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Eco-Mobility andEmpty Vehicle Management
Waldemar Grabski [email protected]
Institute of Computer Science, Warsaw University of Technology
Eco-Mobility project
Eco car
Exoskeleton
Wheelchairs
Stabilizers and endoprosthesis
PRT system
Eco-Mobility website http://www.eco-mobilnosc.pw.edu.pl/
• Performed in Faculty of Transport of Warsaw University of Technology and other faculties
• Co-financed by the European Regional Development Fund
• Chairman prof. Włodzimierz Choromański
Eco-Mobility project
Eco car
Exoskeleton
Wheelchairs
Stabilizers and endoprosthesis
PRT system
Eco-Mobility website http://www.eco-mobilnosc.pw.edu.pl/
PRT – Eco car
Eco-Mobility project
Eco car
Exoskeleton
Wheelchairs
Stabilizers and endoprosthesis
PRT system
Eco-Mobility website http://www.eco-mobilnosc.pw.edu.pl/
Exoskeleton
Eco-Mobility project
Eco car
Exoskeleton
Wheelchairs
Stabilizers and endoprosthesis
PRT system
Electric wheelchair
Lever wheelchair
Eco-Mobility website http://www.eco-mobilnosc.pw.edu.pl/
Wheelchairs
Eco-Mobility project
Eco car
Exoskeleton
Wheelchairs
Stabilizers and endoprosthesis
PRT system
Model series of endoprosthesispre-prototype
Pre-prototype of the endoprosthesis filled with the bio-resorbable substance
Prototype of ankle-joint stabilizer
Eco-Mobility website http://www.eco-mobilnosc.pw.edu.pl/
Stabilizers and endoprosthesis
Eco-Mobility project
Eco car
Exoskeleton
Wheelchairs
Stabilizers and endoprosthesis
PRT system
PRT - Scale physical model
Eco-Mobility website http://www.eco-mobilnosc.pw.edu.pl/
Eco-Mobility project
Eco car
Exoskeleton
Wheelchairs
Stabilizers and endoprosthesis
PRT system
Eco-Mobility website http://www.eco-mobilnosc.pw.edu.pl/
PRT – Podcar and user interface
Eco-Mobility project
Eco car
Exoskeleton
Wheelchairs
Stabilizers and endoprosthesis
PRT system
Corby modelEco-Mobility website http://www.eco-mobilnosc.pw.edu.pl/
PRT – Network simulator
PRT network simulator Feniks
• Statical network analysis• Total track length
• Average distance between stations
• Maximum walking distance
• …
PRT network simulator Feniks
• Massive simulations
• Automatization of the experiments• experiment generator
• simulation management
• global results database
PRT network simulation objectives
• Algorithms verification• Coordination
• Management (empty vehicle management)
• Network ridership
• Network capacity
Network structure
Quality,Performance
Parameters
?
Empty vehicles management
• Multiparamiter algorithm
• Adjustable factors and thresholds
• No central database of the status of stations and vehicles
• Horizon – maximal distance of communication
• Tailored for distributed implementation
Empty vehicle management tasks
Withdrawing
•moving unnecessary vehicles to capacitors
Expelling
•making room for approaching vehicles when the station is full
Balancing
• reallocation of vehicles for better accessibility
Calling
•delivering vehicles for waiting passengers
Empty vehicle management tasks
Withdrawing
•moving unnecessary vehicles to capacitors
Expelling
•making room for approaching vehicles when the station is full
Balancing
• reallocation of vehicles for better accessibility
Calling
•delivering vehicles for waiting passengers
Empty vehicle management tasks
Withdrawing
•moving unnecessary vehicles to capacitors
Expelling
•making room for approaching vehicles when the station is full
Balancing
• reallocation of vehicles for better accessibility
Calling
•delivering vehicles for waiting passengers
Empty vehicle management tasks
Withdrawing
•moving unnecessary vehicles to capacitors
Expelling
•making room for approaching vehicles when the station is full
Balancing
• reallocation of vehicles for better accessibility
Calling
•delivering vehicles for waiting passengers
Horizon experiment
JHorizon
City benchmark model
• Algorithm works well with average horizon
• Tailored for distributed implementation
Comparison with other algorithms
• Grid benchmark (known in the literature)
• Algorithms:• Distr - my distributed algorithm
• NN - Nearest Neighbours
• SD - Surplus/Deficit
• SV - Sampling and Voting
0.01
0.1
1
10
100
1000
0 0.2 0.4 0.6 0.8 1
LOG
( A
VER
AG
E W
AIT
ING
TIM
E)
RHO = DEMAND / MAX RIDERSHIP
Distr NN SD SV
Rzeszów - case study
• Town in south-eastern Poland
• Dense build-up in old town
• A town centre ring-road
Rzeszów – plan of the transportation system
• monorail and PRT - three-layer system• higher layer – monorail ring of 10.08 km
• middle layer – PRT highways (faster)
• lower layer – slower PRT
• Demand based on population statistical analysis• 352.11 requests/hour during rush hours (northern half)
• PRT - 140,84 groups/hour (avg. 2.5 persons in a group)
The town centre
Rzeszów - Monorail Calculations
• A train passes every 10 min – six trains needed
• Maximum ridership – 2251.5 passengers/h• Over three times greater than estimated
(704.22 requests/hour for the whole area)
The town centre
Rzeszów - PRT network (northern half)
monorail
ring
• 22 ordinary stations• demand of 4 groups/hour
• 6 PRT/monorail transfer stations• demand of 10 groups/hour
• Total 148 group/hour (close estimated value 140,84)
Rzeszów - PRT network simulations
• Maximum ridership (obtained by saturation experiment)• 35 vehicles – 385.7 trips/h max
• 45 vehicles – 493.3 trips/h max
• Safety margin = max ridership / input
• Maximum velocity• Highway 54km/h
• Commuter tracks 38.5km/h
Rzeszów case study conclusions
• Analysis for • Monorail (calculations)
• PRT network (simulations)
• 35 vehicles are enough to operate efficiently the PRT network(for the half of the monorail ring during rush hours)
• Proposed transportation system for central part of Rzeszów, is possible and reasonable
Further research
• Distributed simulator• Distributed simulation algorithm
• To use in farm environment (cloud) to perform massive simulations
• Examination co-operation between PRT and other means of transport
• Simulator and managing algorithm for dual-mode vehicles
Feniks simulator webpage http://ii.pw.edu.pl/feniks