Presentation of GYM project in the 7th Research Activity Day of University of Thessaly, Volos, Greece.

1. UNIVERSITY OF THESSALY
SCHOOL OF ENGINEERING
GreenYourMove: Development and promotion of
a co-modal journey application to minimize GHG
emission in Europe
Antonios Fragkogios
PhD Candidate
Georgios K.D. Saharidis
Assistant Professor
DEPARTMENT OF MECHANICAL ENGINEERING
Division of Production Management & Industrial Administration
7η Ημερίδα Ερευνητικής Δραστηριότητας Πολυτεχνικής Σχολής Πανεπιστημίου
Θεσσαλίας, 23 Μαΐου 2019, Βόλος
With the contribution of the LIFE
programme of the European Union -
LIFE14 ENV/GR/000611

2. PRESENTATION STRUCTURE
2

3. 3

4. 4
Main Outcomes:
Web and SmartPhone application for green journey
planning in Greece, Czech Republic and Slovakia
Database of Greek transport network
Promotion of co-modality
Ticketing options
Synchronization of timetables

5. 5
Consortium:
University ofThessaly, Greece (www.mie.uth.gr)
AVMap, Greece (www.avmap.gr)
CHAPS, Czech Republic (www.chaps.cz )
EMISIA S.A., Greece (www.emisia.com)
INPROP, Slovakia (www.inprop.sk)
TRAINOSE, Greece (www.trainose.gr )
Co-funded:
LIFE (https://ec.europa.eu/easme/en/life)
Green Fund Hellas (www.prasinotameio.gr/index.php/el/)
Duration: Sep 2015 –Aug 2019
Total Bugdet: 1,245,052€

6. 6
Implementation Actions:
 Development of emission calculation models.
 Development of a database of Greek network.
 Timetable Synchronization.
 Development of optimization algorithm to solve the green co-modal
problem.
 Development of web and smartphone app for co-modal routing in Greece.
Dissemination Actions:
 Awareness campaign.
 Publications,Website, Press Releases,Videos etc.
Monitoring Actions:
 Development of emission inventory methodology
 Environmental and socio-economic impact monitoring of the project

7. 7
Novel emission calculation models cater for co-modality:
 Road gradient
 Occupancy rate
 Wind velocity and direction
 Heat Index – A/C use
 Visibility
 Road condition / quality
 Speed class

8. 8
Database of Greek network:
 Development of a database including GTFS as well as data related to
emission calculation
 Data updating system-web based platform (Improved GTFS editor)
 GeneralTransit
Feed Specification
(GTFS):
 agency
 routes
 trips
 stop_times
 stops
 shapes
 calendar

9. 9
Database of Greek network:
 Cooperation of University of
Thessaly and 24Transport
Operators.
Database of EU network:
 European GTFS data from 11
different EU regions.
 Cyprus
 The Netherlands
 Luxemburg
 Esthonia
 Switzerland
 Denmark
 Sweden

10. 10
1. Pre-Optimization Stage
2. Mathematical Model
3. Post-Optimization Stage

11. 11
 Co-Modality
1 Athens 16 Alexandria
2 Thiva 17 Veria
3 Livadeia 18 Naoussa
4 Paleofarsalos 19 Skidra
5 Larissa 20 Edessa
6 Katerini 21 Amintaio
7 Thessaloniki 22 Florina
8 Kilkis 23 Volos
9 Serres 24 Karditsa
10 Drama 25 Trikala
11 Xanthi 26 Kalampaka
12 Komotini 27 Lamia
13 Alexandroupoli 28 Chalkida
14 Didimoticho 29 Korinthos
15 Orestiada 30 Patra
 Intermediate nodes

12. 12
• Athens to Piraeus
Old ± 5 ±15 ±45 New
1 5:58
2 6:53 6:58 7:03 7:28 6:58
3
4 7:53 7:58 8:07 8:28 7:58
5 8:58
6 9:53 9:57 10:07 10:28 9:58
7 10:58
8 11:53 11:56 11:58 13:28 11:58
9 12:58
10 13:53 13:57 14:05 14:28 13:58
11 14:58
12 15:53 15:56 16:01 16:28 15:58
13 16:58
14 17:53 17:58 17:59 18:27 17:58
15 18:58
16 19:53 20:57 19:59 20:27 19:58
17 20:58
18 21:53 21:58 21:59 22:27 21:58
19 23:53 23:49 23:40 23:17 23:03
3.9% 5.4% 12.2%
• Athens to Chalkida
Old ±5 ±15 ±45 New
1 04:27 04:32 04:42 04:58 04:51
2 06:44 06:39 06:50 06:19 06:51
3 08:44 08:40 08:52 08:32 08:51
4 10:44 10:41 10:52 10:58 10:51
5 12:44 12:39 12:50 12:05 12:51
6 14:44 14:41 14:52 14:54 14:51
7 16:44 16:39 16:51 16:12 16:51
8 18:44 18:40 18:50 18:45 18:51
9 20:44 20:49 20:52 20:42 20:51
10 22:44 22:49 22:30 22:02 21:51
3.4% 6.9% 10.2%

13. 13
Problem: Environmental co-modal journey planning.
Data-agnostic and cross-platform compatible.
Solution approaches:
 2 exact solution approaches
 2 exact solution approaches based
on decomposition techniques
 2 heuristic approaches
 3 hybrid solution approaches
Optimization Criteria:
 Minimize the arrival time (Earliest Arrival)
 Minimize the travel time
 Minimize the environmental impact (i.e. ecological footprint) of the journey

14. 14
Approach name
Holistically
considers data/
Contains
precomputation
Precomputation
time (in secs)
Average
CPU time
for 30
queries
(in secs)
Min CPU
time for
30 queries
(in secs)
Max CPU
time for
30 queries
(in secs)
Exact Approach
1
No/No - 858.07 471.40 5763.89
Exact Approach
2
No/No - 125.62 118.93 170.94
Hybrid
Approach 1
Yes/Yes 28.89 74.32 5.86 211.49
Decomposition
Technique 1
No/No -
47.35
43.59 52.69
Heuristic
Approach 2
Yes/Yes 28.89 39.32 1.74 510.97
Hybrid
Approach 2
Yes/Yes 222.85 26.32 20.97 32.01
Decomposition
Technique 2
No/No -
15.96
12.44 21.55
Heuristic
Approach 1
Yes/Yes 222.85 13.05 0.11 25.92
Hybrid
Approach 3
Yes/Yes 8.59 6.12 3.38 8.48

15. 15
1. http://greenyourmove.eu/

16. 16
1. http://greenyourmove.eu/

17. 17
1. http://greenyourmove.eu/

18. 18
1. http://greenyourmove.eu/

19. 19
Download the
Application:
GreenYourMove

20. 20
Thank you for your attention.
Antonios Fragkogios
PhD Candidate
With the contribution of the LIFE
programme of the European Union -
LIFE14 ENV/GR/000611