Miguel Figliozzi

Vehicle Routing Problem for Emissions Minimization

Environmental, social, and political pressures to limit the effects associated with greenhouse gas emissions are mounting. Little research has been done on reducing emissions as the primary objective of a routing problem despite the growth in use and impact of commercial vehicles. In the capacitated vehicle routing problem (VRP) with time windows, it is traditionally assumed that carriers minimize the number of vehicles as a primary objective and distance traveled as a secondary objective without violating time windows, route durations, or capacity constraints. New research focuses on a different problem: the minimization of emissions and fuel consumption as the primary or secondary objective. This creates the emissions VRP (EVRP). A formulation and solution approaches for the EVRP are presented. Decision variables and properties are stated and discussed. Results obtained with a proposed EVRP solution approach for different levels of congestion are compared and analyzed.

Potential Impacts of Climate Change on Flood-Induced Travel Disruptions: A Case Study of Portland, Oregon, USA

This study investigated potential impacts of climate change on travel disruption resulting from road closures in two urban watersheds in the Portland, Oregon, metropolitan area. We used ensemble climate change scenarios, a hydrologic model, a stream channel survey, a hydraulic model, and a travel forecast model to develop an integrated impact assessment method. High-resolution climate change scenarios are based on the combinations of two emission scenarios and eight general circulation models. The Precipitation-Runoff Modeling System was calibrated and validated for the historical period of 1988 and 2006 and simulated for determining the probability of floods for 2020 through 2049. We surveyed stream cross-sections at five road crossings for stream channel geometry and determined flood water surface elevations using the Hydrologic Engineering Centers River Analysis System (HEC-RAS) model. Four of the surveyed bridges and roadways were lower in elevation than the current 100-year flood water surface elevation, leading to relatively frequent nuisance flooding. These roadway flooding events will become more frequent under some climate change scenarios in the future, but climate change impacts will depend on local geomorphic conditions. Whereas vehicle miles traveled was not significantly affected by road closure, vehicle hours delay demonstrated a greater impact from road closures, increasing by 10 percent in the Fanno Creek area. Our research demonstrated the usefulness of the integration of top-down and bottom-up approaches in climate change impact assessment and the need for spatially explicit modeling and participatory planning in flood management and transportation planning under increasing climate uncertainty.

Planning Approximations to the Average Length of Vehicle Routing Problems with Varying Customer Demands and Routing Constraints

This paper studies approximations to the average length of vehicle routing problems (VRPs). The approximations are valuable for strategic and planning analysis of transportation and logistics problems. The focus is on VRPs with varying numbers of customers, demands, and locations. This modeling environment can be used in transport and logistics models that deal with a distribution center serving an area with daily variations in demand. The routes are calculated daily on the basis of what freight is available. New approximations and experimental settings are introduced. Average distance traveled is estimated as a function of the number of customers served and the number of routes needed. Approximations are tested in instances with different customer spatial distributions, demand levels, numbers of customers, and time windows. Regression results indicate that the proposed approximations can reasonably predict the average length of VRPs in randomly generated problems and real urban networks.

Collecting Commercial Vehicle Tour Data with Passive Global Positioning System Technology: Issues and Potential Applications

The assessment of strategies designed to manage the continued growth in road-based freight and associated externalities has been hampered by a paucity of disaggregate data on commercial vehicle movements. When disaggregated data are available, the analysis of commercial vehicle route and trip chain structure can provide insightful information about urban commercial vehicle tours, travel patterns, and congestion levels. Over the past 15 years, the ability to collect detailed travel information has been expanded by developments in global positioning system (GPS) technology. In mid-2006, a GPS survey of commercial vehicles was piloted in Melbourne, Australia, to support a major update of freight data and modeling capabilities in the metropolitan region. The survey used passive GPS methods in which the truck drivers involvement in the data collection effort was minimal. The contributions of this research to the field of urban freight data collection were fourfold: (a) describing implementation issues with the data collection, (b) detailing the algorithms used to process the raw GPS data into meaningful travel and trip information, (c) presenting a discussion of pilot survey data tour results, and (d) discussing potential uses and limitations of GPS technology in urban freight modeling and planning. Despite processing challenges, GPS provides an appealing method to enrich commercial vehicle data collection and enhance our understanding of on-road behavior. Because increasing numbers of commercial vehicles become equipped with GPS receivers, only privacy concerns remain as a major barrier to gathering and using such data on a widespread basis in the future.

Modeling Impact of Technological Changes on Urban Commercial Trips by Commercial Activity Routing Type

Several noteworthy developments in logistics practice have taken place without an equivalent and comprehensive development in urban freight transportation modeling. Part of the problem is the lack of deep understanding of the workings of distribution processes in relation to the generation of truck traffic. This study emphasizes the role and importance that distribution network size and information and communications technology have on the truck traffic flows that materialize as the supply chain flows over the public infrastructure. A concept is developed of commercial activity routing types that characterize the interplay between transportation demand requests and routing characteristics. This research contributes to the field by proposing a novel and detailed characterization of truck flows in a supply chain context. With well-known, yet simple, models and formulas from vehicle routing, operations research, and management science literature, behavioral insights are derived about distributors’ and carriers’ routing and order-sizing decisions, since routing constraints and second-order effects are important drivers of truck flows. The main contribution is to bring a new commercial activity-routing perspective and a deeper level of operational decision-making analysis to cope with the intricacies of freight transportation modeling.

