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What are architectural building systems?
Published in Samuel L. Hurt, Building Systems in Interior Design, 2017
This machine is often called a “wheelchair lift” because its main purpose is to lift someone in a wheelchair no more than a single story (often limited to 12 feet vertical) and usually without a hoistway. They are frequently located outdoors where they are used to provide access to building entrances not at grade, but they can be used for indoor level transitions too. Given that they are used to move wheelchairs vertically, their platforms are usually 5′ × 5′ and the overall unit is usually about 5.5′ × 6.5′ in plan. Dumbwaiters are another common form of lift, except that dumbwaiters move trays or carts—never people.
Modeling bus bunching using massive location and fare collection data
Published in Journal of Intelligent Transportation Systems, 2018
Jacqueline Arriagada, Antonio Gschwender, Marcela A. Munizaga, Martin Trépanier
Regarding the importance of waiting time in the quality of public transport, some studies have focused on understanding the phenomenon of irregular buses to prevent the problem. TRB (2003) and Strathman and Hopper (1993) have identified some factors that affect reliability (this term encompasses both on-time performance and the regularity of headways), such as traffic conditions (including incidents and congestion), vehicle and maintenance quality, transit preferential treatments (such as exclusive bus lanes or a transit signal priority [TSP] system), the number of passengers (boarding and alighting) between successive vehicles, wheelchair lift usage, route length, number of stops, and the behavior or skills of bus drivers. Some of these variables were mentioned by Bhouri, Aron, Patrick, and Haj-Salem (2017) as factors that affect travel time reliability, which has a relation with headway variability. Bellei and Gkoumas (2010) developed a stochastic simulation model for a bus service that operates by frequency and found that the bus irregularity phenomenon at a fixed stop is directly related to the advanced distance route, travel time, and boarding passengers. Moreira-Matias, Ferreira, Gama, Mendes-Moreira, and de Sousa (2012) studied data obtained from the Automatic Vehicle Location (AVL) system of the public transport operator of Porto (Portugal) and found that bus bunching is mainly produced by the deviation of the scheduled headway at the beginning of the route, the high frequency of buses, the number of boarding passengers, and the irregularity of arrivals to the previous stop. Albright and Figliozzi (2012) used data from the AVL and Automatic Passenger Counter (APC) systems of two bus services from Portland (USA) that operate with scheduled itineraries to construct a linear regression model where the dependent variable is the headway at the end of the route between each pair of consecutive buses. Using this model, they showed that the bus bunching problem (defined as the presence of short headways) can be explained by the number of boarding passengers and alighting passengers in the first bus of the pair of consecutive buses, the use of elevators in the first bus, and the use of the TSP system in the second bus. Man and Wenquan (2013) presented a bus arrival simulation model for a bus service that operates by frequency and found that traffic conditions, passenger demand, and scheduled headway are factors affecting headway regularity. They found that longer intervals and less scheduled headway fluctuation contribute to more regular headways.