scholarly journals Deep Wide Spatial-Temporal Based Transformer Networks Modeling for the Next Destination According to the Taxi Driver Behavior Prediction

2020 ◽  
Vol 11 (1) ◽  
pp. 17
Author(s):  
Zain Ul Abideen ◽  
Heli Sun ◽  
Zhou Yang ◽  
Rana Zeeshan Ahmad ◽  
Adnan Iftekhar ◽  
...  
Keyword(s):  
Waiting Time ◽  
Traffic Congestion ◽  
Human Mobility ◽  
Driver Behavior ◽  
Urban Traffic ◽  
Urban Transport ◽  
Geographical Information ◽  
Taxi Driver ◽  
Intelligent Transport System ◽  
Neural Network Approach

This paper uses a neural network approach transformer of taxi driver behavior to predict the next destination with geographical factors. The problem of predicting the next destination is a well-studied application of human mobility, for reducing traffic congestion and optimizing the electronic dispatching system’s performance. According to the Intelligent Transport System (ITS), this kind of task is usually modeled as a multi-class problem. We propose the novel model Deep Wide Spatial-Temporal-Based Transformer Networks (DWSTTNs). In our approach, the encoder and decoder are the transformer’s primary units; with the help of Location-Based Social Networks (LBSN), we encode the geographical information based on visited semantic locations. In particular, we trained our model for the exact longitude and latitude coordinates to predict the next destination. The benefit in the real world of this kind of research is to reduce the customer waiting time for a ride and driver waiting time to pick up a customer. Taxi companies can also optimize their management to improve their company’s service, while urban transport planner can use this information to better plan the urban traffic. We conducted extensive experiments on two real-word datasets, Porto and Manhattan, and the performance was improved compared to the previous models.

Path Reconstruction of Intelligent Traffic Based on Positive Feedback System

2014 ◽  
Vol 513-517 ◽  
pp. 3160-3164
Author(s):  
Xue Li Zhang
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Intelligent Systems ◽  
Supply And Demand ◽  
Demand Management ◽  
Reference Value ◽  
Feedback System ◽  
Urban Traffic ◽  
Urban Transport ◽  
Traffic Demand

Traffic congestion are prevalent in worldwide cities. The imbalance between demand and supply of urban traffic is the root cause of this problem. So taking effective measures to regulate traffic demand, and guiding the traffic problems of the supply and demand balance is the best way to solve traffic congestion. This paper improves the TDM measure, and combines with intelligent information platform for the design of a new urban transport demand management adaptability of dynamic traffic data analysis platform. The platform supported by the technology of wireless sensor communications, intelligent terminals, the Internet and cloud computing is facing with the dynamic needs of traffic flow and traffic congestion state to carry out the operations of spatiotemporal data mining, clustering, and track detection, and to apply it into the traffic hot spots, abnormal driving track, traffic congestion trends and traffic flow detection and analysis, which has a good reference value for the improvement of management and service level of traffic intelligent systems.

Urban Transport GSPN Model of Cyber-Physical Systems

2015 ◽  
Vol 740 ◽  
pp. 900-903
Author(s):  
Wen Cang Zhao ◽  
Bo Tong ◽  
Xiao Xiao Wang
Keyword(s):  
Traffic Congestion ◽  
Cyber Physical Systems ◽  
Urban Traffic ◽  
Urban Transport ◽  
Public Works ◽  
Traffic Network ◽  
Bus Priority ◽  
Technical Problems ◽  
Physical Systems ◽  
Generalized Stochastic Petri Net

Urban transport is an important part of urban activities, and it is not just a public works technical problems or traffic problems, but also is a comprehensive social problems. There are some traffic congestion problems exist in the current urban traffic network. By using the theory of generalized stochastic Petri to the study of Cyber-physical Systems (CPS), this paper established an urban transport GSPN (Generalized Stochastic Petri Net) model, which chosen bus priority strategies to improve the utilization of road.

scholarly journals Driving Behavior Analysis of City Buses Based on Real-Time GNSS Traces and Road Information

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 687 ◽  
Author(s):  
Yuan Yang ◽  
Jingjie Yan ◽  
Jing Guo ◽  
Yujin Kuang ◽  
Mingyang Yin ◽  
...  
Keyword(s):  
Behavior Analysis ◽  
Real Time ◽  
Public Transportation ◽  
Driver Behavior ◽  
Field Tests ◽  
Satellite System ◽  
Driving Behavior ◽  
Urban Environments ◽  
Urban Traffic ◽  
Intelligent Transport System

The driving behavior of bus drivers is related to the safety of all passengers and regulation of urban traffic. In order to analyze the relevant characteristics of speed and acceleration, accurate bus trajectories and patterns are essential for driver behavior analysis and development of effective intelligent public transportation. Exploiting real-time vehicle tracking, this paper develops a platform with vehicle-mounted terminals using differential global navigation satellite system (DGNSS) modules for driver behavior analysis. The DGNSS traces were used to derive the vehicle trajectories, which were then linked to road information to produce speed and acceleration matrices. Comprehensive field tests were undertaken on multiple bus routes in urban environments. The spatiotemporal results indicate that the platform can automatically and accurately extract the driving behavior characteristics. Furthermore, the platform’s visual function can be used to effectively monitor driving risks, such as speeding and fierce acceleration, in multiple bus routes. The details of the platform’s features are provided for intelligent transport system (ITS) design and applications.

