I can’t believe your attitude: a joint estimation of best worst attitudes and electric vehicle choice

The number of conventionally fuelled motor vehicles in use is increasing worldwide despite warnings about finite fossil fuel and the detrimental impacts of burning such fuels. While electric vehicles, the subject of much research, generate far less emissions and offer the potential for power from renewable sources, they are yet to significantly penetrate the market. Tangible barriers such as price and vehicle range still exist, but consumer attitudes also drive behaviour. This paper examines attributes in a framework relatively new to transportation and energy policy; best–worst scaling. This method is widely considered an improvement over traditional methods of eliciting attitudes and beliefs, where respondents select attitudes they find best or worst from a set of attitudinal statements. To avoid potential endogeneity bias, we jointly model attitudes and choice for the first time with best–worst data. It is found that energy crisis, air quality and climate change concerns influence behaviour with respect to vehicle range and that travel behaviour change and forms of government incentives are needed influences on behaviour with respect to vehicle emissions. It is argued that correctly modelling attitudes reduces the error term of the vehicle choice model and provides policy makers with an improved lens for assessing behaviour. Additionally, the methods described within can easily be adapted to other policy scenarios.     

How commuting affects subjective wellbeing

Transportation - Commuting between home and work is routinely performed by workers and any wellbeing impacts of commuting will consequently affect a large proportion of the population. This paper...     

Bridging the gap between evacuations and the sharing economy

Transportation - This paper examines the opportunities for addressing evacuations by leveraging the sharing economy. To support this research, we use a mixed-method approach employing archival...     

What cognitive mechanisms predict travel mode choice? A systematic review with meta-analysis

Reduced private car use can limit greenhouse gas emissions and improve public health. It is unclear, however, how promotion of alternative transport choices can be optimised. A systematic review and meta-analysis was conducted to identify potentially modifiable cognitive mechanisms that have been related to car use and use of alternative transport modes. A qualitative synthesis of measures of potentially modifiable mechanisms based on 43 studies yielded 26 conceptually distinct mechanism categories. Meta-analyses of associations between these mechanisms and car use/non-use generated 205 effects sizes (Pearson’s r) from 35 studies. The strongest correlates of car use were intentions, perceived behavioural control, attitudes and habit. The strongest correlates of alternative transportation choices were intentions, perceived behavioural control and attitudes. Implications for researchers and policy implementation are discussed.     

A multi-instrumented approach to observing the activity rescheduling decision process

Activity scheduling simulation models represent an emerging and proposing approach to forecasting travel demand. The most significant developmental challenge is the lack of empirical data on how people actually proceed through the scheduling and conflict resolution process. This paper develops a new methodology to collect data about the rescheduling decision process. The data collection involves six stages: preplanned schedule interview, coding of the preplanned schedule, second-by-second Global Positioning System tracking, internet-based prompted recall diary, detection of rescheduling decisions (via comparison of planned versus executed activities), and a final in-depth interview probing the how and why of rescheduling decisions. Each stage of the methodology is described in detail with example results drawn from a pilot study. Key discoveries include: elicitation of multiple preplanned schedule reporting methods (verbal, point-form, calendar); discovery that activity attributes (time, location, involved persons) are planned on significantly different time horizons and include partial elaboration; and provision of new insights into how and why rescheduling decisions are made. A method for automatically tracking rescheduling decisions was also discovered. Overall, the new methodology has potential to contribute to the development of more realistic models of the entire scheduling process, especially rescheduling and conflict resolution sub-models.     

Multimodal route choice in maritime transportation: the case of Korean auto-parts exporters

Global offshoring has increased the need for transport of half-finished goods and components, along with finished goods. The auto-parts industry in Korea has also entered the global market as Korean car manufacturers have started to build overseas factories. Maintaining cost competitiveness by minimising total logistics costs will thus be a critical strategy for the industry. This research compares the total annual costs of four feasible transport routes from Korea to the US using the inventory-theoretic model, which encompasses direct transport costs, in-transit carrying costs, and warehouse inventory costs. We apply this model to real transport data collected from a Korean auto-parts company. A static analysis shows that inventory costs can play a decisive role in altering the cost competitiveness of different routes. In addition, sensitivity and scenario analyses with changes in variables and the market situations reveal that the cost structure of each route plays an important role in determining their relative cost competitiveness in varying market conditions.     

