Large volumes of data are produced every day in the transportation industry; for instance, data collected using sensors in passenger counting, vehicle location systems, and ticketing and collection systems opens up new opportunities for the transportation industry. Logistics companies can leverage big data tools and predictive analytics to make better decisions, improve operations, reduce costs, and streamline processes. This will eventually help transportation stakeholders and also help serve travelers and customers better.
Legislators around the world have become more proactive toward leveraging the data, but mainly they haven’t legislated anything particularly related to big data. In retrospect, lawmakers have taken the high moral ground by adapting to the implementation of intelligent transport systems, the increased open data policies, automated driving, and smart mobility.
Regardless of the existence of public and private policies, the use of big data creates new ethical and policy challenges that require the adoption of new policies or the replacement of existing ones.
Legislations currently in force in EU and its member states level are not made keeping big data in mind. Changes in legislation tend to be slow because legislative processes tend to be dull, and often seem to end up procrastinating behind technological evolution. As a result, advancements in big data will be confronted with legal hurdles.
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The LeMO Project identified vital legal issues, which are relevant for the changing terrain of the big data, including the transport industry as well. These critical issues include privacy and data protection, (cyber-)security, breach-related obligations, anonymization and pseudonymization, supply of digital content and services (and accurately, personal data as counter-performance), free flow of data, intellectual property in a big data environment, open data, data sharing obligations, data ownership, liability, and competition.
The project has also presented some unique insights on ethical and social fronts which equally apply to the transport industry, ranging from trust, surveillance, privacy (including transparency, consent, and control), free will, and personal data ownership, to data-driven social discrimination and equity, and environmental issues.
In conclusion, new developments in the transport industry that rely on data-driven technologies will raise technical, economic, legal, ethical and social matters which would require reflection and critical evaluation.