Abstract
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 language | English |
|---|---|
| Pages (from-to) | 89-101 |
| Number of pages | 13 |
| Journal | Computers and Operations Research |
| Volume | 100 |
| DOIs | |
| Publication status | Published - Dec 2018 |
Funding
The authors gratefully acknowledge funding provided by the Southampton Business School and by the Canadian Natural Sciences and Engineering Research Council under grants 2015–06189 and 436014–2013. Thanks are due to the referees for their valuable comments.
Keywords
- Autonomous trucks
- Green VRP
- Speed optimization
- Stochastic programming
ASJC Scopus subject areas
- General Computer Science
- Modelling and Simulation
- Management Science and Operations Research