scholarly journals Prediction of travel time for railway traffic management by using the AdaBoost algorithm

2021 ◽  
Author(s):  
Mehmet Taciddin AKÇAY ◽  
Abdurrahim AKGUNDOGDU ◽  
Hasan TİRYAKİ
Keyword(s):  
Travel Time ◽  
Traffic Management ◽  
Adaboost Algorithm ◽  
Railway Traffic

Constraint-force driven control design for rail vehicle virtual coupling

2021 ◽  
pp. 107754632110079
Author(s):  
Bin Wang ◽  
Dengke Yang ◽  
Xinrong Zhang ◽  
Xingheng Jia
Keyword(s):  
Dynamic Model ◽  
Traffic Management ◽  
Control Method ◽  
Constraint Force ◽  
Explicit Equation ◽  
Coupling Problem ◽  
Railway Traffic ◽  
Rail Vehicle ◽  
Virtual Coupling ◽  
Traffic Management System

This study investigates the constraint-force driven control problem of virtual coupling. To solve the constraint force, the explicit equation of vehicle motion with equality constraints is established using the Udwadia–Kalaba approach. First of all, this study introduces a brief overview of virtual coupling concepts in the European Railway Traffic Management System and some scenes of virtual coupling. The control method is proposed to enable the mechanical system to follow the designed constraint. Moreover, the dynamic model for virtual coupling problem is established. Second, combined with the dynamic model, the equation constraint is designed to make the rail vehicle movenment reach the control objective. By solving the equation based on the Udwadia–Kalaba approach, the control inputs that can render the vehicle to move along the desired trajectory. Third, numerical simulation results demonstrate the effectiveness of the proposed method in virtual coupling problem.

scholarly journals Road Traffic Congestion Management Based on a Search-Allocation Approach

2017 ◽  
Vol 18 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Jamal Raiyn
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Smart Cities ◽  
Self Regulation ◽  
Congestion Management ◽  
Shortest Route ◽  
Road Traffic Congestion

Abstract This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA). An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT) technologies.

scholarly journals Estimates of Economic Cost of Congestion Travel Time Delay Between Onne-Seaport and Eleme-Junction Traffic Corridor

2020 ◽  
Vol 11 (2) ◽  
pp. 33-43
Author(s):  
Theophilus C. Nwokedi ◽  
Lazarus I. Okoroji ◽  
Ifiok Okonko ◽  
Obed C. Ndikom
Keyword(s):  
Time Delay ◽  
Travel Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Oil And Gas ◽  
Economic Cost ◽  
Oil And Gas Industry ◽  
Research Approach ◽  
Traffic Corridor ◽  
Output Losses

AbstractTravelers along the Onne-seaport to Eleme-junction road corridor in the hub of the oil and gas industry in Port-Harcourt, Nigeria, have continued to experience very serious traffic congestion travel time delays, culminating into loss of man-hours and declining productivity. This study estimated the economic cost of traffic congestion travel time delay along the corridor, with a view to providing economic justification for developing traffic management policies and road infrastructure, to remedy it. A mixed research approach was adopted in which data was sourced through field survey and from secondary sources. The gross output model was used to estimate the output losses occasioned by productive time losses related to traffic congestion. The study established that the average daily traffic congestion travel time delay along the traffic corridor by travelers in trucks, car, bus and taxi modes are 104.17 minutes, 46.60 minutes, 58.5 minutes and 56.4 minutes respectively. The estimated daily aggregate economic cost of output losses associated with traffic congestion time delay on the corridor is 46049809.8 naira (210923.5USD) for all modes. This justifies any investment in traffic congestion remedial strategies along the route.

scholarly journals Digitization in Rail Transport

2020 ◽  
Vol 64 (188) ◽  
pp. 137-148
Author(s):  
Janusz Poliński ◽  
Krzysztof Ochociński
Keyword(s):  
Customer Service ◽  
Traffic Management ◽  
Transport Infrastructure ◽  
Rolling Stock ◽  
Railway Transport ◽  
Railway Traffic ◽  
Railway Industry ◽  
Operations And Maintenance ◽  
Trained Staff

Digital transformation in the railway industry is an important element in the development of railways and should benefit commuters, railway operators, infrastructure managers and rolling stock manufacturers. The process of digitization applies to two domains, i.e. customer service and railway companies’ operation. This paper aims to present previous eff orts regarding the use of digital technologies in customer relations and in the field of operations and maintenance, which translates into the quality of services provided. This paper highlights important concepts of this domain with respect to passenger and freight transport, infrastructure, railway rolling stock and railway traffic management. It is also argued that the process of digitization needs properly trained staff . Examples of innovative initiatives of Polish and European railway companies are covered. Keywords: railway transport, digitization, digitization of the railways

Performance Analyses of Information-Based Managed Lane Choice Decisions in a Connected Vehicle Environment

2020 ◽  
Vol 2674 (11) ◽  
pp. 120-133 ◽  
Author(s):  
Xiaoyu Guo ◽  
Yongxin Peng ◽  
Sruthi Ashraf ◽  
Mark W. Burris
Keyword(s):  
Travel Time ◽  
Travel Behavior ◽  
Information Exchange ◽  
Traffic Management ◽  
Connected Vehicle ◽  
Market Penetration ◽  
Performance Measurements ◽  
Time Saving ◽  
Travel Time Savings ◽  
Time Savings

Connected vehicle (CV) technology can connect, communicate, and share information between vehicles, infrastructure, and other traffic management systems. Recent research has examined and promoted CV and connected automated vehicle (CAV) technology on managed lane systems to increase capacity and reduce congestion, as managed lane systems could be equipped with advanced infrastructure relatively quickly. However, the effect on travel considering, information-based managed lane choice decisions in a CV environment is not clear. Therefore, this research analyzed the potential effects on a managed lane system with connected vehicles considering several travel behavior elements, including drivers’ willingness to reroute and their choice of managed lanes based on individual travel time savings. This study analyzed the potential effects on a managed lane system by assigning different market penetration rates (0%, 10%, 50%, 100%) of CVs and informing CV drivers about travel time savings for a 10-mi stretch at 5-min intervals. How the traffic performance measurements (i.e., throughput, travel time saving, average speed and average travel time) vary under different market penetration rates of CVs is then investigated. Two major conclusions are reached: (i) although information exchange was assumed to be instantaneous between vehicles and the system, there existed a response time (or time delay) in the macroscopic traffic reflection; (ii) managed lane use may decrease, when travel time information becomes available, since drivers perceive they are saving more travel time than they actually do save.

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