Seismic Analysis of Urban Elevated Continuous Bridges Installed Different Damping Devices

2014 ◽  
Vol 638-640 ◽  
pp. 983-986
Author(s):  
Li Jun Ma ◽  
Jian Ming Xu
Keyword(s):  
Traffic Congestion ◽  
Seismic Analysis ◽  
General Scheme ◽  
Urban Traffic ◽  
Urban Transport ◽  
Human Society ◽  
Seismic Capacity ◽  
Continuous Beam Bridge ◽  
Response History Analysis ◽  
Elevated Road

Earthquakes are human recognized natural disasters, causing tremendous loss of life and property to human society, so how to strengthen the seismic capacity of the building more effectively is one of the challenges faced by scientists.While the use of a damping device is an effective method. With the rapid economic and social development, the urban transport problem is an extremely serious livelihood problem faced by all countries. To solve urban traffic congestion, in many cities setting up viaducts is a widely used way to ease urban traffic pressure, and elevated expressways are the main bridges among continuous bridges. In order to ensure the safe operation of the urban elevated road system, we must make the correct evaluation of their seismic capacity. This paper focuses on the continuous beam bridge seismic response history analysis of installing viscous dampers and lock-up devices,compared with the general scheme of continuous bridge.

Development of GIS Integrated Big Data Research Toolbox (BigGIS-RTX) for Mobile CDR Data Processing in Disasters Management

2018 ◽  
Vol 13 (2) ◽  
pp. 380-386 ◽  
Author(s):  
Ko Ko Lwin ◽  
◽  
Yoshihide Sekimoto ◽  
Wataru Takeuchi
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Disaster Management ◽  
Research Collaboration ◽  
Query Language ◽  
Population Distribution ◽  
Human Mobility ◽  
Urban Transport ◽  
Geographical Information ◽  
Transport Planning

This article reports the development of a geographical information system (GIS) embedded text-based geospatial Big Data research toolbox (BigGIS-RTX) designed especially for mobile CDR (Call Details Record) data processing in urban transport planning and disaster management. BigGIS-RTX is a standalone computer program that aims to provide a bridge between geospatial Big Data and end users (i.e. students and researchers) by reducing difficulties in handling geospatial Big Data processing and analysis tasks. This research toolbox makes it possible to handle text-based geospatial Big Data cleaning, formatting, subsetting, and extraction by keywords or structured query language (SQL), CDR data aggregation by base transceiver stations (BTSs), generation of origin–destination (OD) trips, OD matrices, and OD routes, and computation of OD links. Moreover, this research toolbox can be integrated with current commercial GIS software to perform further geospatial analysis functions to improve spatial decision making in urban and transport planning and disaster management. In this report, we discuss two current research outputs using BigGIS-RTX: first, multitemporal grid square population estimation and second, human mobility studies in transportation planning. These research outputs are essential for disaster management and emergency preparedness in terms of providing knowledge and information about population distribution changes over space and time, human mobility flow by a user defined time frame, and travel volume or link count information for individual road segments. This research is part of the core project “Development of a Comprehensive Disaster Resilience System and Collaboration Platform in Myanmar” in a research collaboration between Yangon Technological University, Myanmar, and The University of Tokyo, Japan, sponsored by the Japan Science and Technology Agency (JST) and the Japan International Cooperation Agency (JICA).

scholarly journals Dynamic Bus Scheduling of Multiple Routes Based on Joint Optimization of Departure Time and Speed

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Yingxin Liu ◽  
Xinggang Luo ◽  
Shengping Cheng ◽  
Yang Yu ◽  
Jiafu Tang
Keyword(s):  
Waiting Time ◽  
Traffic Congestion ◽  
Rational Solution ◽  
Urban Traffic ◽  
Joint Optimization ◽  
Passenger Flow ◽  
Bus Scheduling ◽  
Departure Time ◽  
Speed Group ◽  
Multiple Routes

Dynamic bus scheduling is a rational solution to the urban traffic congestion problem. Most previous studies have considered a single bus line, and research on multiple bus lines remains limited. Departure schedules have been typically planned by making separate decisions regarding departure times. In this study, a joint optimization model of the bus departure time and speed scheduling is constructed for multiple routes, and a coevolutionary algorithm (CEA) is developed with the objective function of minimizing the total waiting time of passengers. Six bus lines are selected in Shenyang, with several transfer stations between them, as a typical case. Experiments are then conducted for high-, medium-, and low-intensity case of smooth, increasing and decreasing passenger flow. The results indicate that combining the scheduling departure time and speed produces better performances than when using only scheduling departure time. The total passengers waiting time of the genetic algorithm (GA) group was reduced by approximately 25%–30% when compared to the fixed speed group. The total passengers waiting time of the CEA group can be reduced by approximately 17%–24% when compared to that in the GA group, which also holds true for a multisegment convex passenger flow. The feasibility and efficiency of the constructed algorithm were demonstrated experimentally.

