Modelling the Impact of New Mobility Trends and Technologies on Travel Behaviour and Demand

点击翻译按钮获取中文摘要

The transportation system is rapidly evolving in response to the development of new mobility trends and technologies. These technologies include autonomous vehicles (AVs), ride hailing and ride sharing services and micro mobility options like shared biked and e-scooters. There is also a movement towards integrating these mobility technologies as well as existing shared mobility tools like transit under a single technology-enabled ecosystem. This integration, commonly referred to as mobility as a service (MaaS) falls under the broad information and communications technology umbrella of NSERCs strategic areas of interest. The proposed research program will focus on developing predictive models that can be used to assess how new mobility technologies will change the transportation system. The models that are proposed will focus on predicting changes to travel behaviour and travel demand for urban residents. These models can be applied in a simulation framework to proactively test the impact of the introduction of policies that encourage safe, sustainable and cost-effective travel options for everyone living in an urban area. The models to be developed use best practice and new and novel methods. To develop the tools for this research, a data collection system will be established. The data collection will use different methods to capture different aspects of travel behaviour. Methods will include: 1.Global positioning system (GPS) and smartphone tracking apps used over an extended time frame; 2.A virtual reality study where respondents experience riding in an AV and other modes of transport; 3.A group decision making experiment where households negotiate how much to spend on mobility. These datasets will lead to behavioural models to predict: 1.The habitualness of travel patterns for the purposes of understanding the feasibility of prescheduling ride hailing services. 2.Does experiencing riding in an AV change users' perception of the viability of the technology? 3.How will households negotiate mobility expenditure if there are ride hailing services? HQP in this program will gain training in key areas including travel survey design and deployment, data processing, travel model development and policy assessment that are in high demand in the transportation planning and demand forecasting industry. These skills are widely applicable for transportation engineers in both research and practical contexts. Furthermore, the developed models will provide insights into policy development, allowing decision makers to test how effective a particular policy is within the model before implementation. These models will ideally help decision makers to understand how best to use AVs and MaaS. Canadians from all walks of life will benefit under this new system leading to broad positive social, economic and environmental outcomes.