Enablers and Barriers to the Adoption of Alternatively Powered Buses

Abstract

This paper seeks to identify enablers and barriers that stimulate or prevent the adoption of alternatively powered buses (APBs) in cities. The research method concentrates on an in‐depth analysis of 21 European demonstration case studies of APBs. Considerable differences exist between these cities due to the different reference situation. The type of measurement and the situation in the demonstration cities influence the exact fuel consumption and emission reduction. Variables that could enable the adoption of all types of APBs are: (1) the compatibility with previously introduced ideas; (2) the already available necessary supporting infrastructure in the city; (3) a changed external appearance of the APB; (4) the acceptance of the APBs by passengers and bus drivers; and (5) political support in the city regarding the APBs. The main variables that could be determined as barriers are: the relative economic advantage (the outline of costs is higher than that of conventional buses); and the understanding of the APB for bus drivers and mechanics (because special training is needed for both groups).     

LUTI operational models review based on the proposition of an a priori ALUTI conceptual model

ABSTRACT

This paper focuses on understanding to what extent the components of LUTI models and their mutual interactions are conceptually represented by eight operational LUTI models. This is important for the understanding of LUTI models’ mechanisms, firstly because it may reduce communication barriers between planning communities, secondly because it may help us understand the models’ applicability, and thirdly it may highlight the models’ shortcomings and point for future research. We present a discussion about what subsystems should be considered for LUTI modelling, from which we derived an “a priori” conceptual ALUTI model (incorporating Activities, besides Land Use and Transport). By comparing the rationale behind each model with this conceptual model, we establish the basis for our review, focussing on whether these models incorporate the ALUTI components, its inner workings and the relationships between these components. Results indicate three main limitations of the reviewed models. First, models not always adequately include all the components of the a priori ALUTI model. Second, the ALUTI subsystems’ internal functions are not explicitly modelled in several of the models reviewed, making it difficult to evaluate how planning decisions affect the subsystem. Third, only few models recognise all mutual interactions, especially in respect to the Activity subsystem.     

Modeling time mean speed and space mean speed for heterogeneous traffic conditions

This paper analyzes vehicular speeds at a micro level and studies the relationships between the important elements of speed, namely space mean speed (SMS) and time mean speed (TMS) under heterogeneous traffic conditions. Vehicular speed data were collected at selected road stretches around Delhi, India, in an attempt to understand and model the type of relationships between SMS and TMS under heterogeneous traffic conditions. To demonstrate the superiority of the proposed models, comparisons are made with existing traditional models. The results reveal that the proposed models are consistent in predicting speeds with high accuracy.     

An integrated framework to jointly model decisions of activity time allocation and work-related travel

Five activity-travel choice dimensions, including three activity time allocation decisions and two work-related travel choices, are jointly modeled using the structural equation model in order to accommodate the complex interactions among them. Via a two-step estimation approach, the behavioral pattern underlying activity-travel decisions is explicitly revealed. For example, it demonstrates the priority with respect to subsistence activity, maintenance activity, and recreation activity due to a limited time budget; and bus commuting behavior positively influences the time allocated to the maintenance activity. In addition, two attitudinal factors are constructed and confirmed to have important effects on the five behavioral dimensions, which contribute to reveal the decision-making process from the perspective of psychology. This comprehensive framework is expected to provide important implications for mobility management and urban planning.     

A stochastic computational model for yellow time determination and its application

This paper proposes a stochastic model to determine the yellow time according to the occurring probability of Type‐I dilemma zone (P_DZ). Unlike the conventional methods generally based on the deterministic traffic flow theory, the proposed model fully accounts for the randomness of input variables such as approaching speed, deceleration rate, perception‐and‐reaction time, and distance to stop‐line at the yellow onset. A theoretical model is firstly established, and a computational program incorporating Monte Carlo Simulation is then developed to facilitate its general solution. These two alternative solution approaches to derive P_DZ and Y are proposed, depending upon whether D/V and (τ + V/2d) follow certain analytical distributions or not. In addition, field data at a typical high‐speed highway intersection are collected to validate the model. Based on the validated model, comprehensive sensitivity analysis is conducted to look into the entire picture of the relationship between P_DZ and the distributions as well as correlations of the input variables. To demonstrate the application of the proposed model, the required yellow times for various conditions are calculated based on the acceptable levels of P_DZ, and representative application tables for typical cases are finally provided. With the aid of the proposed methodology, traffic engineers are capable of designing yellow time in a more sophisticated manner. Copyright © 2014 John Wiley & Sons, Ltd.     

