Modelling energy consumption of electric freight vehicles in urban pickup/delivery operations: analysis and estimation on a real-world dataset

Electric Freight Vehicles (EFVs) are a promising and increasingly popular alternative to conventional trucks in urban pickup/delivery operations. A key concerned research topic is to develop trip-based Tank-to-Wheel (TTW) analyses/models for EFVs energy consumption: notably, there are just a few studies in this area. Leveraging an earlier research on passenger electric vehicles, this paper aims at filling this gap by proposing a microscopic backward highly-resolved power-based EFVs energy consumption model (EFVs-ECM). The model is estimated and validated against real-world data, collected on a fleet of five EFVs in the city centre of Rome, for a total of 144 observed trips between subsequent pickup/delivery stops. Different model specifications are tested and contrasted, with promising results, in line with previous findings on electric passenger vehicles.     

Reducing the energy consumption of heavy goods vehicles through the application of lightweight trailers: Fleet case studies

Reducing the empty weight of articulated heavy goods vehicle trailers is one avenue that needs to be explored in reducing the carbon footprint of the road freight industry as a whole. A statistical analysis of two heavy goods vehicle fleets operating in the United Kingdom has helped to identify double-deck trailers used in grocery haulage and ‘walking-floor’ trailers used in bulk haulage as two examples of trailers that can benefit significantly from lightweighting. Energy consumption of numerous articulated heavy goods vehicles is quantified through an idealised drive cycle analysis reflecting a long haul journey over a highway. This energy analysis allows for a mass energy performance index to be established. The analysis has shown that reducing the empty weight of trailers by 30% can cause reductions of up to 18% and 11% in mass energy performance index for double-deck trailers and ‘walking-floor’ trailers respectively. Using this approach, trailers that will benefit the most from weight reduction can be identified systematically, allowing for lightweighting strategies to be implemented more effectively. Strategies to reduce empty trailer weight and improve vehicle utilisation are also discussed.     

The impact of urban form on automobile travel: disentangling causation from correlation

A longstanding question within the field of transportation demand management is the strength of the relationship between urban form and mobility behavior. Although several studies have identified a strong correlation between these variables, there is as yet scant evidence to support policy interventions that target land use as a means of influencing travel. To the contrary, some of the more recent research has cast skepticism on the proposition that the relationship is causative, recognizing the possibility that households endogenously self-select themselves into communities that support their preferences for particular transportation modes. Focusing on individual automobile travel, the present study seeks to contribute to this line of inquiry by estimating econometric models on a panel of travel-diary data collected in Germany between 1996 and 2003. Specifically, we employ the two-part model (2PM)—a procedure involving probit and OLS estimators—to assess the determinants of the discrete decision to use the car and the continuous decision of distance traveled. Beyond modeling variables that capture the urban form features that are commonly suggested to influence mobility behavior, including mixed use and public transit, this study employs instrumental variables to control for potential endogeneity emerging from the simultaneity of residential and mode choices. Unlike much of the work to date, our results suggest that urban form has a causative impact on car use, a finding that is robust to alternative econometric specifications.

The impact of transit station areas on the travel behaviors of workers in Denver,Colorado

Transit development is one planning strategy that seeks to partially overcome limitations of low-density single use car oriented development styles. While many studies focus on how residential proximity to transit influences the travel behaviors of individuals, the effect of workplace proximity to transit is less understood. This paper asks, does working near a light rail transit station influence the travel behaviors of workers differently than workers living near a station? We begin by examining workers’ commute mode based on their residential and workplace proximity to transit station areas. Next, we analyze the ways in which personal travel behaviors differ between those who drive to work and those who do not. The data came from a 2009 travel behavior survey in the Denver, Colorado metropolitan area, which contains 8000 households, 16,000 individuals, and nearly 80,000 trips. We measure sustainable travel behaviors as reduced mileage, reduced number of trips, and increased use of non-car transportation. The results of this study indicate that living near a transit station area by itself does not increase the likelihood of using non-car modes for work commutes. But if the destination (work) is near a transit station area, persons are less likely to drive a car to work. People who both live and work in a transit station area are less likely to use a car and more likely to take non-car modes for both work and non-work (personal) trips. Especially for persons who work near a transit station area, the measures of personal trips and distances show a higher level of mobility for non-car commuters than car commuters – that is, more trips and more distant trips. The use of non-car modes for personal trips is most likely to occur by non-car commuters, regardless of their transit station area relationship.     

