Pathfinding in Multi-dimensional Road Networks
Project Description
The criteria in multi-dimensional road networks are divided into two types: additive criteria (AC) and non-additive criteria (NAC). AC includes factors like travel time, distance, and carbon emissions, which are aggregated using a weighted sum to evaluate road segments. NAC, such as maximum edge height and lane occupancy rate, present a challenge in aggregation methods and may require other techniques like lexicographic or conjunctive/disjunctive methods.

The project's aim is to design an algorithm that efficiently handles queries involving both AC and NAC. For example, finding a path for a 40-ton truck that minimizes fuel consumption and keeps toll charges under $40, considering both AC (fuel and tolls) and NAC (weight limits of edges).
Supervisor
LIU, Ziyi
Quota
2
Course type
UROP1100
UROP2100
UROP3100
UROP4100
Applicant's Roles
We seek 2 students with an interest in spatial data indexing and query processing. Fundamental understanding of data structures, graph, and proficiency in C++ programming are highly recommended
Applicant's Learning Objectives
Project goals include:
1. Collecting and analysing real-world multi-dimensional road networks.
2. Reviewing current algorithms for multi-dimensional road networks.
3. Developing an effective algorithm to determine optimal paths considering both AC and NAC.
4. Conducting experiments and preparing detailed reports.
Complexity of the project
Challenging