Within day rescheduling microsimulation combined with macrosimulated traffic

The concept of rescheduling is essential to activity-based modeling in order to calculate effects of both unexpected incidents and adaptation of individuals to traffic demand management measures. When collaboration between individuals is involved or timetable based public transportation modes are chosen, rescheduling becomes complex. This paper describes a new framework to investigate algorithms for rescheduling at a large scale. The framework allows to explicitly model the information flow between traffic information services and travelers. It combines macroscopic traffic assignment with microscopic simulation of agents adapting their schedules. Perception filtering is introduced to allow for traveler specific interpretation of perceived macroscopic data and for information going unnoticed; perception filters feed person specific short term predictions about the environment required for schedule adaptation. Individuals are assumed to maximize schedule utility. Initial agendas are created by the FEATHERS activity-based schedule generator for mutually independent individuals using an undisturbed loaded transportation network. The new framework allows both actor behavior and external phenomena to influence the transportation network state; individuals interpret the state changes via perception filtering and start adapting their schedules, again affecting the network via updated traffic demand. The first rescheduling mechanism that has been investigated uses marginal utility that monotonically decreases with activity duration and a monotonically converging relaxation algorithm to efficiently determine the new activity timing. The current framework implementation is aimed to support re-timing, re-location and activity re-sequencing; re-routing at the level of the individual however, requires microscopic travel simulation.     

User perspectives in public transport timetable optimisation

The present paper deals with timetable optimisation from the perspective of minimising the waiting time experienced by passengers when transferring either to or from a bus. Due to its inherent complexity, this bi-level minimisation problem is extremely difficult to solve mathematically, since timetable optimisation is a non-linear non-convex mixed integer problem, with passenger flows defined by the route choice model, whereas the route choice model is a non-linear non-continuous mapping of the timetable. Therefore, a heuristic solution approach is developed in this paper, based on the idea of varying and optimising the offset of the bus lines. Varying the offset for a bus line impacts the waiting time passengers experience at any transfer stop on the bus line.In the bi-level timetable optimisation problem, the lower level is a transit assignment calculation yielding passengers’ route choice. This is used as weight when minimising waiting time by applying a Tabu Search algorithm to adapt the offset values for bus lines. The updated timetable then serves as input in the following transit assignment calculation. The process continues until convergence.The heuristic solution approach was applied on the large-scale public transport network in Denmark. The timetable optimisation approach yielded a yearly reduction in weighted waiting time equivalent to approximately 45 million Danish kroner (9 million USD).     

Biofuel futures in road transport – A modeling analysis for Sweden

First and second generation biofuels are among few low-carbon alternatives for road transport that currently are commercially available or in an early commercialization phase. They are thus potential options for meeting climate targets in the medium term. For the case of Sweden, we investigate cost-efficient use of biofuels in road transport under system-wide CO₂ reduction targets to 2050, and the effects of implementation of targets for an almost fossil-free road transport sector to 2030. We apply the bottom-up, optimization MARKAL_Sweden model, which covers the entire Swedish energy system including the transport sector. For CO₂ reductions of 80% to 2050 in the Swedish energy system as a whole, the results of the main scenario show an annual growth rate for road transport biofuels of about 6% from 2010 to 2050, with biofuels accounting for 78% of road transport final energy use in 2050. The preferred biofuel choices are methanol and biomethane. When introducing additional fossil fuel phase-out policies in road transport (−80% to 2030), a doubling of the growth rate to 2030 is required and system CO₂ abatement costs increases by 6% for the main scenario. Results imply that second generation biofuels, along with energy-efficient vehicle technologies such as plug-in hybrids, can be an important part of optimized system solutions meeting stringent medium-term climate targets.     

Modeling the relationships among urban passenger travel carbon dioxide emissions,transportation demand and supply,population density,and proxy policy variables

To support the development of policies that reduce greenhouse gas (GHG) emissions by encouraging reduced travel and increased use of efficient transportation modes, it is necessary to better understand the explanatory effects that transportation, population density, and policy variables have on passenger travel related CO₂ emissions. This study presents the development of a model of CO₂ emissions per capita as a function of various explanatory variables using data on 146 urbanized areas in the United States. The model takes into account selectivity bias resulting from the fact that adopting policies aimed at reducing emissions in an urbanized area may be partly driven by the presence of environmental concerns in that area. The results indicate that population density, transit share, freeway lane-miles per capita, private vehicle occupancy, and average travel time have a statistically significant explanatory effect on passenger travel related CO₂ emissions. In addition, the presence of automobile emissions inspection programs, which serves as a proxy indicator of other policies addressing environmental concerns and which could influence travelers in making environmentally favorable travel choices, markedly changes the manner in which transportation variables explain CO₂ emission levels.     

