Traffic Modelling, Visualisation and Prediction for Urban Mobility Management

2017 ◽  
pp. 57-70 ◽  
Author(s):  
Tomasz Maniak ◽  
Rahat Iqbal ◽  
Faiyaz Doctor
Keyword(s):  
Mobility Management ◽  
Urban Mobility ◽  
Traffic Modelling

SEnTINEL - INtELligent Transport SystEm for Urban Mobility Management in Smart Cities

2019 ◽  
Author(s):  
Matheus Sanches Quessada ◽  
Andre Luis Cristiani ◽  
Pedro Luis Ranzani Junior ◽  
Matheus Pereira Leal ◽  
Rodolfo Ipolito Meneguette
Keyword(s):  
Transport System ◽  
Mobility Management ◽  
Smart Cities ◽  
Intelligent Transport System ◽  
Urban Mobility ◽  
Intelligent Transport

scholarly journals The contribution of urban mobility management to trip planning and the environmental upgrade of urban areas

2011 ◽  
Vol 20 ◽  
pp. 162-170 ◽  
Author(s):  
Maria Morfoulaki ◽  
Evangelos Mitsakis ◽  
Katerina Chrysostomou ◽  
Iraklis Stamos
Keyword(s):  
Mobility Management ◽  
Urban Areas ◽  
Urban Mobility ◽  
Trip Planning

Improving Urban Mobility Management

2006 ◽  
Vol 1956 (1) ◽  
pp. 52-59 ◽  
Author(s):  
Antonio Musso ◽  
Maria Vittoria Corazza
Keyword(s):  
Mobility Management ◽  
Urban Mobility

scholarly journals Urban mobility management: new challenges for a sustainable future

2013 ◽  
Vol XII (2) ◽  
pp. 164-170
Author(s):  
Fabio Famoso ◽  
Iolanda Laura Lanzafame
Keyword(s):  
Mobility Management ◽  
Urban Mobility ◽  
Sustainable Future ◽  
New Challenges

scholarly journals Route Planning Based On Urban Mobility Management

2016 ◽  
Vol 44 (2) ◽  
pp. 71-79 ◽  
Author(s):  
Tamás Mátrai ◽  
János Tóth ◽  
Márton Tamás Horváth
Keyword(s):  
Significant Role ◽  
Mobility Management ◽  
Information Technologies ◽  
Route Planning ◽  
Urban Transport ◽  
Route Guidance ◽  
Urban Mobility ◽  
Step Model

Abstract Mobility management centres play a significant role in urban transport, taking into account several factors that have an effect on the flow of vehicles. In the present paper a mobility management centre equipped with necessary information and information technologies for travellers is presented that can provide route plans. A route guidance methodology is described that combines current transportation demands with the results of the traditional four-step model.

scholarly journals Exploiting Vehicular Social Networks and Dynamic Clustering to Enhance Urban Mobility Management

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3558 ◽  
Author(s):  
Ademar Takeo Akabane ◽  
Roger Immich ◽  
Richard Wenner Pazzi ◽  
Edmundo Roberto Mauro Madeira ◽  
Leandro Aparecido Villas
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Mobility Management ◽  
Traffic Management ◽  
Dynamic Clustering ◽  
Urban Mobility ◽  
Traffic Lights ◽  
Management Efficiency ◽  
Advanced Traffic Management System ◽  
Alternative Routes

Transport authorities are employing advanced traffic management system (ATMS) to improve vehicular traffic management efficiency. ATMS currently uses intelligent traffic lights and sensors distributed along the roads to achieve its goals. Furthermore, there are other promising technologies that can be applied more efficiently in place of the abovementioned ones, such as vehicular networks and 5G. In ATMS, the centralized approach to detect congestion and calculate alternative routes is one of the most adopted because of the difficulty of selecting the most appropriate vehicles in highly dynamic networks. The advantage of this approach is that it takes into consideration the scenario to its full extent at every execution. On the other hand, the distributed solution needs to previously segment the entire scenario to select the vehicles. Additionally, such solutions suggest alternative routes in a selfish fashion, which can lead to secondary congestions. These open issues have inspired the proposal of a distributed system of urban mobility management based on a collaborative approach in vehicular social networks (VSNs), named SOPHIA. The VSN paradigm has emerged from the integration of mobile communication devices and their social relationships in the vehicular environment. Therefore, social network analysis (SNA) and social network concepts (SNC) are two approaches that can be explored in VSNs. Our proposed solution adopts both SNA and SNC approaches for alternative route-planning in a collaborative way. Additionally, we used dynamic clustering to select the most appropriate vehicles in a distributed manner. Simulation results confirmed that the combined use of SNA, SNC, and dynamic clustering, in the vehicular environment, have great potential in increasing system scalability as well as improving urban mobility management efficiency.

Model for shaping urban mobility – system-functional approach

2018 ◽  
Vol 120 ◽  
pp. 471-480
Author(s):  
Renata Żochowska ◽  
Grzegorz Karoń
Keyword(s):  
Decision Making ◽  
Mobility Management ◽  
Decision Model ◽  
Functional Form ◽  
Functional Approach ◽  
Formal Description ◽  
Urban Mobility ◽  
Basic Assumptions ◽  
Mobility System ◽  
Decision Making Model

The article presents a decision-making model for shaping urban mobility in a system-functional form. First, the mobility management process was characterized. Next, a formal description of the basic assumptions of the decision-making model for urban mobility management and the architecture of the decision model in the form of an algorithm for selecting mobility actions were presented.

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