Transportation of dangerous goods by road: the Brazilian case for selection of carriers based on a risk management methodology

Abstract

This article applies a methodology for selecting carriers for the transportation of dangerous goods by road, with a special focus on risk management aspects. The methodology makes use of Stated Preference techniques and verifies the most critical risk-related variables influencing decision-making from the shippers' point of view. It embraces the planning and execution stages, an evaluation of the contracted company and a feedback process. The methodology was effectively applied to the case of liquid fuel shippers in the Brazilian middle-west region where it proved possible to identify which dangerous goods road transport company to contract in accordance with the risk management factors selected by the decision makers.     

The impact of road traffic noise on urban protected areas: A landscape modeling approach

We modeled the propagation of traffic noise over the landscape and analyzed its impact on the structure and configuration of protected areas of the Twin Cities Metro Region, Minnesota. Using four noise thresholds, we found that at low and medium noise levels, 19% and 11% of the protected areas are within the road-effect zone. Using mean patch area and patch shape index, we measured the acoustic fragmentation of habitats. We found that at higher levels of noise patch shape index increased, while mean patch size decreased. The acoustic diversity of a patch is also found to be correlated with land cover type, patch area, and patch shape.     

The role of light duty vehicles in future air pollution: a case study of Sacramento

Abstract

On-road light-duty vehicles (LDVs) play an important role in contributing to urban air pollution. Although vehicles are getting cleaner, regional growth in vehicle population and vehicle miles traveled would somewhat offset California's efforts in transportation pollution reduction. To better understand the role of LDVs in future air pollution, we conduct a case study for Sacramento, California, and investigate future trends in urban air pollution attributable to the light-duty fleet. Results indicate that ambient concentrations of CO, NO _x , and total organic gases (TOGs) caused by future light-duty fleets would dramatically decrease over coming years. The resulting concentrations in 2030 might be as low as approximately 20% of the 2005 concentrations. These reflect the improvements in vehicle/fuel technologies and standards in California. However, the future particulate matter (PM₁₀) pollution could be slightly worse than that caused by the 2005 fleet. This is a result of the growing fleet-average emission factors of particulates from 2005 to 2030. For purposes of future particulate control, more attention needs to be paid to LDVs, besides heavy-duty vehicles.     

Analysis of the effect of charging needs on battery electric vehicle drivers’ route choice behaviour: A case study in the Netherlands

Electric travelling appears to dominate the transport sector in the near future due to the needed transition from internal combustion vehicles (ICV) towards Electric Vehicles (EV) to tackle urban pollution. Given this trend, investigation of the EV drivers’ travel behaviour is of great importance to stakeholders including planners and policymakers, for example in order to locate charging stations. This research explores the Battery Electric Vehicle (BEV) drivers route choice and charging preferences through a Stated Preference (SP) survey. Collecting data from 505 EV drivers in the Netherlands, we report the results of estimating a Mixed Logit (ML) model for those choices. Respondents were requested to choose a route among six alternatives: freeways, arterial ways, and local streets with and without fast charging. Our findings suggest that the classic route attributes (travel time and travel cost), vehicle-related variables (state-of-charge at the origin and destination) and charging characteristics (availability of a slow charging point at the destination, fast charging duration, waiting time in the queue of a fast-charging station) can influence the BEV drivers route choice and charging behaviour significantly. When the state-of-charge (SOC) at the origin is high and a slow charger at the destination is available, routes without fast charging are likely to be preferred. Moreover, local streets (associated with slow speeds and less energy consumption) could be preferred if the SOC at the destination is expected to be low while arterial ways might be selected when a driver must recharge his/her car during the trip via fast charging.     

Experimental study of the impact of structural geometry and wind direction on vehicle emissions in urban environment

Vehicle emissions inside an urban environment are investigated using a wind-tunnel under neutral atmospheric conditions. The urban environment was formed as street canyon model. The diffusion flow field in the boundary layer inside the street canyon was examined at different locations of varying geometry of the street and wind directions in the downwind distance of the leeward side of the street canyon model. The results show that the vertical velocity increases as the aspect ratio increases and with wind direction increases from θ = 90°. The pollutant concentration increases as the aspect ratio decreases. The pollutant concentration decreases as the wind direction increases from θ = 90°. The pollutant concentration distributions indicate that the variability of the structure, geometry and wind direction inside the street canyon are important parameters for estimating air quality in the urban street canyon.     

