Electric freight vehicles (EVs) are a sustainable alternative to conventional internal combustion freight vehicles. The driving autonomy of EVs is a fundamental component in the planning of EV routes for goods distribution. In this respect, a complicating factor lies in the fact that EVs' energy consumption is subject to a great deal of uncertainty, which is due to a number of endogenous and exogenous factors. Ignoring such uncertainties in the planning of EV routes may lead a vehicle to run out of energy, which -given the scarcity of recharging stations- may have dire effects. Thus, to foster a widespread use of EVs, we need to adopt new routing strategies that explicitly account for energy consumption uncertainty. In this paper, we propose a new two-stage stochastic programming formulation for the single electric vehicle routing problem with stochastic energy consumption. Furthermore, we develop a decomposition algorithm for this problem. We provide an illustrative example showing the added value of incorporating uncertainty in the route planning process. We perform a variety of computational experiments and show that our decomposition algorithm is capable of efficiently solving instances with 20 customers and 30 scenarios.

Public transport systems, being a safe and sustainable mode of transport, can benefit to a great extent from availing Autonomous vehicle (AV)s. However, the advancements in the road transport infrastructure is not at par with advancements in Intelligent Transportation System (ITS) and vehicle technologies. Cities must consider these changes to realize AVs as a public transport mode. In this paper, we propose three bus-bay designs to integrate AVs with public transport to address this issue. We develop a microscopic traffic simulation model to find the effectiveness of these designs with traffic data obtained from local transport authority and field measurements. The designs are simulated in Singapore city and could be adopted to other cities. Results show that an exclusive AV bay which is physically separated from bus bay reduced the travel time of AV by 5%. Queue length, at the signal near bus stop, has decreased by 27% for such a design.