A new approach for improving the performance of freight train timetabling of a single-track railway system

A new approach for improving the performance of freight train timetabling for single-track railways is proposed. Using the idea of a fixed-block signaling system, we develop a matrix representation to express the occupation of inter- and intra-station tracks by trains illustrating the train blocking time diagram in its entirety. Train departure times, dwell times, and unnecessary stopping are adjusted to reduce average train travel time and single train travel time. Conflicts between successive stations and within stations are identified and solved. A fuzzy logic system is further used to adjust the range of train departure times and checks are made to determine whether dwell times and time intervals can be adjusted for passenger and freight trains at congested stations to minimize train waiting times. By combining manual scheduling expertise with the fuzzy inference method, timetable efficiency is significantly improved and becomes more flexible.     

Measuring quality of service in dial-a-ride operations: the case of a Canadian city

In many countries, dial-a-ride services are provided by public authorities to elderly and handicapped people who cannot use regular transit. Cost minimization is key to running these services, but one can observe a growing interest in quality measurement and improvement. A first step in improving quality is to define a quality measurement scale specific to dial-a-ride services. A second step is to incorporate quality measurements in mathematical models that serve as a basis for optimization algorithms. To this end, an extensive survey of dial-a-ride users was conducted in Longueuil, the largest suburb of Montreal, Canada. This paper describes the steps of the survey and presents its main conclusions: (1) 56 attributes were identified based on interviews, (2) the questionnaire developed has proved to be reliable and valid, (3) an exploratory factor analysis allowed us to determine 13 dimensions of quality in dial-a-ride services, (4) the most important criteria for users were identified, and (5) population segmenting variables by which subgroups of users can be categorized were also determined. Managerial implications of our results are also discussed.     

Vulnerability analysis for large-scale and congested road networks with demand uncertainty

To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.     

Traffic noise abatement: How different pavements, vehicle speeds and traffic densities affect annoyance levels

In this paper, annoyance ratings from traffic noise recorded on cobblestones, dense asphalt, and open asphalt rubber pavements are assessed with regard to car speeds and traffic densities. It was found that cobblestones pavements are the most annoying; also while open asphalt rubber pavement imposes less annoyance than dense asphalt it is not significantly different. Higher car speeds always lead to greater annoyance, as does higher traffic densities. LAeq and LAmax correlate well with annoyance, but loudness is the best predictor. Roughness and sharpness exhibit inconsistent interactions.     

Modelling the impact of weather conditions on active transportation travel behaviour

Three weather sensitive models are used to explore the relationship between weather and home-based work trips within the City of Toronto, focusing on active modes of transportation. The data are restricted to non-captive commuters who have the option of selecting among five basic modes of auto driver, auto passenger, transit, bike and walk. Daily trip rates in various weather conditions are assessed. Overall, the results confirm that impact of weather on active modes of transportation is significant enough to deserve attention at the research, data collection and planning levels.     

Estimating the robustness of questionnaire results: lessons from a mixed-mode survey of expectations for tele-working and road-based business travel

The robustness of questionnaire results to various forms of bias are explored in the context of a dual-mode (web and hardcopy) survey of employers’ anticipations of levels of employee commuting and business travel activity under a range of future ICT scenarios. The questionnaire incorporated several innovative features which, together with the dual-mode format, allowed an unusually wide range of analyses. For example: the robustness of respondents’ opinions was tested by examining the effect of incorporating alternative versions of a briefing text, one being very positive and one very negative, about the role of ICT; instrument bias was identified via detailed comparison of the results from the two versions of the questionnaire; and the impact of exogenous factors which are often ignored or taken as constant was assessed via special supplementary questions. Analysis showed that the robustness of opinions and expectations varied and was influenced by respondent characteristics, and that results from the two versions of the questionnaire differed significantly. It is concluded that opinions and expectations are less robust, and questionnaire results are more subject to bias and myopic interpretation, than is generally recognised and that web-based surveys seem particularly vulnerable to sampling bias. Methods are suggested for measuring robustness, for reducing bias and for validating and contextualising results. The use of contrasting briefing texts is recommended as a means of establishing the robustness of opinions and expectations while supplementary questions are recommended for validating and contextualising SP and SE exercises.

Second best toll and capacity optimisation in networks: solution algorithm and policy implications

This paper looks at the first and second best jointly optimal toll and road capacity investment problems from both policy and technical oriented perspectives. On the technical side, the paper investigates the applicability of the constraint cutting algorithm for solving the second best problem under elastic demand which is formulated as a bilevel programming problem. The approach is shown to perform well despite several problems encountered by our previous work in Shepherd and Sumalee (Netw. Spat. Econ., 4(2): 161–179, 2004). The paper then applies the algorithm to a small sized network to investigate the policy implications of the first and second best cases. This policy analysis demonstrates that the joint first best structure is to invest in the most direct routes while reducing capacities elsewhere. Whilst unrealistic this acts as a useful benchmark. The results also show that certain second best policies can achieve a high proportion of the first best benefits while in general generating a revenue surplus. We also show that unless costs of capacity are known to be low then second best tolls will be affected and so should be analysed in conjunction with investments in the network.

Identifying optimal data aggregation interval sizes for link and corridor travel time estimation and forecasting

With the recent increase in the deployment of ITS technologies in urban areas throughout the world, traffic management centers have the ability to obtain and archive large amounts of data on the traffic system. These data can be used to estimate current conditions and predict future conditions on the roadway network. A general solution methodology for identifying the optimal aggregation interval sizes for four scenarios is proposed in this article: (1) link travel time estimation, (2) corridor/route travel time estimation, (3) link travel time forecasting, and (4) corridor/route travel time forecasting. The methodology explicitly considers traffic dynamics and frequency of observations. A formulation based on mean square error (MSE) is developed for each of the scenarios and interpreted from a traffic flow perspective. The methodology for estimating the optimal aggregation size is based on (1) the tradeoff between the estimated mean square error of prediction and the variance of the predictor, (2) the differences between estimation and forecasting, and (3) the direct consideration of the correlation between link travel time for corridor/route estimation and forecasting. The proposed methods are demonstrated using travel time data from Houston, Texas, that were collected as part of the automatic vehicle identification (AVI) system of the Houston Transtar system. It was found that the optimal aggregation size is a function of the application and traffic condition.

Regulation of the informal transport sector in Rio de Janeiro,Brazil: welfare impacts and policy analysis

In Brazil, the explosion of informal transport activity during the past decade has had profound effects on formal public transport systems and is a source of great controversy in the urban transportation sector. A variety of policies have been proposed to manage the growth of the sector. This study seeks to understand how proposed policies will impact the users of these systems. A corridor in Rio de Janeiro with substantial informal activity was used as a case study. Measures of welfare changes in a discrete choice framework were used to estimate proposed policies’ impacts on users. Eleven candidate policies were evaluated, ranging from the eradication of the informal modes and investment in formal modes, to the legalization of the informal modes. Benefits were compared with costs and the distribution of benefits across income classes was explored. Net benefits from some policies were found to be substantial. Legalizing the informal sector was found to benefit users slightly but further investments in the sector are probably inefficient. Users benefited most from improvements in formal mass transit modes, at roughly 100–200 dollars per commuter per year. Finally, policies to foster a competitive environment for the delivery of both informal and formal services were shown to benefit users about 100 dollars per commuter per year. Together, the regulation of the informal sector and investments in the formal sector serve to reinforce the movement towards competitive concessions for services and help reduce the impacts of cartelization and costly in-road competition.