Results 21 to 30 of about 22,275 (285)
International Journal of Transportation Science and Technology, 2022 In-vehicle crowding is an external cost imposed on passengers by public transport. It is necessary to quantify the crowding discomfort to measure its influence on passengers’ travel choice.
Minhua Shao +3 more
doaj +1 more source
Bus Travel Time Predictions Using Additive Models [PDF]
2014 IEEE International Conference on Data Mining, 2014 Many factors can affect the predictability of public bus services such as traffic, weather and local events. Other aspects, such as day of week or hour of day, may influence bus travel times as well, either directly or in conjunction with other variables.
Matthias Kormaksson +3 more
openaire +2 more sources
British Educational Research Journal, EarlyView., 2023 Abstract Children's relationship with time in preschools is an under‐researched area. Young children rarely know how to measure time using a clock, but their experiences of time may contribute to understanding children's well‐being and debates about quality in preschools.
Kristín Dýrfjörð +3 more
wiley +1 more source
International Journal of Transportation Science and Technology, 2022 Travel time variability (TTV) is the key indicator used in assessing the service quality of bus transit system. This study explores the most appropriate model to describe the day-to-day TTV of bus section.
Victor Jian Ming Low +2 more
doaj +1 more source
Timely Data Delivery in a Realistic Bus Network [PDF]
, 2010 International audienceWiFi-enabled buses and stops may form the backbone of a metropolitan delay-tolerant network, which exploits nearby communications, temporary storage at stops, and predictable bus mobility to deliver non-real-time information.
Paolo Giaccone +19 more
core +1 more source
Composition of bus travel time.
, 2022 Composition of bus travel time.
Les Lauber (11868978) +5 more
core +1 more source
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020 We present BusTr, a machine-learned model for translating road traffic forecasts into predictions of bus delays, used by Google Maps to serve the majority of the world's public transit systems where no official real-time bus tracking is provided. We demonstrate that our neural sequence model improves over DeepTTE, the state-of-the-art baseline, both in
Richard Barnes 0002 +5 more
openaire +2 more sources
Car Travel Time Estimation near a Bus Stop with Non-motorized Vehicles [PDF]
International Journal of Computational Intelligence Systems, 2011 Real time system for vehicle travel time and traffic flow is an essential part of Intelligent Transportation Systems. In many Chinese cities, the interactions among buses, bicycles and cars bring difficulty to travel time prediction and traffic safety ...
Yang Xiaobao +3 more
doaj +1 more source
Journal of Advanced Transportation, 2020 To analyze the influence of tradable credits and bus departure quantity on travelers' travel mode choice, this study investigated car travel and bus travel as research objects and established a two-mode day-to-day travel mode choice model based on ...
Fang Zhou, Jianhui Wu, Yan Xu, Chi Yi
doaj +1 more source
MODELLING AND ANALYSIS OF THE BUS PRIORITY IMPLEMENTATION
Journal of the Civil Engineering Forum, 2013 Bus is expected to play an important role in providing a reliable travel in congested conditions. Therefore, it has been widely studied to minimize the travel time and the delay of the bus by proposing bus priority scheme to increase the attractiveness ...
Lydia Hidayati
doaj +1 more source