TimeMap is a visualization aimed at commuters that maps locations based on the time taken to travel to them from a particular location. It is dynamic and the shape of the map varies in response to changes in traffic and travel options. The currently available web version of TimeMap plots train travel times across Netherlands.
Load TimeMaps from anywhere in the country, and it automatically checks your location, shows the nearest train station, and charts trip times around the country in rings, with each colored ring representing another 30 minutes. Most importantly, the map is live. It grows and shrinks throughout the day, as travel times themselves grow and shrink; the bigger the map, the longer it’ll take you to get around... the map expands at night, when trains run infrequently or not at all, then contracts during the day, when trains run on their regular, zippy schedule. Track delays? The map grows again.
TimeMaps can be useful to generate maps for air and road travel times. One option would be to integrate mobile phone traffic data into the TimeMap application and generate real-time maps of traffic conditions and travel options in any city. Characteristics of the mobile phone data can be used to identify those used by road users and its mobility patterns can give information about road traffic conditions.
Such cognitively salient data visualization can provide excellent decision support for road users and help everyone optimize their travel times and thereby minimize traffic problems. The real-time nature of the information and its availability in the simplest form to its consumers will help them use it optimally and thereby generate the most efficient traffic outcomes.
Such visualization tools become potent traffic force multipliers in cities where commuters have multiple travel options. For example, the presence of good public transit system helps commuters effectively switch across different travel modes and travel routes to make their daily peak-hour travel decisions in a manner that would contribute towards optimizing traffic patterns.