Mapping the Future Transportation Stack

Authors: Luis Alvarez Leon*, Dartmouth College
Topics: Economic Geography, Cyberinfrastructure, Transportation Geography
Keywords: automated vehicles, digital technologies, automobile industry, navigation technologies, self-driving cars
Session Type: Paper
Day: 4/3/2019
Start / End Time: 9:55 AM / 11:35 AM
Room: 8201, Park Tower Suites, Marriott, Lobby Level
Presentation File: No File Uploaded


The rapidly expanding scope and scale characterizing the corporate landscape of autonomous navigation underscore its potentially widespread ramifications, as well as its deep interconnection with larger dynamics of digital informational capitalism, such as data privacy, physical-digital infrastructure, regulatory regimes, and national security, among others. Key to the different components of autonomous navigation is an increased reliance on geospatial data, media, and technologies. In light of this, the present paper takes as a starting point this expanding complex of firms, known as the ‘future transportation stack’, to advance two interrelated objectives. First, it draws a systematic overview of the structure and evolving dynamics of a rapidly transforming sector of the economy. Through the analysis of data from mergers and acquisitions, strategic alliances, firm locational patterns, patent networks, policy documents, lawsuits, and investment flows, this paper provides an economic geographic context of the ‘future transportation stack’. The paper then takes this context to inform an examination of the specific role of geospatial data, media, and technologies in enabling the definition and implementation of the notion of ‘future’ in ‘future transportation stack’— as a marker of qualitative difference from current transportation systems. These two objectives are brought together to show how the geospatial is both a necessary component to imagine, fund, and build (the future of) transportation, and simultaneously undergoing important transformations catalyzed by the drive to fulfill this role.

Abstract Information

This abstract is already part of a session. View the session here.

To access contact information login