scholarly journals Traffic Congestion Issues, Perceptions, Experience and Satisfaction of Car Drivers/Owners on Urban Roads

2020 ◽  
Vol 39 (3) ◽  
pp. 489-505
Author(s):  
Reena Majid Memon ◽  
Ravindar Kumar Khiani
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Road Construction ◽  
Urban Traffic ◽  
Urban Transport ◽  
Shopping Malls ◽  
Traffic Police ◽  
The Road ◽  
Traffic Jams ◽  
Pedestrian Bridges

Traffic congestion is a major issue of Asian megacities which causes the irritation, anger and frustrations among drivers and owners of vehicles during driving in these cities. This paper aims at understanding traffic congestion issues from the perception and experiences of car drivers and owners and their satisfaction level concerning accessibility of circulation within urban roads of Karachi. The issues addressed in this respect are road construction, traffic flow, road crossing, shopping malls along roads, traffic blockage due to VIP movement, congestion during school timing, animal presence on roads, traffic police behavior, marriage halls along the roads, peak hour traffic jams, traffic jams during sociopolitical and religious rallies, road disputes, traffic congestion due to young inexperienced drivers, alternate road availability and pedestrian bridges. The method of investigating these issues is through 42 questionnaire surveys with car drivers and car owners from June to October 2018 on urban roads of Karachi. The analysis of feedback from respondents showed that, more than 90% respondents were satisfied with construction of pedestrian bridges and annoyed with sociopolitical and religious rallies on main urban roads. More than 80% respondents were satisfied with marriage halls along the roads, felt congestion during peak hours and preferred alternate routes to go home. More than 70% agreed that, young and inexperienced drivers cause traffic congestion and felt unsatisfied and displeased with disputes on the streets among residents, traffic police and drivers. More than 60% respondents were satisfied with the road construction but annoyed with VIP protocol and felt congestion during school timings and quite uncomfortable while crossing the road. More than 50% respondents were unsatisfied with shopping malls on both sides of the road, presence of animals on main roads and behavior of traffic police during traffic jams. Finally, concerning traffic flow the respondents were equally divided in their perception. Thus this research presents a detailed perspective of people regarding traffic congestion issues in Karachi for the appropriate response by decision makers of urban transport planning and urban traffic management institutions in city.

The Study of Interactive Relationship between Urban Construction Area and Road Area

2014 ◽  
Vol 989-994 ◽  
pp. 5197-5200
Author(s):  
Shan Shan Zhang ◽  
Zhen Zhou Yuan
Keyword(s):  
Land Use ◽  
Traffic Congestion ◽  
Programming Model ◽  
Critical Role ◽  
Urban Land Use ◽  
Urban Traffic ◽  
Urban Transport ◽  
Coordinated Development ◽  
Urban Construction ◽  
Interactive Relationship

Urban land-use plays a critical role in the traffic congestion performance and serves as the key ingredient in establishment of cities. To explore the interactive relationship between urban transport and land-use is of great significance for solving the problem of urban traffic and sustainable development. On the basis of microscopic model for the interactive relationship between urban transport and land-use, our paper analyses the interaction between urban construction area and road area, whose dynamic variation is proposed in the simulation. A programming model is presented to assess to the transportation and construction depending the parametric values. Our paper proves that changing the behaviors of travel and improving degree of mixed land-use appropriately can increase the urban construction area, eventually reaching the coordinated development between urban transport and land-use.

A Comprehensive Study on Intelligent Transportation Systems

2018 ◽  
Vol 4 (10) ◽  
pp. 10
Author(s):  
Ankur Mishra ◽  
Aayushi Priya
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Transportation Systems ◽  
Environmental Conservation ◽  
Integrated System ◽  
Transport Systems ◽  
Transport Sector ◽  
Intelligent Transport System ◽  
Intelligent Transport ◽  
Transportation Sector

Transportation or transport sector is a legal source to take or carry things from one place to another. With the passage of time, transportation faces many issues like high accidents rate, traffic congestion, traffic & carbon emissions air pollution, etc. In some cases, transportation sector faced alleviating the brutality of crash related injuries in accident. Due to such complexity, researchers integrate virtual technologies with transportation which known as Intelligent Transport System. Intelligent Transport Systems (ITS) provide transport solutions by utilizing state-of-the-art information and telecommunications technologies. It is an integrated system of people, roads and vehicles, designed to significantly contribute to improve road safety, efficiency and comfort, as well as environmental conservation through realization of smoother traffic by relieving traffic congestion. This paper aims to elucidate various aspects of ITS - it's need, the various user applications, technologies utilized and concludes by emphasizing the case study of IBM ITS.

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