Transportation: Difference between revisions

[[File:Transport.png|thumb|A schematic of selected opportunities to reduce greenhouse emissions from transportation using machine learning. From "Tackling Climate Change with Machine Learning."<ref name=":0">{{Cite journal|last=Rolnick|first=David|last2=Donti|first2=Priya L.|last3=Kaack|first3=Lynn H.|last4=Kochanski|first4=Kelly|last5=Lacoste|first5=Alexandre|last6=Sankaran|first6=Kris|last7=Ross|first7=Andrew Slavin|last8=Milojevic-Dupont|first8=Nikola|last9=Jaques|first9=Natasha|last10=Waldman-Brown|first10=Anna|last11=Luccioni|first11=Alexandra|date=2019-11-05|title=Tackling Climate Change with Machine Learning|url=http://arxiv.org/abs/1906.05433|journal=|volume=|pages=|via=arXiv:1906.05433 [cs, stat]}}</ref>]]

Transportation systems form a complex web that is fundamental to an active and prosperous society. Globally, the transportation sector accounts for about a quarter of energy-related CO2CO₂ emissions.<ref>IPCC. ''Global warming of 1.5°C. An IPCC special report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty'' [V. Masson-Delmotte, P. Zhai, H. O. Portner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, Y. Chen, S. Connors, ¨ M. Gomis, E. Lonnoy, J. B. R. Matthews, W. Moufouma-Okia, C. Pean, R. Pidcock, N. Reay, M. Tignor, T. ´ Waterfield, X. Zhou (eds.)]. 2018.</ref> In contrast to the electricity sector, however, transportation has not made significant progress to lower its CO2CO₂ emissions<ref>{{Cite journal|last=Creutzig|first=F.|last2=Jochem|first2=P.|last3=Edelenbosch|first3=O. Y.|last4=Mattauch|first4=L.|last5=Vuuren|first5=D. P. v.|last6=McCollum|first6=D.|last7=Minx|first7=J.|date=2015-11-19|title=Transport: A roadblock to climate change mitigation?|url=http://dx.doi.org/10.1126/science.aac8033|journal=Science|volume=350|issue=6263|pages=911–912|doi=10.1126/science.aac8033|issn=0036-8075}}</ref> and much of the sector is regarded as hard to decarbonize.<ref>{{Cite journal|last=Davis|first=Steven J.|last2=Lewis|first2=Nathan S.|last3=Shaner|first3=Matthew|last4=Aggarwal|first4=Sonia|last5=Arent|first5=Doug|last6=Azevedo|first6=Inês L.|last7=Benson|first7=Sally M.|last8=Bradley|first8=Thomas|last9=Brouwer|first9=Jack|last10=Chiang|first10=Yet-Ming|last11=Clack|first11=Christopher T. M.|date=2018-06-28|title=Net-zero emissions energy systems|url=http://dx.doi.org/10.1126/science.aas9793|journal=Science|volume=360|issue=6396|pages=eaas9793|doi=10.1126/science.aas9793|issn=0036-8075}}</ref> This is because of the high energy density of fuels required for many types of vehicles, which constrains low-carbon alternatives, and because transport policies directly impact end-users and are thus more likely to be controversial.

Passenger and freight transportation are each responsible for about half of transport GHG emissions.<ref name=":1">R. Schaeffer, R. Sims, J. Corfee-Morlot, F. Creutzig, X. Cruz-Nunez, D. Dimitriu, and M. et al. D’Agosto. ''Transport, in IPCC, Working Group III contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Climate Change 2014: Mitigation of Climate Change, chapter 8.'' Geneva [O. Edenhofer, R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlomer, C. von Stechow, T. Zwickel, J.C. Minx, (eds.)]. ¨ Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2014.</ref> Both freight and passengers can travel by road, by rail, by water, or by air (referred to as transport modes). Different modes carry vastly different carbon emission intensities. At present, more than two-thirds of transportation emissions are from road travel,<ref name=":1" /> but air travel has the highest emission intensity and is responsible for an increasingly large share. Strategies to reduce GHG emissions from transportation include:<ref name=":1" />

Each of these mitigation strategies offers opportunities for ML. While many of us probably think of autonomous vehicles and ride-sharing when we think of transport and ML, these technologies have uncertain impacts on GHG emissions,<ref>{{Cite journal|last=Wadud|first=Zia|last2=MacKenzie|first2=Don|last3=Leiby|first3=Paul|date=2016-04|title=Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles|url=http://dx.doi.org/10.1016/j.tra.2015.12.001|journal=Transportation Research Part A: Policy and Practice|volume=86|pages=1–18|doi=10.1016/j.tra.2015.12.001|issn=0965-8564}}</ref> potentially even increasing them. In reality, ML can play a role for decarbonizing transportation that goes much further. ML can improve vehicle engineering, enable intelligent infrastructure, and provide policy-relevant information.<ref name=":0" /> Many interventions that reduce GHG emissions in the transportation sector require changes in planning, maintenance, and operations of transportation systems, even though the GHG reduction potential of those measures might not be immediately apparent. ML can help in implementing such interventions, for example by providing better demand forecasts. Typically, ML strategies are most effective in tandem with strong public policies.