Knowledge Agora



Similar Articles

Title Smart Bus Rerouting
ID_Doc 43708
Authors Roop, VN; Revathy, R
Title Smart Bus Rerouting
Year 2018
Published
Abstract In this paper, an optimization theory for efficient usage of public transport is presented, which determines the optimal way of re-routing, aiming to provide appropriate number of buses based on the need in both less crowded and more crowded areas. This tends to improve the quality of the transportation system leading to a smart city. A "smart city" is an integration of several technologies that are capable of making everyday living more sophisticated and comfortable. Smart city is defined in terms of various domains like smart transportation, waste management, energy management, education, etc. The concept of "smart transportation" is the primary concern of this paper. The Internet of things and Information Communicating Technologies are widely being implemented to cater to the needs of a smart city. The arena of Network Management consists of various challenges, out of which the road side traffic poses a potential issue in day-to-day lives. To solve this problem, the current mechanism opted for routing the buses is based on the particular time-period of the day, classified as peak hours and normal hours. According to this, a route in its peak hours has approximately twice the number of buses in its normal hours. Although this serves advantageous to the large student mass and the corporate employees, the rest of the city residents do not fully benefit from it. Therefore, the technique of dynamic rerouting of buses based on the passenger count at that instant can be utilized in order to achieve the goal. This objective is effectively achieved with the help of maximum flow graph algorithm by mapping the bus stops as vertices and bus routes as edges. The vertex capacity denoting the passenger count in the respective bus stops.
PDF

Similar Articles

ID Score Article
38954 Spaho, E; Koroveshi, A A Low-Cost Solution for Smart-City Based on Public Bus Transportation System Using Opportunistic IoT(2022)
45146 Kos, B Intelligent Transport Systems (ITS) in Smart City(2019)
41066 Bin Hariz, M; Said, D; Mouftah, HT Mobility Traffic Model Based on Combination of Multiple Transportation Forms in the Smart(2019)
42053 Vakula, D; Raviteja, B Smart Public Transport for Smart Cities(2017)
42841 Sadanandan, L; Nithin, S A Smart Transportation System Facilitating On-Demand Bus And Route Allocation(2017)
38825 Thiranjaya, C; Rushan, R; Udayanga, P; Kaushalya, U; Rankothge, W Towards a Smart City: Application of Optimization for a Smart Transportation Management System(2018)
44690 Yue, WS; Chye, KK; Hoy, CW Towards Smart Mobility in Urban Spaces: Bus Tracking and Information Application(2017)
38599 Podlesna, L; Bublyk, M; Grybyk, I; Matseliukh, Y; Burov, Y; Kravets, P; Lozynska, O; Karpov, I; Peleshchak, I; Peleshchak, R Optimization Model of the Buses Number on the Route Based on Queueing Theory in a Smart City(2020)
43086 Jiang, JW Intelligent City Traffic Scheduling Optimization Based on Internet of Things Communication(2021)
43069 Kuo, YH; Leung, JMY; Yan, YM Public transport for smart cities: Recent innovations and future challenges(2023)European Journal Of Operational Research, 306, 3
Scroll