Ground-truthing social vulnerability indices of Alaska fishing communities

Abstract

Community vulnerability is increasingly evaluated through quantitative social indices, typically developed using secondary data sources rather than primary data collection. It is necessary to understand the validity of these indices if they will be used to inform policy and decision making. This paper presents a ground-truthing effort to validate quantitative indices that characterize the well-being of Alaska fishing communities. We utilized ethnographic data collected from 13 representative communities and a capital assets framework to ground-truth the indices, in which qualitative ranks of vulnerability were compared against quantitative indices. The majority (73.8%) of ranks were in complete or moderate agreement and the results indicate that most of the indices are representative of community vulnerability; yet some variables utilized to create the indices could be modified to better reflect realities in Alaska. Indices of commercial fishery engagement and reliance appeared to be more reliable than socio-economic indicators, particularly for smaller fishing communities. We also confirmed that the indices do not capture political, or ecological factors that affect levels of community vulnerability. We conclude that quantitative indices of community vulnerability are useful rapid assessment tools; however, they should be validated, and complemented with ethnographic data prior to their implementation as policy making and management tools.     

Lateral dynamics of motorcycles towing single-wheeled trailers

A motorcycle towing a single-wheel trailer may provide useful transport for light cargo on narrow tracks and off-road use, particularly in rural areas of developing countries. Four designs of such trailers are described. Linear models are derived for the lateral dynamics of an off-road motorcycle towing this type of trailer straight ahead at constant speed. The trailers were tested behind an instrumented motorcycle. Linear autoregressive models were fitted to the experimental data using system identification techniques. Analytical and experimentally derived models largely agreed on frequency, damping and shape of the weave, wobble and trailer sway normal modes. The trailers made the motorcycle's steering heavier but the analytical models did not predict this. The location of the articulation axes between the motorcycle and the trailer were found to be critical for stability. The best trailer design handled well with loads up to 200 kg and speeds up to 70 km/h.     

Lateral Dynamics of an Offroad Motorcycle by System Identification

An instrumented offroad motorcycle was run at a range of speeds in approximately straight lines whilst the rider excited its lateral dynamics by shaking the steering. Autoregressive models were fitted to the resulting multiple output time series data using system identification. The method allowed statistical estimation of state space models to represent the dynamics of an unstable or marginally stable vehicle under manual control. A symbolic algebra computer package was used to derive an analytical state space model to describe the lateral dynamics of the motorcycle. Results from the experiments and analysis compared well with respect to frequency, damping and modal shape of weave and wobble modes, frequency response and model order.     

Combining technology development and behaviour change to meet CO2 cumulative emission budgets for road transport: Case studies for the USA and Europe

Global temperature rise over the long term will be proportional to the total amount of CO₂ emitted. Any given probability of exceeding a targeted maximum temperature rise implies a maximum limit on the cumulative total of CO₂ that can be emitted: a CO₂ “budget”. This paper describes an approach to modelling cumulative emissions from light and heavy duty road transport from the present to 2050, focussing on the USA and Europe, and comparing the potential impacts of a range of technological and behaviourally-based abatement measures with such cumulative emissions budgets.The model shows that abatement measures would have a lower effect on cumulative emissions from 2000 to 2050 than on annual emissions in 2050, so that focussing only on annual emissions could be misleading. It shows that technological developments would be insufficient on their own to enable Europe and the USA to meet CO₂ budgets for road transport. Behavioural changes, which potentially can be implemented much sooner, would be essential too. There is potential to keep European light duty emissions very close to CO₂ budgets, and US light duty emissions not far above the least restrictive budget, but the model predicts that heavy duty emissions in both regions are likely to exceed their CO₂ budgets. Deeper emissions reductions in other regions and sectors will be needed to compensate for this. Timing would be critical: for the greatest impact, behaviour change policies and interventions would need to be applied early and deeply.