An analysis on long term emission benefits of a government vehicle fleet replacement plan in northern illinois

There have been a number of studies of the effectiveness of vehicle scrappage programs, which offer incentives to accelerated scrappage of older vehicles often thought to be high emitters. These programs are voluntary and aimed at replacement of household vehicles. In contrast, there is a gap in knowledge related to the emissions benefits of government fleet replacement (retirement) programs. In this study, the efficacy of a fleet replacement program for a local government agency in Northern Illinois, the Forest Preserve of DuPage County (FPDC), is examined using a probabilistic vehicle survival model that accounts for time-varying covariates such as vehicle age and gasoline price. The vehicle lifetime operating emissions are calculated based on the estimated vehicle survival probabilities from the survival model and compared with those derived using the EPA default fleet used in MOBILE6 and the fleet represented by the Oak Ridge National Laboratory (ORNL) survival curve. The results suggest that while there may be short term emission benefits of the FPDC fleet replacement plan, the long-term emission benefits are highly sensitive to economic factors (e.g., future gasoline price) and exhibit a decreasing trend. This indicates that an adaptive multi-stage replacement strategy as opposed to a fixed one is preferable to achieve optimal cost effectiveness.

“I can do perfectly well without a car!”

This article presents the results of a study exploring travellers’ preferences for middle-distance travel using Q-methodology. Respondents rank-ordered 42 opinion statements regarding travel choice and motivations for travel in general and for car and public transport as alternative travel modes. By-person factor analysis revealed four distinct preference segments for middle-distance travel: (1) choice travellers with a preference for public transport, (2) deliberate-choice travellers, (3) choice travellers with car as dominant alternative, and (4) car-dependent travellers. These preference segments differ in terms of the levels of involvement and cognitive effort in travel decision making, the travel consideration-set and underlying motivations. The study showed that for most people there is more to travel than getting from point A to point B, and that there is considerable heterogeneity in middle-distance travel preferences. Policy implications for reducing the need for travel and promoting a modal shift from car to other travel modes are discussed.     

Shift of reference point and implications on behavioral reaction to gains and losses

It is widely recognized that individual decision-making is subject to the evaluation of gains and losses around a reference point. The estimation of discrete choice models increasingly use data from stated choice experiments which are pivoted around a reference alternative. However, to date, the specification of a reference alternative in transport studies has been fixed, whereas it is common to observe individuals adjusting their preferences according to a change in their reference point. This paper focuses on individual reactions, in a freight choice context, to a negative change in the reference alternative values, identifying the behavioural implications in terms of loss aversion and diminishing sensitivity. The results show a significant adjustment in the valuation of gains and losses around a shifted reference alternative. In particular, we find an average increase in loss aversion for cost and time attributes, and a substantial decrease for punctuality. These findings are translated to significant differences in the willingness to pay and willingness to accept measures, providing supporting evidence of respondents’ behavioural reaction.     

Optimal design and benefits of a short turning strategy for a bus corridor

We develop a short turning model using demand information from station to station within a single bus line-single period setting, aimed at increasing the service frequency on the more loaded sections to deal with spatial concentration of demand considering both operators’ and users’ costs. We find analytical expressions for optimal values of the design variables, namely frequencies (inside and outside the short cycle), capacity of vehicles and the position of the short turn limit stations. These expressions are used to analyze the influence of different parameters in the final solution. The design variables and the corresponding cost components for operators and users (waiting and in-vehicle times) are compared against an optimized normal operation scheme (single frequency). Applications on actual transit corridors exhibiting different demand profiles are conducted, calculating the optimal values for the design variables and the resulting benefits for each case. Results show the typical demand configurations that are better served using a short turn strategy.     

Airport management: a strategic approach

In this paper a Dynamic Balanced Scorecard (DBSC) is used for the main purpose of indicating strategy implementation avenues to managers so as to equip them with more efficient decision-making tools. To that end, Fuzzy Multicriteria Decision-Making methodology is used as a source of technical support in formulating a cause and effect system and fuzzy strategic indicators. This methodological instrument brings a strategic vision to performance analysis and is designed to furnish a tool for evaluating the impacts of management action on the BSC fuzzy indicators. The proposed analytical methodology is applied to Brazil’s seven main international airports.     

