• HubCab will track more than 150 million taxi trips in NYC to gain insight on ride share scenarios
• Insights will inform researchers on how car sharing systems can lower vehicle emissions, reduce congestion, and save money and time
• Scientific study conducted at Massachusetts Institute of Technology’s Senseable City Lab with support of VW Group’s ERL, Audi and GE
HubCab tracks more than 150 million taxi rides in New York City over the course of a year. With this information, researchers can identify commuter travel patterns and work to develop a more efficient car share system. MIT researchers say HubCab technology could not only save people money and time, but allow users to better plan their taxi rides around the city, potentially reducing the number of trips by 40%. HubCab is another step by Audi and the Massachusetts Institute of Technology’s Senseable City Lab to work toward improving transportation efficiency systems that reshape that way people move and live in their daily lives.
“The so called ‘sharing economy’ is blossoming all over the Internet”, said Carlo Ratti, Director of the Senseable City Lab. “Today it is mostly about fixed assets – such as homes on AirBNB. But tomorrow, it will increasingly involve our mobility infrastructure, blurring the difference between public and private transportation.”
“The HubCab project makes visible the immense benefits in New York City’s taxi system that would arise from just sharing a cab,” said Paolo Santi and Michael Szell at the MIT Senseable City Lab. “By engaging citizens in potential sharing economies, HubCab clears the way towards more sustainable urban futures.”
Part of the vision for a more sustainable urban future involves the utilization of Big Data, such as that provided by HubCab. This remains a goal for both the MIT Senseable City Lab and ERL. Project researchers say the HubCab tool embodies one of the most cutting-edge applications of this concept.
“MIT and Audi are interested in solving future mobility challenges, such as the increasing mobility demands that are placed against limited infrastructure capacity,” said Chuhee Lee, deputy director, Electronics Research Laboratory. “By utilizing the Big Data that’s publicly available we can optimize car sharing and other opportunities to reduce this tension.”
Additionally, users can explore 200 thousand street segments in New York over several time segments of the day, which amounts to more than one trillion flow combinations.
HubCab allows users to discover exactly when and where taxis pick up and drop individuals in New York City, which is useful in helping identify specific areas and time of condensed pickup and drop-off activities.
Information generated by the HubCab project also offers potential application to other existing Audi urban mobility initiatives, including Audi Urban Intelligent Assist (AUIA). The project, conducted by Audi, ERL and university research partners, utilizes real time urban data to develop connected car technologies that reduce congestion, improve safety and make urban driving less stressful. This data includes local vehicle and pedestrian information, which could ultimately be sourced from the HubCab project.
The HubCab project team was led by Carlo Ratti, director of the Senseable City Lab at the Massachusetts Institute of Technology, which is sponsored by ERL and General Electric. Ratti is a member of the World Economic Forum’s Global Agenda Council for Urban Management.
HubCab is available at www.hubcab.org.
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