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Real-time passenger bus routing problems with preferences and tradeoffs
One category of vehicle routing problems involving groups of people where there can be multiple possible drop-off locations is the School Bus Routing...
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Passenger flow prediction in bus transportation system using deep learning
The forecasting of bus passenger flow is important to the bus transit system’s operation. Because of the complicated structure of the bus operation...
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Improving Public Transportation Efficiency Through Accurate Bus Passenger Demand
This paper highlights the significance of efficient management of public transportation systems for providing high-quality service to passengers. The...
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Statistal Methods of Bus Passenger Flow Based on Improved YOLOv5s and DeepSORT Algorithms
Aiming at the problem of low tracking accuracy in the statistics of bus passengers getting on and off, an improved passenger flow statistics...
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Enhancing Passenger Safety in an Autonomous Bus: A Multimodal Fall Detection Approach for Effective Remote Monitoring
With the rise of autonomous public transportation, passenger safety in autonomous buses is paramount. This paper introduces a novel Multimodal Long...
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A School Bus Routing Heuristic Algorithm Allowing Heterogeneous Fleets and Bus Stop Selection
This paper addresses a school bus routing problem formulated as a capacitated and time-constrained open vehicle routing problem with a heterogeneous...
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A Bus Stop
We have plenty of complaints about a certain bus stop. People can not get on the bus because when it stops it is already too crowded. We could add...
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Bus Passenger Load Prediction: Challenges from an Industrial Experience
In times of ongoing pandemic outbreak, public transportation systems organisation and operation have been significantly affected. Among others, the...
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Bus passenger flow statistics algorithm based on deep learning
Bus passenger flow statistics can be used to improve passenger travelling experience and reduce trip delay, this is very important for intelligent...
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Exploring trade-offs in public bus electrification under stochastic conditions
In this article, we address the question of electric bus planning and operation under stochastic travel time and energy consumption. Uncertainties in...
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Interfering Spatiotemporal Features and Causes of Bus Bunching using Empirical GPS Trajectory Data
Bus bunching refers to the phenomenon that several buses arrive at a station within a short period. It dramatically increases passengers’ waiting...
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Multivariate long-time series traffic passenger flow prediction using causal convolutional sparse self-attention MTS-Informer
As an important part of the operation preparation process of the intelligent transportation system, the passenger flow distribution law and forecast...
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Intercity customized passenger transportation service plan optimization design with spatial-temporal accessibility based on BIRCH-VNS
Traditional intercity passenger transportation is inefficient, inflexible, and financially unrewarding, failing to meet the demands of intercity...
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Exploring the association between network centralities and passenger flows in metro systems
Network science offers valuable tools for planning and managing public transportation systems, with measures such as network centralities proposed as...
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Meta-learning based passenger flow prediction for newly-operated stations
By tap** into the human mobility of the urban rail transit (URT) network to understand the travel demands and characteristics of passengers in the...
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Estimating urban rail transit passenger inflow caused by special events occurrences fusing multi-source data
It is essential to provide accurate real-time forecasting to manage the intense passenger inflow (IPF) of urban rail transit (URT) stations caused by...
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A distributed EEMDN-SABiGRU model on Spark for passenger hotspot prediction
To address the imbalance problem between supply and demand for taxis and passengers, this paper proposes a distributed ensemble empirical mode...
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A data analytics framework for reliable bus arrival time prediction using artificial neural networks
The analysis of extensive vehicle location data in an urban bus system requires an efficient data-driven method so that its output can be used to...
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A method for short-term passenger flow prediction in urban rail transit based on deep learning
Short-term passenger flow prediction is a critical component of urban rail transit operations. However, predictions of passenger flow are mostly...
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Deep reinforcement learning of passenger behavior in multimodal journey planning with proportional fairness
Multimodal transportation systems require an effective journey planner to allocate multiple passengers to transport operators. One example is...
