Mobile Enabled RFID-GPS Based Bus Tracking System

2014 ◽  
Vol 6 (4) ◽  
pp. 10-34 ◽  
Author(s):  
Suresh Sankaranarayanan ◽  
Paul Hamilton
Keyword(s):  
Public Transportation ◽  
Tracking System ◽  
Research Work ◽  
Transportation Systems ◽  
Urban Transport ◽  
Time Of Arrival ◽  
Rfid Technology ◽  
Arrival Times ◽  
Traffic Lights ◽  
Bus Stops

Public transportation in many countries is being used as a means of transport for travelling and accordingly people would prefer these public transportation to be scheduled properly, on time and the frequency be adequately fixed for commuters to make good use of it. It has been found that quite an amount of research work has been carried out, by way of using RFID technology in the public transportation systems towards the tracking of passengers when they board and exit buses. In addition research has also been carried out in using GPS towards the tracking of buses along with RFID technology at traffic lights, bus stops, intersections etc and also displaying expected arrival times on LCD screen at bus stops along with their current positions. Taking these aspects into consideration, an intelligent mobile bus tracking system for the Jamaican Urban Transport Corporation has been proposed and validated as a case study. The proposed system also enables commuters towards tracking the bus of their choice and also knowing their expected arrival times. So taking the above aspects into consideration, in this research the authors have proposed and validated on how control center of a bus company could track the location of a bus based on information received from RFID reader and GPS Transmitter positioned at various Bus stops and in the Bus and accordingly the expected time of arrival calculated for displaying the information on commuter's handset via Gmap. The implementation of the bus tracking scheme has been carried out using Adobe Flash player and Java.

Transit Travel Demand Analysis Method Based on APTS Multi-Source Data

2013 ◽  
Vol 361-363 ◽  
pp. 2122-2126
Author(s):  
Jun Chen ◽  
Xiao Hua Li ◽  
Lan Ma
Keyword(s):  
Public Transportation ◽  
Large Scale ◽  
Travel Demand ◽  
Low Cost ◽  
Transportation Systems ◽  
Demand Analysis ◽  
Sample Survey ◽  
Analysis Method ◽  
Source Data ◽  
Bus Stops

Traditional transit travel information is acquired by Trip Sample Survey which has some disadvantages including high cost and short data lifecycle. This paper researched transit travel demand analysis method using Advanced Public Transportation Systems (APTS) data. The study collected APTS data of Nanning City in China and established APTS multi-source data analysis platform applying data warehouse technology. Based on key problems research, the paper presented the analysis procedure and content. Then, this study proposed the core algorithms of the method which are determinations of boarding bus stops, alighting bus stops and transfer bus stops of smart card passengers. Finally, these algorithms programs are experimented using large scale practical APTS data. The results show that this analysis method is low cost, operability and high accuracy.

scholarly journals Passive Wi-Fi monitoring in the wild: a long-term study across multiple location typologies

2020 ◽  
Author(s):  
Miguel Ribeiro ◽  
Nuno Nunes ◽  
Valentina Nisi ◽  
Johannes Schöning
Keyword(s):  
Public Transportation ◽  
Rural Areas ◽  
Urban Areas ◽  
Large Scale ◽  
Tracking System ◽  
Human Mobility ◽  
Transportation Systems ◽  
Mobility Patterns ◽  
Systematic Analysis ◽  
Long Term Study

Abstract In this paper, we present a systematic analysis of large-scale human mobility patterns obtained from a passive Wi-Fi tracking system, deployed across different location typologies. We have deployed a system to cover urban areas served by public transportation systems as well as very isolated and rural areas. Over 4 years, we collected 572 million data points from a total of 82 routers covering an area of 2.8 km2. In this paper we provide a systematic analysis of the data and discuss how our low-cost approach can be used to help communities and policymakers to make decisions to improve people’s mobility at high temporal and spatial resolution by inferring presence characteristics against several sources of ground truth. Also, we present an automatic classification technique that can identify location types based on collected data.