Mathematical properties and constraints representation for bottom-up approaches to the evaluation of GHG mitigation policies

Bottom-up models, including MARKAL, MESSAGE and AIM, are widely used when analyzing the effect of greenhouse gas (GHG) abatement policies. These bottom-up models are mostly formulated as a linear programming (LP) optimization model to find both the minimal cost combination of abatement technologies and energy flows while satisfying demands. It is not unusual that the bottom-up modeling involves a great number of technical, industrial, socioeconomic and environmental constraints. Investigating representative constraints needed for analyzing GHG abatement policies, this study proposes how to implement these constraints in bottom-up modeling.     

Energy savings in transport

A decade of increasing Federal attention to urban transportation needs has culminated in the 1970 Urban Mass Transportation Assistance Act. This Act is intended to provide 10 thousand million dollars over the next 12 years in Federal assistance money to urban public transportation systems. This paper examines the needs of selected U.S. cities as a basis for (1) understanding the vast, various and complex transportation needs of urban areas throughout the country, and (2) assessing the sufficiency of these funds. The sample cities have been placed into three broad categories based on the state of development of their transportation systems. In Category I cities, the essential need is to ensure the survival of bus systems for the use of non‐drivers, or to provide some other viable alternative to the automobile; in Category II cities, the primary needs are to relieve auto congestion and to improve public transportation components, while in Category III cities, the primary need is massive investment to improve and to extend public transportation facilities. It is concluded that the presently intended Federal funding level for transportation will not meet the financial requirements of the Category III cities.     

Editorial Comment

This article examines fundamental questions concerning the origins and evolution of academic transport studies and the dynamics of its historical development. These fundamental questions are generally little discussed, yet are vital in gaining a better understanding of how the subject is driven forward. This article therefore attempts to answer these questions by taking the UK as a case study, with the principal method being evidence from semi-structured interviews with 20 senior figures integrally involved in the development of the subject. The characterization of transport studies provided by Allsop is employed as an analytical framework, enabling the construction of a historical narrative that can provide salient insights. Thus, it is argued that for academic transport studies the degree of early cross-fertilization with public arenas has meant that subsequent developments have been shaped by the subject's contextual environment. Most prominent among these developments has been the trend towards wider disciplinary breadth. This article examines the evolution of these processes, while the concluding section discusses their implications for consequent strengths and limitations of the subject.     

The use of demand correlation in the modeling of air carrier departure delays as first‐order autoregressive random processes

A method for modeling air carrier departure delays at commercial‐service airports as autoregressive random processes is presented. This method employs the correlation of a priori demand data to significantly reduce prediction error in the optimal least‐squares estimator for additive white noise. The reduction factor of the prediction error is demonstrated to be on the order of 10² over that of the unbiased estimator. Copyright © 2011 John Wiley & Sons, Ltd.     

Traffic noise studies in a tropical environment

This paper reports upon a survey of traffic noise annoyance in three residential districts of Trinidad, West Indies. Householder perceptions were solicited by means of a questionnaire survey and direct measurements of traffic noise levels were taken. The results were compared with surveys elsewhere. It was concluded that household status had little effect on annoyance perception, that at L₁₀ levels greater than 70 dB(A) at a dwelling facade the noise level is unacceptable. L₁₀ levels less than 65 dB(A) at the building facade are not perceived as annoying in the environment considered.     

Innovative systems for the transportation disadvantaged: Toward more efficient and operationally usable planning tools

When considering innovative forms of public transport for specific groups, such as demand responsive services, the challenge is to find a good balance between operational efficiency and 'user friendliness' of the scheduling algorithm even when specialized skills are not available. Regret insertion-based processes have shown their effectiveness in addressing this specific concern. We introduce a new class of hybrid regret measures to understand better why the behaviour of this kind of heuristic is superior to that of other insertion rules. Our analyses show the importance of keeping a good balance between short- and long-term strategies during the solution process. We also use this methodology to investigate the relationship between the number of vehicles needed and total distance covered - the key point of any cost analysis striving for greater efficiency. Against expectations, in most cases decreasing fleet size leads to savings in vehicle mileage, since the heuristic solution is still far from optimality.