Red River College is hosting the inaugural Vehicle Technology International Conference, September 30 – October 2 at the Victoria Inn Hotel & Convention Centre in Winnipeg. RRC is excited to welcome a range of speakers who will be covering topics relating to the evolution and future of vehicle technology in Canada in beyond. Get to know one of the speakers, Ying Ying Liu, below:
“Nine years ago, I came to Canada as an immigrant from China. With a degree in Information Management and Systems, I worked at IBM China in business operation. I always had a fascination with the technical world and wanted to learn more about what happens behind the scenes. So when I came to Canada, I decided to start fresh by going back to school, where I embraced every single opportunity to learn.
After receiving my second bachelor’s degree in Computer Science with First Class Honours from the University of Manitoba in 2013, I went on to get my Master’s in 2016. I am now a PhD student. I have strong academic performance and a passion in solving real world problems with technologies. I also work at Manitoba Hydro as a system developer.
I joined InterDisciplinary Evolutionary Algorithmic Sciences (IDEAS) lab in 2013. My research areas are in computational intelligence, high performance computing, and distributed algorithms. My recent interest is in traffic-aware many objective dynamic route planning. I find this topic interesting because it is both theoretical and practical.
Individual vehicle routing refers to the task of finding the optimal travel path from place A to place B. With classical static routing algorithms, this problem is usually solved by finding the shortest path on a graph representing a road map with the weight of an edge representing the actual geometric distance between two junctions. A static routing algorithm is run once at the path planning stage and does not consider dynamic traffic information such as congestion, accidents and road closure.
As congestion becomes alarmingly severe in modern metropolitan areas, traffic-aware vehicle routing is one of the important problems in improving quality of life and building smart cities with higher productivity, less air pollution and less fuel consumption. In our problem setting, the road network is modelled as a graph with constantly changing edge weights, and a vehicle makes routing decision based on real-time and predictive traffic as it goes.
Our traffic-aware dynamic routing is composed of three steps:
- distributive road network clustering using real-time traffic
- traffic prediction at cluster level
- the vehicle incorporates the road network, clustering, and traffic information into its path planning algorithm to find a set of solutions for the optimizations of total vehicular emission cost (TEC), travel time, number of turns, and distance.
I would like to thank the organizers of the Vehicle Technology International Conference to give me the opportunity to present research work of the IDEAS lab. I look forward to attending the conference!”