Application of RFID Technology in Development Smart Home and Traffic System

2013 ◽  
Vol 341-342 ◽  
pp. 709-714
Author(s):  
Ting Zhong Wang ◽  
Ai Di Zhi
Keyword(s):  
Intelligent Transportation Systems ◽  
Smart Home ◽  
Electrical Equipment ◽  
Transportation Systems ◽  
Urban Transport ◽  
Traffic Information ◽  
Rfid Technology ◽  
Emission Data ◽  
Traffic System ◽  
Passive Tags

Smart Home is a versatile technology system family residential platform, the use of advanced computer technology and network technology, the families in a variety of electrical equipment connected together through some form of network. RFID can also be divided into active tags and passive tags. An active tag with RF energy initiative to give the reader sends data main obstacles applications; passive tags using modulated backscatter emission data. The paper puts forward the application of RFID technology in development Smart Home and Traffic System. The application of intelligent transportation systems in urban transport is by increasing the effective use and management of traffic information to improve the efficiency of the transportation system.

scholarly journals Analysis of Aerial Ropeways by following various Indian and International Codes for Urban Mobility with some Structural Modifications in Monocable Ropeways to make it Safe, Secure, Economical and all Weather Durable

2021 ◽  
Vol 9 (VI) ◽  
pp. 1539-1548
Author(s):  
Bhat Omair Bashir
Keyword(s):  
Public Transportation ◽  
Urban Areas ◽  
Public Transit ◽  
Transportation Systems ◽  
Urban Transport ◽  
Transport Systems ◽  
Transit Systems ◽  
Tourist Attractions ◽  
Structural Modifications ◽  
Transit Service

Cable-propelled transit’ (CPT), in particular detachable aerial ropeways are widely employed as transportation systems in alpine areas. In recent years, these transport systems have also been increasingly used in urban areas and are no longer a niche public transportation technology (Hoffmann 2006, Alshalalfah, Shalaby, and Dale 2014). Cable cars systems compete with performance characteristics of other more common urban transport technologies and have the potential to enhance the existing transport provision in cities (O'Connor and Dale 2011). While many applications can be found as transportation systems in airport facilities, and to provide access to tourist attractions, several metropolitan areas have even incorporated gondolas and aerial tramways into their public transport networks. This paper focuses on aerial ropeway systems that operate as a mass transit service (similar to buses, BRT, LRT, etc.) and are part of the public transit systems in their respective cities. Therefore, the analysis and case studies presented in the paper concern systems that are used as a public transit service

Efficient Traffic Simulation Using Busses as Active Sensor Network

2011 ◽  
Author(s):  
Ludovico Catani ◽  
Emanuele Frontoni ◽  
Primo Zingaretti ◽  
Guido Di Pasquale
Keyword(s):  
Sensor Network ◽  
Public Transportation ◽  
Traffic Simulation ◽  
Transportation Systems ◽  
Simulation System ◽  
Traffic Data ◽  
Traffic Lights ◽  
The Road ◽  
Normal Speed ◽  
On The Road

In this paper we present a traffic simulation system using traffic data gathered from readings by GPS devices installed on board of busses, i.e., busses running on the road are used as a mobile sensor network. Traffic data are inferred from the comparison of data about normal speed and current speed in a certain position. The simulation system was developed to invent mechanisms that use such information for traffic optimization. In particular, simulations allow to manage traffic lights in real time and to control the traffic system in order to give priority to public transportation systems.

scholarly journals Enabling and Emerging Sensing Technologies for Crowd Management in Public Transportation Systems: A Review

2021 ◽  
Author(s):  
Donatella Darsena ◽  
Giacinto Gelli ◽  
Ivan Iudice ◽  
Francesco Verde
Keyword(s):  
Real Time ◽  
Information And Communication Technologies ◽  
Public Transportation ◽  
Urban Areas ◽  
Transportation Systems ◽  
Normal Operation ◽  
Reference Architecture ◽  
Sustainable Mobility ◽  
Crowd Management ◽  
Bus Stops

