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By raising the issue of data requirements for the purpose of modal development, validation and application, this study proposes an approach to calibrate choice model parameters in heterogeneous traffic condition using minimal empirical data. For this, a real-world scenario of Patna, India is chosen. For the calibration, a Bayesian framework-based calibration technique (CaDyTS: Calibration of Dynamic Traffic Simulations) is used. Commonly available, mode-specific, hourly-classified traffic counts are used to generate full day plans of agents and their initially unknown activity locations. While the proposed approach implements location choice implicitly, the approach can be applied to a variety of other problems. Further, the effect of household income is included in the utility function to incorporate the effect of income in the decision-making process of individual travelers and to filter out inconsistencies in the daily plans, which originate from the survey data. [ABSTRACT FROM AUTHOR]

• A bicycle superhighway is proposed for an urban area. • Algorithm to identify optimum number and locations of bicycle superhighway connectors. • Household income is included in the decision-making process of individual travellers. • The potential of increase in bicycle share is quantified. • Impact of BSH on emissions and accessibilities is visualised for policy implications. Bicycle is a sustainable low-carbon transport mode. However, insufficient or unplanned infrastructure leads to decrease in the share of bicycle in many cities of developing nations. In order to increase the bicycle share and to provide safer, faster and more direct routes, a bicycle superhighway is proposed for urban areas. This study identifies the potential of increase in the bicycle share. For maximum utilization of the new infrastructure, an algorithm is presented to identify the optimum number and locations of the connectors between proposed new infrastructure and existing network. Household income levels are incorporated into the decision making process of individual travellers for a better understanding of the modal shift. A real-world case study of Patna, India is chosen to show the application of the proposed superhighway. It is shown that for Patna, the bicycle share can escalate as high as 48% up from 32% by providing this kind of infrastructure. However, together with bicycles, allowing motorbikes on the superhighway limits the bicycle share to 44%. The increase in bicycle share is mainly a result of people switching from motorbike, public transport and walk to the bicycle. Further, to evaluate the benefits of the bicycle superhighway, this study first extends an emission modelling tool to estimate the time-dependent, vehicle-specific emissions under mixed traffic conditions. Allowing only bicyclists on the superhighway improves congested urban areas, reduces emissions, and increases accessibility. However, allowing motorbikes on the superhighway increases emissions significantly in the central part of the urban area and reduces accessibilities by bicycle mode to education facilities which are undesirable. This study elicits that a physically segregated high-quality bicycle superhighway will not only attract current non-cyclist travellers and increase the share of the bicycle mode, but will also reduce negative transport externalities significantly. [ABSTRACT FROM AUTHOR]