相关论文: Trans-Sense: Real Time Transportation Schedule Est…

Shifting travel from private cars to public transport is critical for meeting climate and related mobility goals, yet passengers will only choose transit if it offers a consistently positive experience. Previous studies of passenger…

In recent decades, mobile applications (apps) have gained enormous popularity. Smart services for smart cities increasingly gain attention. The main goal of the proposed research is to present a new AI-powered mobile application on…

Routine and consistent data collection is required to address contemporary transportation issues.The cost of data collection increases significantly when sophisticated machines are used to collect data. Due to this constraint, State…

Drive-by sensing (i.e. vehicle-based mobile sensing) is an emerging data collection paradigm that leverages vehicle mobilities to scan a city at low costs. It represents a positive social externality of urban transport activities. Bus…

In an effort to improve user satisfaction and transit image, transit service providers worldwide offer delay compensations. Smart card data enables the estimation of passenger delays throughout the network and aid in monitoring service…

Providing transport users and operators with accurate forecasts on travel times is challenging due to a highly stochastic traffic environment. Public transport users are particularly sensitive to unexpected waiting times, which negatively…

Public transport systems are expected to reduce pollution and contribute to sustainable development. However, disruptions in public transport such as delays may negatively affect mobility choices. To quantify delays, aggregated data from…

Travel time prediction is central to transport geography and planning's accessibility analyses, sustainable transportation infrastructure provision, and active transportation interventions. However, calculating accurate travel times,…

Accurate and reliable travel time predictions in public transport networks are essential for delivering an attractive service that is able to compete with other modes of transport in urban areas. The traditional application of this…

Household travel surveys have been used for decades to collect individuals and households' travel behavior. However, self-reported surveys are subject to recall bias, as respondents might struggle to recall and report their activities…

Urban commuting data has long been a vital source of understanding population mobility behaviour and has been widely adopted for various applications such as transport infrastructure planning and urban anomaly detection. While…

The growing prevalence of Internet of Things (IoT) technologies has led to a rise in the popularity of intelligent vehicles that incorporate a range of sensors to monitor various aspects, such as driving speed, fuel usage, distance…

Public transport routing plays a crucial role in transit network design, ensuring a satisfactory level of service for passengers. However, current routing solutions rely on traditional operational research heuristics, which can be…

The idea of modern urban systems and smart cities requires monitoring and careful analysis of different signals. Such signals can originate from different sources and one of the most promising is the BTS, i.e. base transceiver station, an…

We present T-REX (Transfer-Ranked EXploration), a new algorithm for journey planning in public transit networks on the country and continental scale. Our algorithm applies the principles of multi-level overlays to Trip-Based Public Transit…

The growth of urban areas intensifies the need for sustainable, efficient transportation infrastructure and mobility systems, driving initiatives to enhance infrastructure and public transit while reducing traffic congestion and emissions.…

Because of the complexity of urban transportation networks and the temporal changes in traffic conditions, it is difficult to assess real-time traffic situations. However, the development of information terminals has made it easier to…

Detailed understanding of multi-modal mobility patterns within urban areas is crucial for public infrastructure planning, transportation management, and designing public transport (PT) services centred on users' needs. Yet, even with the…

Recent statistical methods fitted on large-scale GPS data can provide accurate estimations of the expected travel time between two points. However, little is known about the distribution of travel time, which is key to decision-making…

Public bus transport systems in developing countries often suffer from a lack of real-time location updates and for users, making commuting inconvenient and unreliable for passengers. Furthermore, stopping at undesired locations rather than…