This chapter re-examines the general solutions proposed to improve the environmental sustainability of transport discussed in Sect. 1.3.2, with a view to understanding the potential for big data in each of these approaches. How can big data be used to reduce transport energy and emissions in cities? Specifically, how can big data encourage modal shift from cars to more environmentally friendly modes, and reduce vehicular transport overall through better trip planning? The chapter also includes a case study of a ‘personal transport planner’ designed for use in Beijing, based on the idea of a monthly personal transport energy quota.
|Title of host publication||Big Data for Urban Sustainability|
|Publisher||Springer International Publishing AG|
|Publication status||Published - Mar 2018|