Taxicabs are a critical aspect of the public transit system in New York City. The yellow cabs that are ubiquitous in Manhattan are as iconic as the city’s subway system, and in recent years green taxicabs were introduced by the city to improve taxi service in areas outside of the central business districts and airports. Approximately 500,000 taxi trips are taken daily, carrying about 800,000 pa...

BACKGROUND Research evaluating enforcement and compliance with smoking partial bans is rather scarce, especially in countries with relative weak tobacco control policies, such as Portugal. There is also scarce evidence on specific high risk groups such as vehicle workers. In January 2008, Portugal implemented a partial ban, followed by poor enforcement. The purpose of this study was to explore ...

BACKGROUND Urban taxi drivers differ from other professional drivers in their exposures to physical and psychosocial hazards in the work environment. Epidemiological data on low back pain (LBP) of this occupational group are very scarce. AIMS To examine LBP in taxi drivers and its association with prolonged driving and other occupational factors. METHODS We analyzed the cross-sectional data...

This paper presents a mathematical model for supporting the decision and policy making related to the optimal determination of shifts and fares of taxi services in a major city. The model is based on the system’s generalized cost function and uses continuous approximations and geometric probabilities for estimating the key performance indicators of the taxi market, which are waiting and access ...

BACKGROUND One of the most popular means of public transport within South Africa is mini-bus taxis. OBJECTIVES As South Africa is made up of diverse cultures, religions and beliefs, the aim of this study was to explore Johannesburg based taxi drivers' experiences of beliefs about, and attitudes towards passengers who have a communication disability. METHOD Semi-structured interviews were co...

In building intelligent transportation systems such as taxi or rideshare services, accurate prediction of travel time and distance is crucial for customer experience and resource management. Using the NYC taxi dataset, which contains taxi trips data collected from GPS-enabled taxis [1], this paper investigates the use of deep neural networks to jointly predict taxi trip time and distance. We pr...

In the past few years, we have witnessed a rise in the popularity of ride-hailing services (RHSs), an online marketplace that enables accredited drivers to use their own cars to drive ride-hailing users. Unlike other transportation services, RHSs raise significant privacy concerns, as providers are able to track the precise mobility patterns of millions of riders worldwide. We present the first...

Injury due to road traffic crash is a major cause of ill health and premature deaths in developing countries. Taxis provide a main mode of public transport in Vietnam but there has been little research on the risk of crash for taxi drivers. This retrospective study collected information on taxi crashes for the period 2006-2009 by interviewing drivers from five taxi companies in Hanoi, Vietnam, ...

The predicted growth in air transportation and the ambitious goal of the European Commission to have on-time performance of flights within 1 minute makes efficient and predictable ground operations at airports indispensable. Accurately predicting taxi times of arrivals and departures serves as an important key task for runway sequencing, gate assignment and ground movement itself. This research...

People make systematic and predictable mistakes regarding estimations of average speed and journey time. In addition, people have been shown to commit a time-saving bias by underestimating the time that can be saved when increasing from a low speed and overestimating the time that can be saved when increasing from a relatively high speed. These misestimations have been shown to relate to biases...