Assessment of Trade-offs Among Urban Delivery Vehicles
C A Torres Cruz, Federal Highways Agency; X Ban, Jose Holguin Veras, Rensselaar Polytechnic Institute, US
The objective of this research is to study and analyze the tradeoffs between single unit trucks and heavy trucks in urban areas.
Effective intermodal corridor management, as its name suggests, must be aimed at ensuring the most economically use of the existing network. However, in order to achieve a quasi or optimal use, transportation agencies must be aware of the economic costs and benefits associated with the traffic of the different vehicle classes.
In the case of commercial freight traffic, there is widespread misconception about the relative economic and environmental impact of single unit trucks vs. heavy trucks. As it is widely known, a heavy truck generates more pollution and congestion than a single unit truck which is an obvious consequence of its larger size. However, what it is not frequently taken into account is that if the amount of cargo to be transported by each truck type is the same, heavy trucks are more efficient than single unit trucks. This leads to a situation in which, although the contribution to congestion and pollution of an individual small truck is smaller than the one for a semi-trailer, their total impact is larger because of the larger number.
The objective of this research is to study and analyze the tradeoffs between single unit trucks and heavy trucks in urban areas. This was accomplished by conducting micro-simulation, statistical modeling, economic valuation and optimization of a real world urban network. Micro simulations captured the tradeoffs of these traffic combinations in terms of levels of pollution, total travel time, and vehicle miles traveled for a typical urban area. Using the data obtained from micro-simulation, externality models were generated to assess the tradeoffs between different vehicle classes. Valuation of the externalities was used to complement the externality models to produce cost models that quantify cost of externalities. Finally, an optimization formulation was developed to find the tradeoffs among different vehicles classes in order to minimize the costs incurred by these vehicles. The analyses provide the basis to compute optimal traffic flows by minimizing cost of externalities (e.g. pollution, congestion and pavement deterioration).
The optimization model indicates that as the payload of a single unit truck is 3/5 of the payload for a heavy truck, then any type of truck will be optimal to use. However if the payload of a single unit truck is larger than 3/5 of the payload for a heavy truck then single unit trucks are optimal, otherwise heavy trucks are the best option to minimize social costs. This study contributes to understanding interactions of pollution, congestion and multimodal traffic in a urban network, which has significant implications for, transportation, energy security and the environment and externalities and pricing of transportation services.
Association for European Transport