The project will provide an opportunity to address key challenges related to user expectation of Automated and Connected Electric Shuttles. That is, the project will serve to advance the understanding of user perception and experience of smart shuttles in Canada. This technology is increasingly often being tested in pilots across Canada and it is critically to proactively understand the reaction of residents to this new technology.
This research aims to develop a novel transit signal priority (TSP) strategy under autonomous/connected vehicle environment to ease traffic congestion for transit vehicles at intersections. In this study, the accurate arrival time of transit vehicles at intersections will be estimated and the green time will be extended accordingly to help transit vehicles pass intersections. Moreover, the traffic flow of the crossing streets will be monitored constantly in order to decrease the adverse effect of TSP on traffic flow of crossing streets.
Airports in Canada have the difficult tasks of needing to remain open during adverse weather conditions in the winter. The research that we are undertaking is to develop and deploy a fully autonomous snow removal equipment for Canadian airports. Operating a snowplow is a dangerous and exhausting task for human operators, often they are unable to see clearly when they are operating in extreme conditions. Airports are also finding it increasingly more difficult to recruit and retain seasonal workers. A potential solution for these issues is a fully autonomous snow removal system.
Polymeric matrices containing nano-size additives have demonstrated remarkable mechanical, electrical, and thermal properties when compared to their micro-composite counterparts. Inserting graphene in a polymer matrix consisting of a glass fiber-reinforced resin is assumed to significantly increase the material electrical conductivity, which is needed in order to fulfill electrical conductivity requirements traditionally met by carbon black incorporation.
The public transportation system is crucial in alleviating urban congestion. The widespread of smart card automated fare collection (AFC) system produces massive data recording passengers day-to-day transport dynamic, which provides unprecedented opportunities to researchers and practitioners to understand and improve transit services. This project aims to make full use of the transit operational data (mainly smart card data) to enhance transit services. The main body of the research project is spatiotemporal behavior patterns mining.
With the recent advances in artificial intelligence, applying deep reinforcement learning to improve urban traffic efficiency and reduce traffic congestion has been gaining increasing interest in both academia and industry. This research program aims at developing computational platforms to evaluate models and algorithms for the next generation traffic control and management strategies, such as autonomous vehicles, vehicle-to-vehicle communication, and vehicle-to-infrastructure communication.
The automotive industry has recognized electric bike use as an integral part of the urban mobility of the future. To promote mass adoption of the integration of electric bikes with cars, the user perception of safety has to be improved. The objective of the proposed study is to investigate how aerodynamics and anxiety levels of cyclists influence the interaction of cyclists with other road vehicles and the impact on safety. To achieve this objective, studies will be conducted under controlled conditions in a full-scale climatic wind tunnel. Field studies will also be conducted on urban roads.
Seniors may experience social isolation when they lose the ability to drive their own car due to the loss of access to services and opportunities to socialize. I will examine the role of public transportation in reducing social isolation for seniors in Metro Vancouver. With BC’s aging population, the transportation needs of this demographic will become increasingly important over the coming decade. While many studies focus on how to ensure seniors can continue driving, this project will focus on barriers to other modes of transportation and programs or options to reduce these barriers.
This Mitacs research project will help develop a data collection strategy by identifying key variables such as the kinds of data sets and frequency of collection required. In addition, this Mitacs project will help determine what types of databases are required for data storage and which analytical procedures should be used on the data sets.
With the ever-increasing growth of the consumer Electric Vehicle (EV) market and environmental awareness of federal and provincial governments, electrification of public transit systems has come under the spotlight in recent years. Currently, there is limited practical knowledge on how to efficiently deploy EV buses across different Canadian regions, which results in a wide gap between advanced EV technology and Canadian environmental parameters.
EV batteries are negatively affected by cold temperatures, bad road conditions, and aggressive driving behaviours.
