Intelligent Systems for Sustainable Urban Mobility
Supported by: TBA
Investigators:
- Prof. J. Elder, York University (Project Leader)
- Prof. G. Sohn, York University
- Prof. P. Faloutsos, York University
- Prof. L. Fu, University of Waterloo
- Prof. J. Lewis, University of Waterloo
Industry Partners:
- Esri Canada
- Fugro Roadware
- Optech
- TransPlan
- Mircom
- Exascale Solutions
Public Sector Partners:
- Ontario Ministry of Transportation,
Intelligent Transportation Services Division - Ontario Ministry of Transportation,
Traffic Operations Division - York University Security Services
- York University Campus Services
The health of our cities depends on the freedom of citizens to move safely, efficiently and sustainably through the urban environment. Unfortunately, as our cities have grown this freedom has become challenged in a number of ways: sub-optimal management and planning of transit and roadways has led to congestion and excess greenhouse gas emissions, crime makes some areas unsafe at night when crowds are sparse, and those with disabilities find many routes closed to them.
A key requirement in meeting these challenges is the ability to measure, analyze, simulate, and visualize the movement of people through the 3D cityscape, regardless of their mode of transit (e.g., foot, wheelchair, bike, car, bus). The goal of the proposed project is to research, develop, evaluate and ultimately commercialize an integrated Intelligent System for Sustainable Urban Mobility (ISSUM) that provides this ability.
To find out more:
- Elasal, N. & Elder, J.H. (2016) Unsupervised Crowd Counting. Proceedings of the Asian Conference on Computer Vision.
- Tal, R. & Elder, J.H. (2012) An accurate method for line detection and Manhattan frame estimation, in J.I. Park and J. Kim, eds, ACCV Workshops, Part II, LNCS 7729, Springer-Verlag, Berlin, 580-593.
- Corral-Soto, E.R., Tal, R., Wang, L., Persad, R., Chao, L. Solomon, C., Hou, Y., Sohn G., Elder, J.H. (2012) 3DTown: The automatic urban awareness project, Canadian Conference on Computer and Robot Vision, IEEE Computer Society, Los Alamitos, CA, 433-440.