Incomplete cost – incomplete benefit analysis in transport appraisal

This paper examines the current application of transport appraisal in the UK, in particular exploring the partiality of cost–benefit analysis (CBA) within the wider multi-criteria analysis (MCA) process. It argues that applying a quantitative assessment of the varied impacts of complex transport projects can only be partial within the CBA. Analysis can overlook social, human life, environmental and built environment impacts, and projects can be inconsistent with the planning strategy for an area. The application of CBA is critically reviewed using two case studies: the proposed upgrade of the South Fylde railway line and the Heysham-M6 Link Road, both from North West England. A participatory MCA process is suggested to help improve the process of transport appraisal, as part of an improved public debate on transport investment priorities.     

Calibrating a transit assignment model using smart card data in a large-scale multi-modal transit network

This paper describes a practical automated procedure to calibrate and validate a transit assignment model. An optimization method based on particle swarm algorithm is adopted to minimize a defined error term. This error term which is based on the percentage of root mean square error and the mean absolute percent error encompasses deviation of model outputs from observations considering both segment level as well as the mode level and can be applied to a large scale network. This study is based on the frequency-based assignment model using the concept of optimal strategy while any transit assignment model can be used in the proposed methodological framework. Lastly, the model is validated using another weekday data. The proposed methodology uses automatic fare collection (AFC) data to estimate the origin–destination matrix. This study combines data from three sources: the general transit feed specification, AFC, and a strategic transport model from a large-scale multimodal public transport network. The South-East Queensland (SEQ) network in Australia is used as a case study. The AFC system in SEQ has voluminous and high quality data on passenger boardings and alightings across bus, rail and ferry modes. The results indicate that the proposed procedure can successfully develop a multi-modal transit assignment model at a large scale. Higher dispersions are seen for the bus mode, in contrast to rail and ferry modes. Furthermore, a comparison is made between the strategies used by passengers and the generated strategies by the model between each origin and destination to get more insights about the detailed behaviour of the model. Overall, the analysis indicates that the AFC data is a valuable and rich source in calibrating and validating a transit assignment model.

     

Examining transport futures with scenario analysis and MCA

Climate change is a global problem and across the world the transport sector is finding it difficult to break projected increases in carbon dioxide (CO₂) emissions; there are very few contexts where deep reductions in transport CO₂ emissions are being made. A number of research studies are now examining the potential for future lower CO₂ emissions in the transport sector. This paper develops this work to consider some of the wider sustainability impacts (economic, social and local environmental) as well as the lower CO₂ transport impacts of different policy trajectories. Hence the central argument made is for an integrated approach to transport policy making over the longer term - incorporating scenario analysis and multi-criteria assessment (MCA) - to help assess likely progress against a range of objectives.The analysis is based on work carried out in Oxfordshire, UK. Different packages of measures are selected and two scenarios developed which satisfy lower CO₂ aspirations, one of which also provides wider positive sustainability impacts. A simulation model has been produced to help explore the strategic policy choices and tensions evident for decision-makers involved in local transport planning. The paper argues for a ‘strategic conversation’ (Van der Heijden, 1996) at the sub-regional and city level, based upon future scenario analysis and MCA, discussing the priorities for intervention. Such an approach will help us examine the scale of change and trade-offs required in moving towards sustainable transport futures.     

Household type and structure, time-use pattern, and trip-chaining behavior

In order to examine time allocation patterns within household-level trip-chaining, simultaneous doubly-censored Tobit models are applied to model time-use behavior within the context of household activity participation. Using the entire sample and a sub-sample of worker households from Tucson’s Household Travel Survey, two sets of models are developed to better understand the phenomena of trip-chaining behavior among five types of households: single non-worker households, single worker households, couple non-worker households, couple one-worker households, and couple two-worker households. Durations of out-of-home subsistence, maintenance, and discretionary activities within trip chains are examined. Factors found to be associated with trip-chaining behavior include intra-household interactions with the household types and their structure and household head attributes.     

Park-and-ride lot choice model using random utility maximization and random regret minimization

This research aims to understand the park-and-ride (PNR) lot choice behaviour of users i.e., why PNR user choose one PNR lot versus another. Multinomial logit models are developed, the first based on the random utility maximization (RUM) concept where users are assumed to choose alternatives that have maximum utility, and the second based on the random regret minimization (RRM) concept where users are assumed to make decisions such that they minimize the regret in comparison to other foregone alternatives. A PNR trip is completed in two networks, the auto network and the transit network. The travel time of users for both the auto network and the transit network are used to create variables in the model. For the auto network, travel time is obtained using information from the strategic transport network using EMME/4 software, whereas travel time for the transit network is calculated using Google’s general transit feed specification data using a backward time-dependent shortest path algorithm. The involvement of two different networks in a PNR trip causes a trade-off relation within the PNR lot choice mechanism, and it is anticipated that an RRM model that captures this compromise effect may outperform typical RUM models. We use two forms of RRM models; the classical RRM and µRRM. Our results not only confirm a decade-old understanding that the RRM model may be an alternative concept to model transport choices, but also strengthen this understanding by exploring differences between two models in terms of model fit and out-of-sample predictive abilities. Further, our work is one of the few that estimates an RRM model on revealed preference data.

     

Scheduling considerations for a branching transit route

This paper addresses the impacts of different scheduling alternatives for a branching transit route. It examines different schedule alternatives that might be used to optimize the route performance in terms of the passenger traveling time distributed among branch passengers and trunk‐line passengers. The schedule alternatives considered include transit vehicle allocation to different branches, offset shifting across vehicles on different branches, and vehicle holding (slack time) in the transit vehicle schedule. With these variables, several vehicle schedules are devised and examined based on a wide variety of possible passenger boarding scenarios using deterministic service models. Test outcomes provide general conclusions about the performance of the strategies. Vehicle assignment leading to even headways among branches is generally preferred for the case of low passenger demand. However, when passenger demand is high, or the differences between the passenger demands on branches are significant, unequal vehicle assignment will be helpful to improve the overall route performance. Holding, as a proactive strategy in scheduling, has the potential to be embedded into the schedule as a type of slack time, but needs further evidence and study to determine the full set of conditions where it may be beneficial. Offset shifting does not show sufficient evidence to be an efficient strategy to improve route performance in the case of low or high passenger demand.