Since 2008 most older people in England have benefited from unlimited area-wide free travel by bus after the morning peak period. The official policy rhetoric supporting implementation of the measure drew significantly on the need to reduce social exclusion amongst older people. However, despite a substantial increase in the number of concessionary journeys in England and the associated cost liabilities for local authorities and possibly also operators, there is currently only limited understanding of the wide ranging effects on bus use of providing a free pass, and in particular to whom benefits from the policy accrue. In part, this circumstance results from a methodological focus by evaluation studies hitherto that has emphasised aggregate-level data, often at the expense of the very rich contextual information about how the individual benefits from using a pass. This article presents insights into the perceptions, motivations and decisions relating to use of free bus passes, highlighting the existence of both tangible and intangible benefits which arise. It offers a fresh insight into previously undefined uses and benefits derived from possessing and using a concessionary bus pass. This article concludes by noting possible policy implications of the research in the context of the UK's ageing population and for other international contexts where the transport intervention of free bus travel is being considered.

A framework for the evaluation of the effectiveness of traffic diversion strategies for non-recurrent congestion, based on predictive guidance and using dynamic traffic assignment, is presented. Predictive guidance is based on a short-term prediction of traffic conditions, incorporating user reaction to information and guidance. A case study of the Lower Westchester County network in New York State, using DynaMIT-P, is presented to illustrate the application of the framework. DynaMIT-P is capable of evaluating diversion strategies based on predicted conditions, which take into account drivers' response to traffic information. The case study simulates the operations of predictive variable message signs positioned in strategic locations. DynaMIT-P is calibrated for the study network and used to establish base conditions for two incident scenarios in the absence of advanced traveller information systems. The effectiveness of predictive diversion strategies is evaluated (using rigorous statistical tests) by comparing traffic conditions with and without diversion strategies. The empirical findings suggest that incident diversion strategies based on predictive guidance result in travel time savings and increased travel time reliability.

As congestion pricing has moved from theoretical ideas in the literature to real-world implementation, the need for decision support when designing pricing schemes has become evident. This paper deals with the problem of finding optimal toll levels and locations in a road traffic network and presents a case study of Stockholm. The optimisation problem of finding optimal toll levels, given a predetermined cordon, and the problem of finding both optimal toll locations and levels are presented, and previously developed heuristics are used for solving these problems. For the Stockholm case study, the possible welfare gains of optimising toll levels in the current cordon and optimising both toll locations and their corresponding toll levels are evaluated. It is shown that by tuning the toll levels in the current congestion pricing cordon used in Stockholm, the welfare gain can be increased significantly, and furthermore improved by allowing a toll on a major bypass highway. It is also shown that, by optimising both toll locations and levels, a congestion pricing scheme with welfare gain close to what can be achieved by marginal social cost pricing can be designed with tolls being located on only a quarter of the tollable links.

Abstract

This paper uses observations from before and during the Stockkholm congestion charging trial in order to validate and improve a transportation model for Stockholm. The model overestimates the impact of the charges on traffic volumes while at the same time it substantially underestimates the impact on travel times. These forecast errors lead to considerable underestimation of economic benefits which are dominated by travel time savings. The source of error lies in the static assignment that is used in the model. Making the volume-delay functions (VDFs) steeper only marginally improves the quality of forecast but strongly impacts the result of benefit calculations. We therefore conclude that the dynamic assignment is crucial for an informed decision on introducing measures aimed at relieving congestion. However, in the absence of such a calibrated dynamic model for a city, we recommend that at least a sensitivity analysis with respect to the slope of VDFs is performed.

In Sweden, rail traffic is almost never separated according to speed. On several double-track lines the mix of heavy freight, regional and high speed trains imposes severe capacity problems. In order to evaluate the capacity for different traffic mixes, a combinatorial model - Timetable Variant Evaluation Model (TVEM) - has been developed. In this model both infrastructure and timetable are modelled as variables. Traffic is divided into train patterns according to a presumed regular timetable and then scheduled systematically in different time locations. The timetable variants are evaluated with regard to: mean values of capacity that give the number of trains/hr for the required mix, variance measures that show how the capacity depends on the timetable and scheduled delays that show the extension of run times imposed by overtaking. The paper shows how the important distance between adjacent overtaking stations can be sampled from Weibull distributions. TVEM has been used to evaluate three different operational cases with mixed traffic. The analysis shows that the impact on capacity from the infrastructure increases with speed difference and frequency of operation for passenger trains, while the importance of the infrastructure decreases when traffic is more heterogeneous. The impact from the timetable is strongest when the speed differences are low and/or the frequency of passenger trains is low. Capacity loss due to increased speed differences can be compensated for by additional overtaking stations. The slower trains suffer from a considerable increase in scheduled delays when speed differences increase.

