Contest No. 3

IoT-based Ride-sharing Systems

Description:

This contest is focused on ‘optimal spatio-temporal trip scheduling for each member of ride-sharing system (passengers and drivers) based on IoT technology in the District 6 of Tehran (https://goo.gl/maps/8V4yTEq867UmqyE67)’. One of the biggest problems today in Tehran is the growing number of passenger vehicles/cars which is proportional with the growth of the population and which causes major traffic congestions, noise and increase the travelling time. Ride-sharing is the transport model which enables ride-share of a single vehicle for multiple passengers. All passengers share the same or similar starting point and they share the ride in order to reduce the number of vehicles on the road and to reduce their travelling expenses. Accordingly, the individual steps of optimal spatio-temporal trip scheduling could be as follows:

a-      Optimal spatio-temporal clustering and matching between the passengers and drivers:

(The position, time, movement speed and direction of all the individuals are measured and transferred by internet-based geo-sensors. Also all the estimations and calculations should be carried out automatically).

b-      Alarming the passengers and drivers automatically (by sending message, calling or vibrating).

c-      Confirming the proposed cluster by the passengers.

d-     Optimum shared-pathfinding (origins-destinations) for each clusters trip.

e-      Using AR (Augmented Reality) for showing the matched car or passenger (when it is near enough) is recommended.

f-       Evaluating the system performance according to the minimum cost according to the time trip, maximum members in each trip, maximum response efficiency.

g-      Writing a technical report by describing all operational individual steps.

All these steps would be accomplished by the following datasets:

Dataset1: position, time, movement speed and direction of drivers.

Dataset2: position, time, movement speed and direction of passengers, their origins and destinations with the maximum and minimum required time for trip.

Evaluation Criteria:

The following criteria are considered for the evaluation of the accomplished tasks:

-          The optimality of spatio-temporal clustering and also matching between the passengers and drivers (Number of clusters, optimal statistical distribution of passengers in clusters, distance between the passengers and driver in a cluster, and any other parameters that could be considered for optimality).

-          The optimality of shared-pathfinding (statistical evaluation of all pathfinding’s required times.

-          Using AR (Augmented Reality) for showing the matched car or passenger (when it is near enough).

-          To develop and use your own program code (preferably open source) instead of using existing commercial tools.

-          Mobile platform is preferred.

-          A comprehensive technical report (in Persian or English).

-          Level of scientific innovation.

Data availability:

The web link for downloading the point cloud data will be available upon the completion of the registration form.