol 713-715 ◽  
pp. 1746-1749
Author(s):  
Min Zhu ◽  
Bo Su ◽  
Gang Min Ning
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Complexity Analysis ◽  
Fitness Function ◽  
Optimal Solution ◽  
Urban Traffic ◽  
Route Optimization ◽  
Optimization Strategy ◽  
Traffic Condition ◽  
Real Time Traffic

The urban traffic condition is changed timely, so the traditional serial algorithm cannot satisfy the requirement of traffic scale and condition changes. Therefore, this paper proposes a DNA non-dominated sorting genetic algorithm for route optimization problem of multi-objects. First, through Pareto frontiers solution set optimization and algorithm complexity analysis, we determine the multi-objects problem to be optimized. Then we convert the problem into optimization problem of single-object fitness function, namely the elite populations optimization strategy, through which we can obtain the optimal solution of timely traffic condition.

scholarly journals Calculating the Contribution Rate of Intelligent Transportation System in Improving Urban Traffic Smooth Based on Advanced DID Model

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Ming-wei Li ◽  
Jun Yun ◽  
Na Liu
Keyword(s):  
Traffic Congestion ◽  
Intelligent Transportation System ◽  
Rapid Development ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Urban Traffic ◽  
Evaluation Index System ◽  
Capital City ◽  
Contribution Rate ◽  
Urban City

Recent years have witnessed the rapid development of intelligent transportation system around the world, which helps to relieve urban traffic congestion problems. For instance, many mega-cities in China have devoted a large amount of money and resources to the development of intelligent transportation system. This poses an intriguing and important issue: how to measure and quantify the contribution of intelligent transportation system to the urban city, which is still a puzzle. This paper proposes a matching difference-in-difference model to calculate the contribution rate of intelligent transportation system on traffic smoothness. Within the model, the main effect indicators of traffic smoothness are first identified, and then the evaluation index system is built, and finally the ideas of the matching pool are introduced. The proposed model is illustrated in Guangzhou, China (capital city of Guangdong province). The results show that introduction of ITS contributes 9.25% to the improvement of traffic smooth in Guangzhou. Also, the research explains the working mechanism of how ITS improves urban traffic smooth. Eventually, some strategy recommendations are put forward to improve urban traffic smooth.

scholarly journals Can Negative Travel Habits Hinder Positive Travel Behavioural Change under Beijing Vehicle Restrictions?

2020 ◽  
Vol 32 (5) ◽  
pp. 691-709
Author(s):  
Xiao Dong ◽  
Ruoya Wang ◽  
Yaodong Zhou
Keyword(s):  
Traffic Management ◽  
Structural Equation ◽  
Rapid Development ◽  
Behavioural Change ◽  
Travel Behaviour ◽  
Urban Traffic ◽  
Mediating Effect ◽  
Personal Lives ◽  
Large Cities ◽  
The Impact

Given the rapid development of large cities, the residents faced with pressure both at work and in their personal lives tend to solidify their choice of transport modes and form personal travel habits, which in turn leads to higher requirements for urban traffic management. Based on the modified Theory of Planned Behaviour, the structural equation method is employed to explore people’s travel behaviour. It is found that policy attitude, perceived behaviour control, and subjective norms comprehensively affect the residents’ travel intentions under the Vehicle Restrictions in place in Beijing. The residents without private cars display a stronger intention to change their travel choices under the policies. When considering the mediating effect of travel habits between travel intention and travel choice, the impact of the restrictive policies is weakened. Compared with lower-income people, those with higher incomes demonstrate more stable travel habits in response to the effects of the restrictions. The higher the income, the greater the dependence on private cars exhibited by the residents. To summarize, people’s travel habits weaken to some extent the effects of the restrictive policies. Such policies should be created with the explicit aim of gradually changing the people’s habits.

scholarly journals Using GPS Trajectories to Adaptively Plan Bus Lanes

2021 ◽  
Vol 11 (3) ◽  
pp. 1035
Author(s):  
Yanjie Sun ◽  
Mingguang Wu ◽  
Huien Li
Keyword(s):  
Optimization Problem ◽  
Construction Cost ◽  
Urban Traffic ◽  
Planning Problem ◽  
Multiobjective Optimization Problem ◽  
The Road ◽  
Shenzhen City ◽  
Road Condition ◽  
Gps Trajectories ◽  
Bus Lane

Since bus prioritization policies can help mitigate urban traffic jams, the planning of bus lanes has drawn considerable attention. Existing methods suffer from a common limitation, which is that the limited spatial adaptability resulting from certain road condition information cannot be directly specified. Many bus GPS trajectories have been accumulated and can be contiguously gathered if needed. This paper proposes a trajectory-based bus lane planning method. First, we formulize the bus lane planning problem as a multiobjective optimization problem in which the road conditions, traffic flow, connectivity of bus lanes, and construction cost are organized as four constraints, and road utilization and bus punctuality are modeled as two objectives. Then, an evolutionary algorithm-based method is presented to solve the problem. We tested the model in the Nanshan District, Shenzhen City, China. Through a comparison with existing survey-based methods, the parameters associated with road conditions in this method are directly extracted from GPS trajectories, and this method is more effectively deployed than other methods. Since GPS trajectories can cover a wide area if needed, and because the proposed method can be effectively executed, this method can be adapted to large urban scales.