In Sweden rail traffic is almost never separated according to speed. On several double-track lines the mix of heavy freight, regional and high speed trains imposes severe capacity problems. In order to evaluate the capacity for different traffic mixes a combinatorial model, TVEM (Timetable Variant Evaluation Model), has been developed. In this model both the infrastructure and the timetable are modelled as variables. The traffic is divided into train patterns according to a presumed regular timetable and then systematically scheduled in different time locations. The timetable variants are evaluated with regard to: mean values of capacity that give the number of trains/h for the required mix, variance measures that show how the capacity depends on the timetable and scheduled delays that show the extension of run times imposed by overtakings.

The paper shows how the important distance between adjacent overtaking stations can be sampled from Weibull distributions. TVEM has been used to evaluate three different operational cases with mixed traffic. The analysis shows that the impact on capacity from the infrastructure increases with speed difference and frequency of operation for the passenger trains, while the importance of the infrastructure decreases when traffic is more homogeneous. The impact from the timetable is strongest when the speed differences are low and/or the frequency of passenger trains is low. Capacity loss due to increased speed differences can be compensated for with additional overtaking stations. The slower trains suffer from a considerable increase in scheduled delays when speed differences increase.

Using a deliberative approach 228 members of the public from four locations in the United Kingdom took part in six focus groups that met on three occasions. Applying a model based on two interlocking sets of theories (Ajzen's Theory of Planned Behaviour and Bronfenbrenner's Ecological Systems Theory) in the analysis of participants' responses, the paper explores the social and environmental systems that an individual interacts with in the articulation of risky behaviours on the road. Participants discussed how taking risks changed over their lifecourse and how they became safer with age. Social norms and perceived behavioural control influence road user safety behaviour through the exchanging of attitudes, and younger drivers especially are more likely to embrace the symbolic role of the car. The paper concludes that the nature of identity and culture within risk taking is important when designing interventions on the ground.

This paper reviews and compares the performance of two dynamic transportation models - METROPOLIS and SILVESTER - which are used to predict the impacts of congestion charging for Stockholm. Both are mesoscopic dynamic models treating accumulation and dissipation of traffic queues, route choice, modal split and departure time choice. The models are calibrated independently for the baseline situation without charges and applied to forecast the effects of congestion charging. The results obtained from the two models are mutually compared and validated against the actual outcome of the Stockholm congestion charging scheme. Both models successfully predict the outcomes of the congestion charging trial at both aggregate and disaggregate levels. Results of welfare analysis, however, differ substantially due to differences in model specification.

Using the 2005 Dutch National Travel Survey data-set this paper investigates the influences of socio-demographics, journey patterns and built environment factors on the ratio of travel time and activity duration that an individual spends when engaging in work, daily shopping, non-daily shopping and sport/recreation activities. The results show that socio-demographics and other variables have unique influence on each type of activity. The travel-time ratios (TTRs) of some activities are more varied across the population whilst some have more 'acceptable' ratios. The interaction between activity duration and travel time is also unique for each socio-demographic group. For example, given the same amount of travel time, males will spend significantly less time on shopping than females; whilst for sports and recreational activities males will spend more time on than their female counterpart. By understanding individuals' different TTR values for different activities, the TTR can be an important guide when providing activity locations which in turn can help in creating sustainable urban transport conditions.

Using data from over 2000 convenience store customers within and outside London, this paper explores how individuals access their convenience stores and how significant the influence of their socio-demographics, shopping types and trip chaining is to their mode choice in visiting the stores. Trip chaining is found to be crucial in influencing customers' mode choice and their visit frequency. The application of logit models also shows that frequent shoppers are the ones most likely to visit the stores on foot. Interestingly, the estimation results also show that the location's density, shopping types and the day of the week are not significant in influencing travel modes. Customers who live in the most deprived areas are less likely to use a private car in visiting the stores.

Recent investment in urban ferry transport has created interest in what value such systems provide in a public transport network. In some cases, ferry services are in direct competition with other land-based transport, and despite often longer travel times passengers still choose water transport. This paper seeks to identify a premium attached to urban water transit through an identification of excess travel patterns. A one-month sample of smart card transaction data for Brisbane, Australia, was used to compare bus and ferry origin–destination pairs between a selected suburban location and the central business district. Logistic regression of the data found that ferry travel tended towards longer travel times (OR = 2.282), suggesting passengers do derive positive utility from ferry journeys. The research suggests the further need to incorporate non-traditional measures other than travel time for deciding the value of water transit systems.

Using a data-set collected among paratransit users in Bandung, Indonesia, this paper explores the impacts of paratransit users' negative experiences and dissatisfactions with their paratransit usage pattern. Segmentation and ordered probit analyses are used to examine the impacts of users' opinions on service quality on their trip-making behaviour. The results indicate that users are divided into six segments - namely, the unlucky, the young user, the experienced, the adapter, the infrequent user and the captive. The results further indicate that paratransit users, especially women, perceive negative experiences related to on-time performance (departure and arrival time) and security issues related to vehicles. Despite these dissatisfactions and negative experiences, they are still likely to use paratransit as part of their daily life. Two paratransit market segments (the adapter and the captive) are also likely to result in more trips using paratransit. The study offers several strategies and recommendations that can improve the current paratransit system so that it can better serve local needs.