Reducing CO<Subscript>2</Subscript> from cars in the European Union

The European Union (EU) recently adopted CO₂ emissions mandates for new passenger cars, requiring steady reductions to 95 gCO₂/km in 2021. We use a multi-sector computable general equilibrium (CGE) model, which includes a private transportation sector with an empirically-based parameterization of the relationship between income growth and demand for vehicle miles traveled. The model also includes representation of fleet turnover, and opportunities for fuel use and emissions abatement, including representation of electric vehicles. We analyze the impact of the mandates on oil demand, CO₂ emissions, and economic welfare, and compare the results to an emission trading scenario that achieves identical emissions reductions. We find that vehicle emission standards reduce CO₂ emissions from transportation by about 50 MtCO₂ and lower the oil expenditures by about €6 billion, but at a net added cost of €12 billion in 2020. Tightening CO₂ standards further after 2021 would cost the EU economy an additional €24–63 billion in 2025, compared with an emission trading system that achieves the same economy-wide CO₂ reduction. We offer a discussion of the design features for incorporating transport into the emission trading system.     

A hazard-based approach to modelling the effects of online shopping on intershopping duration

Despite growing prevalence of online shopping, its impacts on mobility are poorly understood. This partially results from the lack of sufficiently detailed data. In this paper we address this gap using consumer panel data, a new dataset for this context. We analyse one year long longitudinal grocery shopping purchase data from London shoppers to investigate the effects of online shopping on overall shopping activity patterns and personal trips. We characterise the temporal structure of shopping demand by means of the duration between shopping episodes using hazard-based duration models. These models have been used to study inter-shopping spells for traditional shopping in the literature, however effects of online shopping were not considered. Here, we differentiate between shopping events and shopping trips. The former refers to all types of shopping activity including both online and in-store, while the latter is restricted to physical shopping trips. Separate models were estimated for each and results suggest potential substitution effects between online and in-store in the context of grocery shopping. We find that having shopped online since the last shopping trip significantly reduces the likelihood of a physical shopping trip. We do not observe the same effect for inter-event durations. Hence, shopping online does not have a significant effect on overall shopping activity frequency, yet affects shopping trip rates. This is a key finding and suggests potential substitution between online shopping and physical trips to the store. Additional insights on which factors, including basket size and demographics, affect inter-shopping durations are also drawn.     

Resilience and accessibility of Swedish and Dutch municipalities

Recent years have shown a rising popularity of the concept of resilience—both theoretically and empirically—in complex systems analysis. There is also a rising literature on resilience in the transport and spatial-economic field. The pluriform interpretation of resilience (e.g., engineering vs. ecological resilience) is related to methodological differences (e.g., stability in dynamics vs. evolutionary adaptivity). But in all cases the fundamental question is whether a complex system that is subjected to an external shock is able to recover, and if so, to which extent. The present paper [Based on presentation from cluster 6 (Accessibility) of the Nectar 2015 conference in Ann Arbour, USA.] aims to add a new dimension to resilience analysis in spatial systems, by addressing in particular the relationship between spatial accessibility at a municipality level and the resilience outcomes of the spatial system concerned. It does so by investigating to which extent accessibility of Swedish and Dutch municipalities has mitigated the local shock absorption from the recent economic recession. In our study the shock absorption capacity of municipal accessibility is estimated by analysing the relevant resilience indicators for the period concerned. In this context, conventional resilience indicators based on either multivariate complex data (in particular, the Foster Resilience Capacity Index) or employment data (in particular, the Martin Resilience-Employment Index) are confronted with spatial connectivity data based on local accessibility measures, so that geographical mobility may be regarded as one of the shock-mitigating factors. The empirical analysis is carried out for two countries which have both proven to be rather shock-resistant during the recent economic crisis, viz. Sweden and The Netherlands. Clearly, the geographical structure of these countries forms a sharp mutual contrast, viz. a spatially dispersed economy with a few distinct urban concentrations versus a spatially dense economy with one major metropolitan centre (the Randstad), respectively. Our experiments are carried out for the 290 municipalities in Sweden and 40 COROPs in The Netherlands. Our research findings show relevant and new insights into differences in the local recovery potential in Sweden and The Netherlands.     

Camionetas: Informal travel among immigrants

Camionetas are mini-vans privately operated as jitney services, run by immigrants for immigrants throughout cities in the US, Mexico, and Central America. Media accounts have portrayed camionetas as part of an unscrupulous industry that endangers and exploits riders, primarily farm workers and other undocumented laborers. Using interviews and ethnography, we analyze who patronizes camionetas in Southern California, and why. Patrons discussed why they use this service, their attitudes about it, other transportation options, and access to employment. Finally, we conducted empirical tests to determine whether these services are as exploitative of their riders as portrayed. This research suggests that camionetas are primarily used by Mexican immigrants with varied socio-economic characteristics who want to travel inter-regionally and transnationally. Patrons praised camioneta service for timesaving, Spanish-speaking drivers, more flexible and “out-of-the-way” stops, the inclusion of Spanish music and television in the vehicle, and door-to-door service. Our ethnographic evidence suggested that the camionetas operating in Southern California were comfortable and safe. But statistical tests suggest that undocumented patrons in our sample may face price discrimination due to the paucity of travel opportunities that do not require US identification. This research informs policy debates about transnational vehicle travel, safety, privatized transit, and access among marginalized groups.     