Estimating a model of dynamic activity generation based on one-day observations: Method and results

In this paper we develop and explore an approach to estimate dynamic models of activity generation on one-day travel-diary data. Dynamic models predict multi-day activity patterns of individuals taking into account dynamic needs as well as day-varying preferences and time-budgets. We formulate an ordered-logit model of dynamic activity-agenda-formation decisions and show how one-day observation probabilities can be derived from the model as a function of the model’s parameters and, with that, how parameters can be estimated using standard loglikelihood estimation. A scale parameter cannot be identified because information on within-person variability is lacking in one-day data. An application of the method to data from a national travel survey illustrates the method. A test on simulated data indicates that, given a pre-set scale, the parameters can be identified and that estimates are robust for a source of heterogeneity not captured in the model. This result indicates that dynamic activity-based models of the kind considered here can be estimated from data that are less costly to collect and that support the large sample sizes typically required for travel-demand modeling. We conclude therefore that the proposed approach opens up a way to develop large-scale dynamic activity-based models of travel demand.     

Influence of 3D printing on transport: a theory and experts judgment based conceptual model

Consumer 3D printing is on the rise and has the potential to significantly change the transport and logistics sector. Current literature on 3D printing and transport studies does not provide a systematic model of the impact of 3D printing on transport and related (policy relevant) areas, such as traffic safety, location decisions, accessibility and environmental effects. Based on a literature review and two rounds of expert consultation, we propose and refine a conceptual model as a way to approach this gap in the literature. The expert consultation yields that the conceptual model comprises the relevant and important elements for assessing the impact of 3D printing on transport and transport-related challenges. Location, needs and transport resistance are important: (a) city-level hubs are the most likely locations for 3D printers because they can coordinate material flows and gather expertise; (b) mass-individualisation and personification dictates the needs for 3D printers; (c) distribution networks will be organised more efficiently, less empty vehicles, but raw materials still need shipping. However, experts’ opinions diverged on the impact of 3D printing on transport volumes and environmental impacts.     

Demand management of congested public transport systems: a conceptual framework and application using smart card data

Transportation - Transportation demand management, long used to reduce car traffic, is receiving attention among public transport operators as a means to reduce congestion in crowded public...     

A structural and empirical model of subsistence activity behavior and income

This paper develops a structural and empirical model of subsistence activity behavior and income. Subsistence activity decisions (work participation and hours of work decisions) and income have an important bearing on activity and travel behavior of individuals. The proposed structural model represents an effort to analyze subsistence activity behavior and income earnings to support a better understanding, and reliable forecasting, of individual travel behavior. The empirical model formulates and estimates an integrated model of employment, hours of work and income which takes account of interdependencies among these choices and their structural relationships with other relevant variables. Social factors that inhibit an individual's employment and work hours decision and affect an individual's income are incorporated in the model. A sample of households from the Dutch National Mobility Panel is used in the empirical analysis.     

A subway planning bi-objective multi-period optimization model integrating timetabling and vehicle scheduling: a case study of Tehran

Due to the interaction among different planning levels and various travel demands during a day, the transit network planning is of great importance. In this paper, a bi-objective multi-period planning model is proposed for the synchronization of timetabling and vehicle scheduling. The main aim of the problem is to minimize the weighted transfer waiting time in the interchange stations along with the operational costs of vehicles. In order to demonstrate the effectiveness of the proposed integrated model, a real case study of Tehran subway is considered. The proposed model is solved by the ε-constraint method and some outstanding results are achieved.

     

Modeling the spatial and temporal dimensions of recreational activity participation with a focus on physical activities

This study presents a unified framework to understand the weekday recreational activity participation time-use of adults, with an emphasis on the time expended in physically active recreation pursuits by location and by time-of-day. Such an analysis is important for a better understanding of how individuals incorporate physical activity into their daily activities on a typical weekday, and can inform the development of effective policy interventions to facilitate physical activity. Furthermore, such a study of participation and time use in recreational activity episodes contributes to activity-based travel demand modeling, since recreational activity participation comprises a substantial share of individuals’ total non-work activity participation. The methodology employed here is the multiple discrete continuous extreme value (MDCEV) model, which provides a unified framework to explicitly and endogenously examine time use by type, location, and timing. The data for the empirical analysis is drawn from the 2000 Bay Area Travel Survey (BATS), supplemented with other secondary sources that provide information on physical environment variables. To our knowledge, this is the first study to jointly address the issues of ‘where’, ‘when’ and ‘how much’ individuals choose to participate in ‘what type of (recreational) activity’.     