Critical success conditions of collaborative methods: a comparative evaluation of transport planning projects

This paper explores critical success conditions of collaborative planning projects in the area of urban transport, evaluating the impact of new collaborative methods, instruments and processes on project performance. Hypothesis building is based on a comparative, empirical research design, rather than on deductive theory construction. Potential critical success conditions are derived from literature. Based on five urban transport planning projects in Gothenburg (Sweden), London (United Kingdom), Milwaukee (United States), Tokyo (Japan) and Mexico City (Mexico), a rough set analysis of the five cases reveals validated success conditions, which can be used for formulating hypotheses for further research or for policy and process improvement. The results suggest that a dedicated management of the multi-actor network, a high diversity of actors, as well as an extensive use of knowledge integration methods in combination with a high network density are critical success conditions of these planning processes. Surprisingly, the extensive use of unilateral methods also showed to be an important success condition. The traditional role of the planner will have to be complemented with the expertise of network and methodology management. The authors conclude that rough set analysis can be a valuable addition to narrative, single-case analysis of collaborative urban transport planning processes.     

The effect of location,mobility and socio-demographic factors on task and time allocation of households

This paper investigates the role of location factors in task and time allocation at the household level. It is hypothesized that, if time constraints are less binding as a result of living in an urban area or owning more cars, spouses engage more often and longer in out-of-home activities and schedule their activities more independently. The hypotheses are tested with logistic and Cox regression models of activity participation and time allocation on a data set collected in the Amsterdam–Utrecht region in the Netherlands. Results suggest that the hypotheses are supported with respect to specific household activity scheduling decisions.     

Longer-term changes in mode choice decisions in Chennai: a comparison between cross-sectional and dynamic models

The rapid and continuing changes in travel and mobility needs in India over the last decade necessitates the development and use of dynamic models for travel demand forecasting rather than cross-sectional models. In this context, this paper investigates mode choice dynamics among workers in Chennai city, India over a period of five years (1999–2004). Dynamics in mode choice is captured at four levels: exogenous variable change, state-dependence, changes in users’ sensitivity to attributes, and unobserved error terms. The results show that the dynamic models provide a substantial improvement (of over 500 log-likelihood points and ρ² increases from 44% to 68%) over the cross-sectional model. The performance was compared using two illustrative policy scenarios with important methodological and practical implications. The results indicate that cross-sectional models tend to provide inflated estimates of potential improvement measures. Improving the Level of Service (LOS) alone will not produce the anticipated benefits to transit agencies, as it fails to overcome the persistent inertia captured in the state-dependence factors. The results and models have important applications in the context of growing motorization and congestion management in developing countries.

The transition to electric bikes in China: history and key reasons for rapid growth

Annual electric bike (e-bike) sales in China grew from 40,000 in 1998 to 10 million in 2005. This rapid transition from human-powered bicycles, buses and gasoline-powered scooters to an all-electric vehicle/fuel technology system is special in the evolution of transportation technology and, thus far, unique to China. We examine how and why e-bikes developed so quickly in China with particular focus on the key technical, economic, and political factors involved. This case study provides important insights to policy makers in China and abroad on how timely regulatory policy can change the purchase choice of millions and create a new mode of transportation. These lessons are especially important to China as it embarks on a large-scale transition to personal vehicles, but also to other countries seeking more sustainable forms of transportation.

Who escort children: mum or dad? Exploring gender differences in escorting mobility among parisian dual-earner couples

The present article looks to pinpoint explanatory factors for the sharing of escorting of children in dual-earner families. It proposes a detailed analysis of inequalities and interactions in dual-earner families when it comes to escorting children by taking into account the characteristics of trips to and from school for children, the characteristics of the parents’ occupations, and the characteristics of the household. Compared with earlier research, the model considers more detailed data about the escorts’ jobs, such as specific working hours, which provide a better understanding of the constraints on parents and insight into the choices made when both parents are in a position to escort their children. The findings depart somewhat from those of earlier work on the question because more specific data are considered. They show a marked gender inequality in escorting because mothers in dual-earner families do more than two-thirds of the escorting. But the factors explaining the sharing of escorting act almost symmetrically for both parents, with the effect of work starting and finishing times being preponderant. These models confirm that the inequality kicks in ahead of this: mothers in dual-earner households are more often than fathers in jobs with short working hours and which are more compatible with escorting.