Eco-Mobility and Empty Vehicle...

Eco-Mobility andEmpty Vehicle Management

Waldemar Grabski [email protected]

Institute of Computer Science, Warsaw University of Technology

mailto:[email protected]

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

http://www.eco-mobilnosc.pw.edu.pl/


Eco car

Exoskeleton

Wheelchairs


PRT system


PRT – Eco car



Eco car

Exoskeleton

Wheelchairs


PRT system


Exoskeleton



Eco car

Exoskeleton

Wheelchairs


PRT system

Electric wheelchair

Lever wheelchair


Wheelchairs



Eco car

Exoskeleton

Wheelchairs


PRT system

Model series of endoprosthesispre-prototype

Pre-prototype of the endoprosthesis filled with the bio-resorbable substance

Prototype of ankle-joint stabilizer





Eco car

Exoskeleton

Wheelchairs


PRT system

PRT - Scale physical model




Eco car

Exoskeleton

Wheelchairs


PRT system


PRT – Podcar and user interface



Eco car

Exoskeleton

Wheelchairs


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

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

http://ii.pw.edu.pl/feniks

Eco-Mobility and Empty Vehicle...

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