Bus Information Systems

Psychology and Technology

Many people find waiting with uncertainty particularly tedious, and studies have found that the lengths of waits are often overestimated when a person does not know how long a wait will last. In the case of bus systems, an additional factor of perceived safety may intensify this experience, as people may be reluctant to use the bus system at night if they are uncertain how long they may have to wait in a dark area that they perceive as potentially dangerous. Providing accurate information about the expected length of a wait, whether by a range of minutes or by a countdown format, has been shown to reduce this overestimation of wait time. In addition, this information allows people to judge when they need to be at the bus stop, and thus when they need to leave their house, whether they have time to run an errand before getting on the bus, etc.

The roots of today's real-time bus information systems lie in technology developed in the 1980s and 1990s to allow transit systems to track the location of their vehicles. Known as automatic vehicle location (AVL) systems, this technology was first used to help transit systems increase their operating efficiency and only later was adapted to provide information to customers.

European municipalities were the first to use AVL systems to provide customers with real-time bus arrival information. The first INFOPOLIS survery, conducted from 1996 to 1997, described over 50 European transit systems supplying real-time information to passengers; the second INFOPOLIS survey, conducted in 1998–2000, described over 150 such systems operating in Europe. By way of contrast, as of 2000 in the United States, just 88 transit systems were using AVL data to supply real-time information to their passengers, although [Page 317]another 142 systems were in the process of developing such programs.

Most real-time bus information systems use GPS (global positioning system) AVL systems to locate vehicles, while some use signpost and transponder systems or other methods. In any case, vehicle location information is combined with operations data (e.g., the travel time between two bus stops, based on the last several trips on a particular route), information about current and past traffic conditions, etc., to estimate vehicle arrival time at a particular stop. Some systems provide additional information, such as the time to the next few stops. Algorithms are used to make this estimation, and different transit systems use different models, based on their needs and the characteristics of their operating environment. In addition to providing arrival information, most transit systems regularly monitor the accuracy of the information provided, so adjustments can be made to the algorithms necessary; unfortunately, such monitoring often drops off the longer a system is in service, thus potentially reducing the benefit of the program by providing inaccurate information to customers.

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