Autonomous cars have arrived — Uber has a fleet operating in Pittsburgh, Google’s parent company is spinning off its driverless car project in a sign it is closer to coming to market, and the federal government has begun to issue guidelines on how the cars should work.
Economic evaluation (also called appraisal, assessment or analysis) refers to various methods to determine the value of a policy, program or project. It involves quantifying incremental (also called marginal) economic impacts (benefits and costs) to determine net benefits or net value (benefits minus costs), and the distribution (also called incidence) of these impacts. Economic evaluation is not limited to market impacts (which involve goods that are commonly traded in competitive markets), it can also incorporate non-market resources such as personal time, health and environmental quality.
A common theme among articles within TransitWiki is strategies to improve reliability of transit service (see Off-vehicle fare payment, Transit signal priority, and Internet communications, for example). To understand how to improve reliability of service, transit planners should understand the perception of unreliability among passengers and common responses to such factors. Many people may consider transit were it not for fear of perceived or true unreliability. Reliability can be an objective, performance-based measure, but what is most important for passengers making a decision about how to travel is the subjective perception of reliability . Users do not typically consider the reported statistical performance of a roadway when making a trip; they rely on their personal recollection of typical circumstance or from reputation and other subjective information sources. Therefore, it is in the best interest of transit planners to consider passenger perceptions of the travel experience and, to the extent possible, plan to mitigate factors of unreliability.
Activity-based models are based on the principle that travel demand is derived from people's daily activity patterns. Activity-based models predict which activities are conducted when, where, for how long, for and with whom, and the travel choices they will make to complete them. Having this type of detailed model at their disposal allows researchers, practitioners, and policy makers to evaluate the effect of alternative policies on individuals travel behavior at a high level of temporal and spatial resolution and select the best policy alternative considering a potential wide range of performance indicators. For a comprehensive introductory overview of this paradigm, consider reading the Activity Based Modeling Primer published under SHRP2 in 2014.