Short‐term travel time forecasts for transport information system in hong kong

In this paper, a case study is carried out in Hong Kong for demonstration of the Transport Information System (TIS) prototype. A traffic flow simulator (TFS) is presented to forecast the short‐term travel times that can be served as a predicted travel time database for the TIS in Hong Kong. In the TFS, a stochastic deviation coefficient is incorporated to simulate the minute‐by‐minute fluctuation of traffic flows within the peak hour period. The purposes of the case study are: 1) to show the applicability of the TFS for larger‐scale road network; and 2) to illustrate the short‐term forecasting of path travel times in practice. The results of the case study show that the TFS can be applied to real network effectively. The predicted travel times are compared with the observed travel times on the selected paths for an OD pair. The results show that the observed path travel times fall in the 90% confidence interval of the predicted path travel times.     

Rural mobility and mode choice: Evidence from the 2001 National Household Travel Survey

This article uses data from the 2001 National Household Travel Survey (NHTS) to compare travel behavior in rural and urban areas of the U.S. As expected, the car is the overwhelmingly dominant mode of travel. Over 97% of rural households own at least one car vs. 92% of urban households; 91% of trips are made by car in rural areas vs. 86% in urban areas. Regardless of age, income, and race, almost everyone in rural areas relies on the private car for most travel needs. Mobility levels in rural areas are generally higher than in urban areas. That results from the more dispersed residences and activity sites in rural areas, which increase trip distances and force reliance on the car. Somewhat surprisingly, the rural elderly and poor are considerably more mobile than their urban counterparts, and their mobility deficit compared to the rural population average is strikingly less than for the urban elderly and poor compared to the urban average. Data limitations prevented a measurement of accessibility, however, and it seems likely that rural areas, by their very nature, are less accessible than urban areas, especially for the small percentage of car-less poor and elderly households.     

Mass transit in developing cities

Using case study material, this paper examines the relative merit of metros and high performance bus systems in use in Third World cities. It demonstrates that buses with suitable priority measures are capable of meeting high passenger demands. The paper also shows that despite the poor financial performance and other shortcomings of metros, they can yield a respectable economic return. The paper draws on studies undertaken as part of the research program of the Overseas Unit of the Transport Research Laboratory.     

Behavioural responses to vehicle emissions charging

Road pricing as an economic construct is not a new phenomenon in transportation research. Whilst fuel taxation and tolling of roads are common ways of raising revenue in many countries, these initiatives are primarily aimed at road infrastructure financing. Worldwide there has been growing interest in pricing structures designed to also manage the growing levels of traffic congestion and, in recent times, an increasing focus on generating reductions in carbon emissions from vehicle ownership and use. This paper presents a stated choice experiment undertaken in response to the increasing interest in the environmental externalities of travel behaviour. The aim of this choice experiment is to identify the potential to switch to more fuel efficient cars that emit lower emissions, under differing pricing and technology scenarios. Results indicate that annual and variable emissions surcharges targeted very specifically to vehicle emission rates have a noticeable role in modifying vehicle purchasing decisions.     

Computational methodology to predict injury risk for motor vehicle crash victims: A framework for improving Advanced Automatic Crash Notification systems

Advanced Automatic Crash Notification (AACN) systems, capable of predicting post-crash injury severity and subsequent automatic transfer of injury assessment data to emergency medical services, may significantly improve the timeliness, appropriateness, and efficacy of care provided. The estimation of injury severity based on statistical field data, as incorporated in current AACN systems, lack specificity and accuracy to identify the risk of life-threatening conditions. To enhance the existing AACN framework, the goal of the current study was to develop a computational methodology to predict risk of injury in specific body regions based on specific characteristics of the crash, occupant and vehicle. The computational technique involved multibody models of the vehicle and the occupant to simulate the case-specific occupant dynamics and subsequently predict the injury risk using established physical metrics. To demonstrate the computational-based injury prediction methodology, three frontal crash cases involving adult drivers in passenger cars were extracted from the US National Automotive Sampling System Crashworthiness Data System. The representative vehicle model, anthropometrically scaled model of the occupant and kinematic information related to the crash cases, selected at different severities, were used for the blinded verification of injury risk estimations in five different body regions. When compared to existing statistical algorithms, the current computational methodology is a significant improvement toward post-crash injury prediction specifically tailored to individual attributes of the crash. Variations in the initial posture of the driver, analyzed as a pre-crash variable, were shown to have a significant effect on the injury risk.     

Equilibrium analysis of the scheduling of tours in congested networks

In this paper, we develop a model of travel in tours that joins several locations by travel through a congested network. We develop a microscopic analysis in continuous time of individual benefits obtained by spending time at each of the locations and costs incurred through travel between them. This is combined with a continuous time macroscopic equilibrium model of travel during congested peak periods to show how individuals' travel choices are influenced by the congestion that result from corresponding choices made by others. We show how different travellers can achieve identical net utilities by making different combinations of choices within the equilibrium. The resulting model can be used to investigate the effect on travel behaviour and individual utility of various transport interventions, and we illustrate this by considering the effect of a peak‐period charge that eliminates congestion.