Research on behavior recognition based on feature fusion of automatic coder and recurrent neural network

2020 ◽  
Vol 39 (6) ◽  
pp. 8927-8935
Author(s):  
Bing Zheng ◽  
Dawei Yun ◽  
Yan Liang
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Behavior Pattern ◽  
Rapid Development ◽  
Video Data ◽  
Support Vector ◽  
Behavior Recognition ◽  
Learning Methods ◽  
The Impact ◽  
Internet Of Things Technology

Under the impact of COVID-19, research on behavior recognition are highly needed. In this paper, we combine the algorithm of self-adaptive coder and recurrent neural network to realize the research of behavior pattern recognition. At present, most of the research of human behavior recognition is focused on the video data, which is based on the video number. At the same time, due to the complexity of video image data, it is easy to violate personal privacy. With the rapid development of Internet of things technology, it has attracted the attention of a large number of experts and scholars. Researchers have tried to use many machine learning methods, such as random forest, support vector machine and other shallow learning methods, which perform well in the laboratory environment, but there is still a long way to go from practical application. In this paper, a recursive neural network algorithm based on long and short term memory (LSTM) is proposed to realize the recognition of behavior patterns, so as to improve the accuracy of human activity behavior recognition.

“Land fever” and “Bankruptcy”: Social Problems in Hanoi’s Urbanizing Peri-urban Communities

2019 ◽  
Vol 5 (5) ◽  
pp. 550-562
Keyword(s):  
Rural Communities ◽  
Urban Communities ◽  
Agricultural Production ◽  
Social Problems ◽  
Social Issues ◽  
Field Research ◽  
Credit Market ◽  
Urbanization Process ◽  
Impact Of Urbanization ◽  
The Impact

Drawn upon field research in two peri-urban villages of Hanoi in 2014 and short re-visits recently, the research examines the widespread of gambling and other social issues in Hanoi’s urbanizing peri-urban communities which happened concurrently with the phenomenon of “land fever,” and at the time local villagers received compensation from land appropriation. The article aims to understand the impact of urbanization on these communities and the interface between urbanization and the increase of social problems. It argues that gambling, drug use, and other social problems have been existing in Vietnamese rural communities long before; however, when urbanization came, some people have higher chances to engage in these activities. Those are villagers who want to transform quickly into entrepreneurs or bosses by joining the “black credit” market and gambling. Together with middle-aged and old farmers who greatly relied on agricultural production and face difficulties in transforming their occupation, they formed the group of losers in the urbanization process. Received 6th January 2019; Revised 26th April 2019; Accepted 15th May 2019

Relay Selection-aware Non-orthogonal Multiple Access Networks: Direct and Relaying Mode

2020 ◽  
Vol 13 (3) ◽  
pp. 348-354
Author(s):  
Dinh-Thuan Do ◽  
Minh-Sang V. Nguyen
Keyword(s):  
Relay Selection ◽  
Multiple Access ◽  
Decode And Forward ◽  
Selection Scheme ◽  
Fixed Power ◽  
Transmission Quality ◽  
Improved Performance ◽  
Outage Probabilities ◽  
Future Work ◽  
The Impact

Objective: In this paper, Decode-and-Forward (DF) mode is deployed in the Relay Selection (RS) scheme to provide better performance in cooperative downlink Non-orthogonal Multiple Access (NOMA) networks. In particular, evaluation regarding the impact of the number of multiple relays on outage performance is presented. Methods: As main parameter affecting cooperative NOMA performance, we consider the scenario of the fixed power allocations and the varying number of relays. In addition, the expressions of outage probabilities are the main metric to examine separated NOMA users. By matching related results between simulation and analytical methods, the exactness of derived formula can be verified. Results: The intuitive main results show that in such cooperative NOMA networks, the higher the number of relays equipped, the better the system performance can be achieved. Conclusion: DF mode is confirmed as a reasonable selection scheme to improve the transmission quality in NOMA. In future work, we will introduce new relay selections to achieve improved performance.

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