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ITSReviewAnnual2015

www.its-ukreview.org 57 The ChoiceRail project During the ChoiceRail project, we worked with two key partners – Cotares, a Cambridge based SME with a novel patented real-time road routing algorithm, and the Centre for Transport and Society at the University of the West of England (UWE) who are established leaders in the understanding of the links between lifestyles and personal travel behaviour. Technically, the solution seemed quite simple: • Use Cotares’ road algorithm to find candidate interchange stations; • Create and populate a data model for car parking and modal interchanges; • Use the Trapeze public transport algorithm to find solutions from the candidate interchanges to the destination; • Build a set of results that removes duplicates and promotes diversity of results. The Cotares algorithm is able to find car journey times from a given origin to all 2000+ stations in the UK in less than half a second. Journey times are based on real-time road data giving an extra dimension of credibility. Early on in the project it became clear that this approach generated far too many candidate interchange stations – so the work focussed on identifying key ones. This then led to further questions about how to decide which are the best interchange stations – what is the car parking capacity, and is there availability at certain times of the day? What facilities exist at these stations? What frequency are the connecting rail services? It was evident that these questions are key to the decisions made by ‘real’ people when considering their travel options. We realised that some of the data didn’t exist that would enable us to answer these questions – or was commercially unrealistic to include. We resorted to using some pre-determined default values in lieu of any better data. As a result of the work undertaken, we were able to determine a set of journey options which could be presented to the user. In parallel to the development of the software demonstrator, UWE undertook some research which identified four notional journey types. These reflected the options that we expected the ChoiceRail algorithm to generate: • Drive only • Local station rail – journeys ostensibly by rail where the point of access to the rail network is close to the traveller’s origin – these are the options that existing journey planners provide, • Split modes – journeys which are distinctly part by car and part by train and notably where the share between modes is 50/50, and • Park and Ride – journeys ostensibly by car but where the traveller stops at a station short of their destination in order to continue the last part by train, bus or tram At this point in the project, it wasn’t yet clear which of these journey types the ChoiceRail algorithm would offer. We recognised the risk that when your public transport algorithm is allowed to offer car, that ‘drive only’ would always come out as the timeliest option. This wouldn’t have been an ideal outcome – not least because our clients are providers of public transport, or are Local Authorities encouraging modal shift towards public transport. UWE also looked at the types of travellers who might be interested in ChoiceRail as a solution. An initial set of focus groups highlighted five different traveller behaviours in relation to how road and rail are used in combination in practice: • Determined car driving – travellers wedded to driving for long distance journeys; • Local station train loving – travellers who adopt ‘no brainer’ train use for long distance journeys but who use a car to access ‘their’ station; • Evolutionary exploring – travellers  Trapeze’s established algorithm suffers from the very problem ChoiceRail set out to address 〉〉


ITSReviewAnnual2015
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