Assessing the impact of long-term mobility choice motivation and short-term mobility means connotation on the use intention of electric cars in rural areas

In this study several hypotheses comprising a heuristic framework derived from rational-choice (RC) premises and regarding some potentially influencing variables on future use intention of different vehicle types are tested with a rural area sample. Especially the differentiation between long-term vs. short-term as well as functional/rational vs. extra-functional/emotional motivators is assessed. Results suggest a predominance of functional motivators and rational connotations over extra-functional/emotional ones. The models to check whether short-term or long-term effects dominate did not clearly confirm a predominance of long-term factors as hypothesized. In several regression models a moderating effect of rational short-term connotations on different long-term motivators was found, thus contributing notably to the prediction of future vehicle use-intention. The need for further research and theory-driven modeling is briefly discussed.     

The effect of attitudes on reference-dependent preferences: Estimation and validation for the case of alternative-fuel vehicles

Several recent studies in transportation have analysed how choices made by individuals are influenced by attitudes. Other studies have contributed to our understanding of apparently non-rational behaviour by examining how choices may reflect reference-dependent preferences. This paper examines how reference-dependent preferences and attitudes together may explain individual choices. In a modelling framework based on a hybrid choice model allowing for both concepts, we investigate how attitudes and reference-dependent preferences interact and how they affect willingness-to-pay measures and demand elasticities. Using a data set with stated choices among alternative-fuel vehicles, we see that allowing for reference-dependent preferences improves our ability to explain the stated choices in the data and that the attitude (appreciation of car features) explains part of the preference heterogeneity across individuals. The results indicate that individuals have reference-dependent preferences that could be explained by loss aversion and that these are indeed related to an individual’s attitude towards car features. The models are validated using a large hold-out sample. This shows that the inclusion of attitudes improves the models’ ability to explain behaviour in the hold-out sample. While neither reference-dependent preferences nor the attitude affect the average willingness-to-pay measures in our sample, their effect on choice behaviour has implications for policy recommendations as segments with varying attitudes and reference values will act differently when affected by policy instruments related to the demand for alternative-fuel vehicles, e.g. subsidies.     

The impact of a congestion pricing exemption on the demand for new energy efficient vehicles in Stockholm

As governments seek to transition to more efficient vehicle fleets, one strategy has been to incentivize ‘green’ vehicle choice by exempting some of these vehicles from road user charges. As an example, to stimulate sales of energy efficient vehicles (EEVs) in Sweden, some of these automobiles were exempted from Stockholm’s congestion tax. In this paper the effect this policy had on the demand for new, privately-owned, exempt EEVs is assessed by first estimating a model of vehicle choice and then by applying this model to simulate vehicle alternative market shares under different policy scenarios. The database used to calibrate the model includes owner-specific demographics merged with vehicle registry data for all new private vehicles registered in Stockholm County during 2008. Characteristics of individuals with a higher propensity to purchase an exempt EEV were identified. The most significant factors included intra-cordon residency (positive), distance from home to the CBD (negative), and commuting across the cordon (positive). By calculating vehicle shares from the vehicle choice model and then comparing these estimates to a simulated scenario where the congestion tax exemption was inactive, the exemption was estimated to have substantially increased the share of newly purchased, private, exempt EEVs in Stockholm by 1.8% (±0.3%; 95% C.I.) to a total share of 18.8%. This amounts to an estimated 10.7% increase in private, exempt EEV purchases during 2008, i.e., 519 privately owned, exempt EEVs.     

The net effects of the built environment on household vehicle emissions: A case study of Austin,TX

Growing concerns over climate change have led to an increasing interest in the role of the built environment to reduce transportation greenhouse gas (GHG) emissions. Many studies have reported that compact, mixed-use, and well-connected developments reduce vehicle miles traveled (VMT). Others, however, argue that densification and mixture of land uses can slow down vehicle movements, and consequently generate more driving emissions. Methodologically, VMT is only a proxy, not an exact measure of emissions. This study quantifies the net effects of the built environment on household vehicle emissions through a case study of Austin, TX. The study employed structural equation modeling (SEM) techniques and estimated path models to improve understanding of the relationship between the built environment and vehicle emissions. The results show a rather complex picture of the relationship. Densification can reduce regional vehicle emissions despite its secondary effect of reduced vehicle travel speed. A 1% increase in density was found to reduce household vehicle emissions by 0.1%. However, intensification of the design feature of the built environment in developed areas may work in the opposite direction; the modeling results showed a 1% increase in grid-like network being associated with 0.8% increase in household vehicle emissions. Based on the results, the study addressed the potential of and the challenges to reducing vehicle emissions through modifying the built environment in local areas.     

