Multi-agent simulation of adoption of alternative fuels

We have formalized and parameterized a model for the production of six transport fuels and six fuels blends from six feedstocks through 13 different production chains, and their adoption of by 11 distinct subpopulations of motorists. The motorists are represented by agents that use heuristics to choose a fuel on the basis of three attributes and a social feedback loop. Adoption of specific fuels is mostly driven by price differences, but other factors play a role if prices are similar. The results are not always intuitive and do not always show up immediately. We find that sustained combinations of interventions are required to bring about a transition away from petrol or diesel. Adoption of alternative fuels was most often confined to niche markets with a share of 5% or lower. Only in a single case was a complete fuel transition observed.     

Exploratory analysis of Zipf’s universal power law in activity schedules

People’s behavior is governed by extremely complex, multidimensional processes. This fact is well-established in the transportation research community, which has been working on travel behavior (travel demand) models for many years. The number of degrees of freedom in a person’s activity schedule is enormous. However, the frequency of occurrence of day-long activity schedules obeys a remarkably simple, scale-free distribution. This particular distribution has been observed in many natural and social processes and is commonly referred to as Zipf’s law, a power law distribution. This research provides evidence that activity schedules from various study areas exhibit a universal power law distribution. To this end, an elaborate analysis using 13 household travel surveys from diverse study areas discusses the effect of proportional outlier removal on the power law’s exponent value. Statistical evidence is provided for the hypothesis that activity schedules in all these datasets exhibit a power law distribution with a common exponent value. The study proposes that a Zipf power law could be used as an additional dimension within a travel demand model’s validation process. Contrary to other validation methods, no new data is required. The observation of a Zipf power law distribution in the generated schedules appears to be a necessary condition. Additionally, the universal activity schedule distribution might enable the full integration of activity schedules in models based on universal mobility patterns.

     

Cumulative impacts of road developments in floodplains

This paper investigates the impact of differing road development strategies in floodplains for increasing levels of road expansion, focusing on hydraulic characteristics of floods such as water level, velocity and inundation duration and extent. Cumulative impacts are presented in term of both a resistant approach where road transport infrastructure has the secondary purpose of flood dykes and, a resilience approach that maintains the floodplain hydraulics through the use of flow through structures. Each method is examined in the context of road development in the Cambodian Mekong floodplain. Results indicate that resistance approaches necessitate higher levels of road structures, designed to higher technical specifications, whilst resilience approaches maintain the hydraulic character of floodplains but require the inclusion of well-designed flow through structures with localized scour protection.