Impact of Bicycle Lane Characteristics on Exposure of Bicyclists to Traffic-Related Particulate Matter

Bicycling as a mode of transportation is increasingly seen as a healthy alternative to motorized transportation modes. However, in congested urban areas, the health benefits of bicycling can be diminished by the negative health effects associated with inhalation of particulate matter. Particles of small size (ultrafine particles <0.1 μm) are the most harmful, even during short-duration exposure. Because vehicular exhaust is the major source of ultrafine particles, the impact of traffic levels and bicycle lane characteristics on exposure of bicyclists was studied. Ultrafine particle exposure concentrations were compared in two settings: (a) a traditional bicycle lane adjacent to the vehicular traffic lanes and (b) a cycle track design with a parking lane separating bicyclists from vehicular traffic lanes. Traffic measurements were made alongside air quality measurements. The cycle track design mitigated ultrafine particle exposure concentrations for cyclists. Results showed statistically significant differences in terms of exposure levels for the two bike facilities, as well as correlations between traffic levels and exposure level differences. Results also suggested that ultrafine particle levels and spatial distribution were sensitive to proximity to signalized intersections. Findings of this research indicated that, in high traffic areas, bicycle facility design had the potential to lower air pollution exposure levels of bicyclists.

Analysis and evaluation of incentive compatible dynamic mechanisms for carrier collaboration

This paper introduces a framework for carrier dynamic collaboration. In particular it proposes and analyzes dynamic collaborative mechanisms that are incentive compatible. The dynamic collaborative environment is characterized by a set of carriers that have a proprietary set of customers that generate a stream of random demands over time. The proposed collaborative mechanism is such that on each demand arrival each carrier has the incentive to submit the arrived shipment or service request to the collaborative mechanism. Intuition about the efficiency and the workings of the collaborative mechanism is developed. A general framework to formulate and study collaborative frameworks among transportation carriers is proposed. A truckload pickup-and-delivery collaborative environment is simulated, and results are analyzed.

Methodology to Characterize Ideal Short-Term Counting Conditions and Improve AADT Estimation Accuracy Using a Regression-Based Correcting Function

Transportation agencies’ motor vehicle count programs tend to be well established and robust with clear guidelines to collect short-term count data, to analyze data, develop annual average daily traffic (AADT) adjustment factors, and to estimate AADT volumes. In contrast, bicycle and pedestrian traffic monitoring is an area of work for most transportation agencies. In most agencies, there are a low numbers of counting sites and limited agency experience to manage a city-wide or state-wide system of collecting, processing, and using nonmotorized data. Short duration counts are used to estimate longer duration volumes such as AADT. Because bicycle or pedestrian short-term counts vary dramatically over time and significantly more than motorized vehicle counts, the direct application of motorized vehicle AADT estimation methods may be inadequate. The goal of this paper is to present a methodology that will enhance, if needed, existing AADT estimation methods widely employed for motorized vehicle counts. The proposed methodology is based on the analysis of AADT estimation errors using regression models to estimate a correcting function that accounts for weather and activity factors. The methodology can be applied to any type of traffic with high volume variability but in this research is applied to a permanent bicycle counting station in Portland, Oregon. The results indicate that the proposed methodology is simple and useful for finding ideal short-term counting conditions and improving AADT estimation accuracy.

Economic and Environmental Optimization of Vehicle Fleets: Impact of Policy, Market, Utilization, and Technological Factors

This paper focuses on the economic and environmental optimization of decisions about vehicle replacement from a fleet managers perspective. An integer programming vehicle replacement model is used to evaluate environmental and policy issues such as greenhouse gas (GHG) taxes and fiscal incentives for purchasing electric vehicles (EVs). This research also analyzes the impacts of utilization (mileage per year per vehicle) and gasoline prices on vehicle-purchasing decisions. Energy and emissions reductions for a variety of scenarios using real-world data in the United States are presented as well as break-even points at which EVs are competitive. Findings include the following: (a) fuel-efficient vehicles such as hybrids and EVs are purchased only in scenarios with high gasoline prices or high utilization, (b) current European carbon dioxide cap-and-trade emissions price (around

A Survey of China’s Logistics Industry and the Impacts of Transport Delays on Importers and Exporters

18.70/ton) does not significantly alter fleet management decisions, and (c) incentives for using EVs (i.e., tax credits) increase the rate of purchase of hybrid and electric vehicles in scenarios with high gasoline prices and high vehicle utilization. This research indicates that the proposed model can be used effectively to inform environmental and fiscal policies on vehicle regulations, tax incentives, and GHG emissions.