Understanding the role of the forecast-maker in overestimation forecasts of policy impacts: The case of Travel Demand Management policies

Forecasting the impacts of a proposed policy is an important component of the transportation planning and decision making process. Although scientific tools are often used in transportation forecasts, biases and, more specifically, overestimations of the expected impact are often observed. This study explores the correlations between forecast-maker’s characteristics and forecast bias creation and reduction. The study examines two transport-related policies aiming at the reduction of car use: telecommuting and carsharing. Both are Travel Demand Management (TDM) policies, which attract much attention from transport experts. We tested the extent to which the forecast-maker’s beliefs about the policy at stake affected the forecast bias. We found that attitudes and beliefs associates not only with overestimation bias but also with its reduction over time. We also tested the extent to which the forecast-maker’s affiliation, the performing institute and the publication type were correlated with the biases of the forecast and with the forecaster attitudes and beliefs. These characteristics are intuitively used by the forecast user as tools to assess the ‘objectivity’ of the forecast, but our analysis found no association between these characteristics and the forecast bias.     

The impact of transport pricing policy on individual energy consumption: a modeling case study in Kumamoto

To investigate the impact of traffic pricing policies on energy consumption, this study shows a microeconomic quantitative analysis scheme to simulate individual consumption behaviors from a microeconomic viewpoint. Energy consumption is estimated based on individual demand of non‐mobility goods and mobility goods under nine policy scenarios based on strategies of gasoline tax adding and mass transit fare reduction independently or combined. Results show that gasoline tax adding has strong effects on consumption behaviors. Energy consumption reduces mostly because of less consumption of non‐mobility goods and car trips. However, policy of mass transit fare reduction has limited impact on energy saving because consumption of non‐mobility goods and mass transit trips increases, but the number of car trips decline by only a small percentage. Comparing with single‐type policy, policies that combined gasoline tax adding and mass transit fare reduction show less energy consumption. Findings suggest that policies that increase cost of car trips, such as gasoline tax adding, are very helpful to reduce the consumption of non‐mobility goods and car trips, which contribute to less energy consumption. However, reducing cost of mass transit trips suggests limited effect on energy saving. Copyright © 2015 John Wiley & Sons, Ltd.     

The impact of transportation demand management policies on commuting to college facilities: A case study at the University of Trieste,Italy

Universities, like other types of public and private institutions, when located in a city, have both positive and negative impacts on the area where they are situated. On the one hand, they contribute to the prestige of the area; on the other hand, they are large generators/attractors of traffic. The ability to successfully balance the pros and cons of the urban location of these large traffic-generating institutions is crucial for their success and for the livability of the city. In this paper this issue has been analyzed selecting as a representative case the University of Trieste.The aim of the research is to understand: (a) how mode choice decisions are made by the teaching and administrative staff and by the students at the various locations where academic activities take place, and (b) how they would be affected by 8 different transport management policies. It is found that changing the parking regulations (via the annual permit cost, the hourly parking fee, the number of parking spaces and the location of the parking lots) greatly influences mode choice in favor of bus use, especially for teaching and administrative staff and in the suburban locations. The students would be impacted by such changes only if an hourly parking tariff is introduced. The alternative approach of fully subsidizing the bus services would also have a large impact on bus ridership, affecting the mode choice in particular of the teaching staff and in the main university suburban sites.Since the implementation of these bus-favoring policies could face the opposition either of the university staff or of the bus company, two more balanced policy mixes were tested: the first one, increasing parking price and imposing new parking restrictions, would increase bus ridership by 19%; the second one, reducing both bus and parking subsidies, would increase bus ridership by 13%.     

The limits of partial life cycle assessment studies in road construction practices: A case study on the use of hydrated lime in Hot Mix Asphalt

Extensive published literature shows that hydrated lime improves Hot Mix Asphalt (HMA) durability. Its impact on the environmental impact of HMA has not been investigated. This paper presents a comparative Life Cycle Assessment (LCA) for the use of HMA without hydrated lime (classical HMA) and with hydrated lime (modified HMA) for the lifetime of a highway. System boundaries cover the life cycle from cradle-to-grave, meaning extraction of raw materials to end of life of the road. The main assumptions were: 1. Lifetime of the road 50 years; 2. Classical HMA with a life span of 10 years, maintenance operations every 10 years; 3. Modified HMA with an increase in the life span by 25%, maintenance operations every 12.5 years. For the lifetime of the road, modified HMA has the lowest environmental footprint compared to classical HMA with the following benefits: 43% less primary total energy consumption resulting in 23% lower emissions of greenhouse gases. Partial LCAs focusing only on the construction and/or maintenance phase should be used with caution since they could lead to wrong decisions if the durability and the maintenance scenarios differ. Sustainable construction technologies should not only consider environmental impact as quantified by LCA, but also economic and social impacts as well. Avoiding maintenance steps means less road works, fewer traffic jams and hence less CO₂ emissions.