Proceedings ArticleDOI
Public bus arrival time prediction based on traffic information management system
Feng Li,Yuan Yu,HongBin Lin,Wanli Min +3 more
- pp 336-341
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TLDR
A statistical approach to predict the public bus arrival time based on traffic information management system is presented, which has been proved relatively accurate and efficient by experiments.Abstract:
This paper presents a statistical approach to predict the public bus arrival time based on traffic information management system. It considers a number of factors affecting bus travel time, such as departure time, work day, current bus location, number of links, number of intersections, passenger demand at each stop and traffic status of the urban network, etc. A linear model is given to describe the bus arrival time. The parameters of the model are trained by the historical bus arrival times. A prototype system is built to verify the practicability and efficiency of the approach. The approach has been proved relatively accurate and efficient by experiments.read more
Citations
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Proceedings ArticleDOI
Demo: how long to wait?: predicting bus arrival time with mobile phone based participatory sensing
TL;DR: A bus arrival time prediction system based on bus passengers' participatory sensing that achieves outstanding prediction accuracy compared with those bus operator initiated and GPS supported solutions and is more generally available and energy friendly.
Journal ArticleDOI
How Long to Wait? Predicting Bus Arrival Time With Mobile Phone Based Participatory Sensing
TL;DR: A bus arrival time prediction system based on bus passengers' participatory sensing that achieves outstanding prediction accuracy compared with those bus operator initiated and GPS supported solutions and is more generally available and energy friendly.
Journal ArticleDOI
Discovering time-dependent shortest path on traffic graph for drivers towards green driving
TL;DR: This work proposes Heap-based BellmanFord algorithm to find the shortest path in a dynamically changing traffic graph and it works efficiently in practical implementations and proves the correctness of the algorithms and discusses their time complexity.
DatasetDOI
Online Bus Arrival Time Prediction Using Hybrid Neural Network and Kalman filter Techniques
TL;DR: This paper presents an effective method that can be used to predict the expected bus arrival time at individual bus stops along a service route that combines a neural network that infers decision rules from historical data with Kalman filter that fuses prediction calculations with current GPS measurements.
Journal ArticleDOI
Cyclist-aware traffic lights through distributed smartphone sensing
Theodoros Anagnostopoulos,Denzil Ferreira,Alexander Samodelkin,Muzamil Ahmed,Vassilis Kostakos +4 more
TL;DR: A Boundary model able to reduce GPS sensor power consumption, while performing time-of-arrival estimation to the nearest light is treated, achieving a promising model for in-the-wild cycling scenarios.
References
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Journal ArticleDOI
Real-time road traffic prediction with spatio-temporal correlations
Wanli Min,Laura Wynter +1 more
TL;DR: The method presented provides predictions of speed and volume over 5-min intervals for up to 1 h in advance for real-time road traffic prediction to be both fast and scalable to full urban networks.
Journal ArticleDOI
Dynamic Bus Arrival Time Prediction with Artificial Neural Networks
TL;DR: Two artificial neural networks, trained by link-based and stop-based data, are applied to predict transit arrival times and show that the enhanced ANNs outperform the ones without integration of the adaptive algorithm.
Journal ArticleDOI
Experimental Study of Real-Time Bus Arrival Time Prediction with GPS Data:
Wei-Hua Lin,Jian Zeng +1 more
TL;DR: An experimental study has been conducted on forecasting the arrival time of the next bus with automatic vehicle location techniques, and results show that at the site where the study is being conducted, the dwell time at time-check stops is most relevant to the performance of an algorithm.
Bus travel time prediction model for dynamic operations control and passenger information systems
Amer Shalaby,Ali Farhan +1 more
TL;DR: In this article, the authors used AVL and APC dynamic data to develop a bus travel time model capable of providing real-time information on bus arrival times to passengers, via traveler information services and to transit controllers for the application of proactive control strategies.
Journal ArticleDOI
Models for Predicting Bus Delays
Ali M. Abdelfattah,Ata M. Khan +1 more
TL;DR: The development of models for the estimation of the effect of changes in traffic and lane closures on bus performance is described and a microsimulation approach was used, supplemented by field studies.