Discretionary activity time allocation of individuals between in-home and out-of-home and between weekdays and weekends

This paper formulates a model for the allocation of total weekly discretionary time of individuals between in-home and out- of-home locations and between weekdays and the weekend. The model formulation takes the form of a continuous utility-maximizing resource allocation problem. The formulation is applied to an empirical analysis using data drawn from a 1985 time-use survey conducted in the Netherlands. This survey gathered time-use information from individuals over a period of one week and also collected detailed household-personal socio-demographic data. The empirical analysis uses household socio-demographics, individual socio-demographics, and work-related characteristics as the explanatory variables. Among the explanatory variables, age of the individual and work duration during the weekdays appear to be the most important determinants of discretionary time allocation.     

The role of intention as mediator between latent effects and behavior: application of a hybrid choice model to study departure time choices

Transportation - An increasing number of papers are focusing on integrating psychological aspects into the typical discrete choice models. The majority of these studies account for several latent...     

A commuting model for the analysis of the impacts of a tramway project: application to the Lens area

Road congestion is not only an issue for major European urban agglomerations, but also for smaller ones. It is also the case of the Lens urban area, where car use is much higher than the average for medium-sized urban agglomerations in France. Local authorities put forward tramway projects to deal with the strongly negative externalities of congestion: travel time losses and pollution. To analyse its medium-term impact, we have developed a commuting with congestion model, inspired by the four-step traditional model, but with data made available from an origin–destination matrix. The results are encouraging but insufficient, and it is necessary to adopt supplementary measures in order to retrieve and justify the sizeable investments needed. Some measures prove to be very efficient, such as parking fees and urban tolls. Other measures, such as the subsidization of public transport, are partially efficient since they have an impact mainly on intra-urban commutes.     

Development and evaluation of a hybrid travel time forecasting model

The purpose of this paper is to develop and evaluate a hybrid travel time forecasting model with geographic information systems (GIS) technologies for predicting link travel times in congested road networks. In a separate study by You and Kim (cf. You, J., Kim, T.J., 1999b. In: Proceedings of the Third Bi-Annual Conference of the Eastern Asia Society for Transportation Studies, 14–17 September, Taipei, Taiwan), a non-parametric regression model has been developed as a core forecasting algorithm to reduce computation time and increase forecasting accuracy. Using the core forecasting algorithm, a prototype hybrid forecasting model has been developed and tested by deploying GIS technologies in the following areas: (1) storing, retrieving, and displaying traffic data to assist in the forecasting procedures, (2) building road network data, and (3) integrating historical databases and road network data. This study shows that adopting GIS technologies in link travel time forecasting is efficient for achieving two goals: (1) reducing computational delay and (2) increasing forecasting accuracy.     

Travel time ratio: the key factor of spatial reach

An important aspect of reach and accessibility is the time people are willing to spend on reaching activity places. In this paper we see the issue of travel time in an alternative way. Instead of looking at travel time separated from time spent on activities, we examine the relation between travel time and stay time. We operationalize this relation with the concept “travel time ratio”. A hypothetical framework underlying these travel time ratios is displayed. We show that for similar types of activity places the value of travel time ratio are in accordance with each other. We find large differences between trips for mandatory activities and trips for discretionary activities. The results indicate the stability of the travel time ratios. Finally, some implications for future research and policy will be mentioned. This revised version was published online in June 2006 with corrections to the Cover Date.     

Implementation and application of a stochastic aircraft boarding model

The aircraft turnaround processes is mainly controlled by the ground handling, airport or airline staff, except the aircraft boarding, which is driven by the passengers’ experience and willingness or ability to follow the proposed boarding procedures. The paper uses a prior developed, calibrated, stochastic aircraft boarding model, which is applied to different boarding strategies (chronological order of passenger arrival, hand luggage handling), group constellations and innovative infrastructural changes (Flying Carpet, Side-Slip Seat, Foldable Passenger Seat). In this context, passenger boarding is assumed to be a stochastic, agent-based, forward-directed, one-dimensional and discrete process. The stochastic model covers individual passenger behavior as well as operational constraints and deviations. A comprehensive assessment using one model allows for efficient comparison of current research approaches and innovative operational solutions for efficient passenger boarding.