Management of crowd information in public transportation (PT) systems is crucial to foster sustainable mobility, by increasing the user’s comfort and satisfaction during normal operation, as well as to cope with emergency situations, such as pandemic crises, as recently experienced with COVID-19 limitations. This paper presents a taxonomy and review of sensing technologies based on Internet of Things (IoT) for real-time crowd analysis, which can be adopted in various segments of the PT system (buses/trams/trains, railway/subway stations, and bus stops). To discuss such technologies in a clear systematic perspective, we introduce a reference architecture for crowd management, which employs modern information and communication technologies (ICT) in order to: (i) monitor and predict crowding events; (ii) adapt in real-time PT system operations, by modifying service frequency, timetables, routes, and so on; (iii) inform in real-time the users of the crowding status of the PT system, by means of electronic displays installed inside vehicles or at bus stops/stations, and/or by mobile transport applications. It is envisioned that the innovative crowd management functionalities enabled by ICT/IoT sensing technologies can be incrementally implemented as an add-on to traditional intelligent transportation system (ITS) platforms, which are already in use by major PT companies operating in urban areas. Moreover, it is argued that, in this new framework, additional services can be delivered, such as, e.g., on-line ticketing, vehicle access control and reservation in severely crowded situations, and evolved crowd-aware route planning.

scholarly journals Accident Analysis of Bus Rapid Transit System: Before and after construction

2020 ◽  
Vol 79 (ET.2020) ◽  
pp. 1-17
Author(s):  
Amir Izadi
Keyword(s):  
Public Transportation ◽  
Transportation Systems ◽  
Influential Factors ◽  
Urban Transport ◽  
Bus Rapid Transit ◽  
Rapid Transit ◽  
Transit System ◽  
Standard Design ◽  
Before And After ◽  
Accident Data

Among the various transportation systems, public transportation, especially Bus Rapid Transit (BRT), has a significant role in urban transport and has the mission of transfer of passengers and reducing travel time. In addition to these advantages, the weak and non-standard design and implementation of BRT lines result in an escalation of accidents and inefficiency. Therefore, the aim of this study is to investigate the influential factors of the severity of BRT lines accidents before and after their construction. For this purpose, the accident data of Rasht BRT line 1 over the years of 2016 (before the construction of the BRT), 2017 and 2018 (after the construction of the BRT) have been analysed. The results showed that the construction of BRT has brought about 36 and 43 per cent reduction of accidents in 2017 and 2018, respectively, in comparison with 2016, and has given rise to the emergence of new accidents, such as collision with separator fence.

scholarly journals Bus Arrival Prediction – to Ensure Users not to Miss the Bus

2015 ◽  
Vol 5 (2) ◽  
pp. 333 ◽  
Author(s):  
Lutfi Fanani ◽  
Achmad Basuki ◽  
Deron Liang
Keyword(s):  
Normal Distribution ◽  
Public Transportation ◽  
Arrival Time ◽  
Waiting Times ◽  
Transportation Systems ◽  
Accurate Information ◽  
Peak Time ◽  
Distribution Method ◽  
Arrival Times ◽  
Public Transportation Systems

Predicting arrival times of buses is a key challenge in the context of building intelligent public transportation systems. The bus arrival time is the primary information for providing passengers with an accurate information system that can reduce passenger waiting times. In this paper, we used the normal distribution method to the random of travel times data in a bus line number 243 in Taipei area. In developing the models, data were collected from Taipei Bus Company. A normal distribution method used for predicting the bus arrival time in bus stop to ensure users not to miss the bus, and compare the result with the existing application. The result of our experiment showed that our proposed method has a better prediction than existing application, with the probability user not to miss the bus in peak time is 93% and in normal time is 85%, greater than from the existing application with the 65% probability in peak time, and 70% in normal time.

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