Skip to main content

PREDICT - Predictive Consolidated Transportation

The PREDICT project aims to increase resource efficiency and transport efficiency via predictive management of mixed-sized vehicles fleets for consolidated/shared transportation of people and goods.

Photo: Kai Pilger/Pexels

Purpose

Increase resource efficiency and transport efficiency via predictive management of mixed-sized vehicles fleets for consolidated/shared transportation of people and goods.

The project activities related to the projects aims are:

(1) Deep neural network based travel time and consolidated transport demand predictions and road network based propagation for routing; (2) optimized predictive fleet management (i.e., dispatch and re-positioning strategies/control) for mixed sized fleets using deep reinforcement learning, and (3) fleet management simulations based on 100s of millions of taxi request data in NYC.

The project is funded by ITRL. For more information, contact Gyözö Gidofalvi  or Jesper Provoost .

Read more

Page responsible:Malin Danielsson
Belongs to: Integrated Transport Research Lab (ITRL)
Last changed: Apr 20, 2021
ABE Södertörn
Automated Vehicle Traffic Control Tower: Phase 1
Automated Vehicle Traffic Control Tower: Phase 2
Digigoods
Elbilslandet 2.0
Electrification of the Handling of Building Material in the City
Electric Road Systems Engineering Toolbox (ERSET)
Future Scenarios for the Digitalised Road Freight Transport Landscape
Future Scenarios for the Development of Self-driving Vehicles in Sweden
Inductive bus-stop charging Södertälje
InterLink
KOMPIS - Combined Mobility as a Service in Sweden
KTH Mobility Pool
Mistra SAMS Living Lab 2
MMiB Modern Mobility in Barkarby
MOBY - Living lab e-micromobility
PREDICT - Predictive Consolidated Transportation
Research Concept Vehicle model E
RENO - Route Based ERS Network Optimization
RingRoad Logistics
SARA1
Self-driving vehicles and public transport – opportunities and barriers
SIMnVIS
Smart Mobility Needs Smart Governance
Sustainable Mobility Services Södertälje
System Level Impacts of AED for Long-term Transport Planning
System Level Impacts of Self-driving Vehicles
Test Site Stockholm
VMaRS - Values of MaaS Based on Representative Scenarios
ZEUS - Zero Emission off peak Urban distributionS