The objective of this study is to provide a better understanding of the potential of using
Artificial Intelligence (AI) to improve Public Transport (PT), by reviewing research literature …

To improve the prediction accuracy of traffic flow, a travel time prediction model based on
gradient boosting decision tree (GBDT) is proposed. In order to test the applicability of …

The accuracy of travel time information given to passengers plays a key role in the success
of any Advanced Public Transportation Systems (APTS) application. In order to improve the …

Machine learning (ML) solutions have been proposed to make public transportation more
attractive. Works that employ ML in bus transportation focus on various problems, such as …

Public transport buses have uncertainties associated with its arrival/travel times, due to
several factors such as signals, dwell times at bus stops, seasonal variations, fluctuating …

Providing accurate bus travel time information is very important to help passengers plan
their trips and reduce waiting times. Due to the uncertainty of the bus travel time, the …

In an intelligent transportation system, accurate bus information is vital for passengers to
schedule their departure time and make reasonable route choice. In this paper, an improved …

Arrival/Travel times for public transit exhibit variability on account of factors like seasonality,
dwell times at bus stops, traffic signals, travel demand fluctuation etc. The developing world …

Travel time of traffic flow is the basis of traffic guidance. To improve the estimation accuracy,
a travel time estimation model based on Random Forests is proposed. 7 influence variables …

Travel time is one of the most appropriate traffic measures that can be provided to road
users for easy understanding and decision making. This paper presents a simple method to …