Route and speed optimization for autonomous trucks

Moncef Ilies Nasri, Tolga Bektaş, Gilbert Laporte

Research output: Contribution to journalArticlepeer-review

34 Citations (SciVal)


Autonomous vehicles, and in particular autonomous trucks (ATs), are an emerging technology that is becoming a reality in the transportation sector. This paper addresses the problem of optimizing the routes and the speeds of ATs making deliveries under uncertain traffic conditions. The aim is to reduce the cost of emissions, fuel consumption and travel times. The traffic conditions are represented by a discrete set of scenarios, using which the problem is modeled in the form of two-stage stochastic programming formulations using two different recourse strategies. The strategies differ in the amount of information available during the decision making process. Computational results show the added value of stochastic modeling over a deterministic approach and the quantified benefits of optimizing speed.

Original languageEnglish
Pages (from-to)89-101
Number of pages13
JournalComputers and Operations Research
Publication statusPublished - Dec 2018


  • Autonomous trucks
  • Green VRP
  • Speed optimization
  • Stochastic programming

ASJC Scopus subject areas

  • Computer Science(all)
  • Modelling and Simulation
  • Management Science and Operations Research


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