Simulative Study of an Innovative On-Demand Transport System Using a Realistic German Urban Scenario
Abstract
:1. Introduction
2. Related Work
- the PRT traffic does not interfere with other traffic participants, because the PRT track is elevated to a higher level or hidden underground;because of the separation of the track from pedestrian traffic, the PRT system provides a high-level of safety. However, the investment costs for the infrastructure of PRT systems amounted to 30–100 M$/Mile, according to [10], because of the exclusivity and technical complexity of PRT tracks.
2.1. Scientific Research of DARP
2.2. Application Projects of DARP in Germany
3. FLAIT-Trains
4. Methodology
4.1. Aim and Key Figures
- average waiting time per passenger,
- maximum waiting time for a single passenger,
- average in-vehicle time per passenger,
- daily transportation productivity, and
- total annual service provider’s costs.
4.1.1. Average Waiting Time per Passenger
4.1.2. Maximum Waiting Time of a Single Passenger
4.1.3. Average In-Vehicle Time per Passenger
4.1.4. Daily Transportation Productivity
4.1.5. Total Annual Service Provider’s Costs
- infrastructure costs (Cin),
- vehicle costs (Cveh), and
- operating costs (Cop).
4.2. Simulation Scenario
4.2.1. Tram Route between Duisburg Central Station and Mülheim Central Station
4.2.2. Relevant Vehicles
4.3. Modelling and Simulation
4.3.1. Vehicle Models
Tram
FLAIT
4.3.2. Passengers
- the time to the second when the first passenger of this group departs;
- the to-the-second times until when the last passenger of that group departs;
- the number of group members;
- the street ID where the group departs;
- the stop where the group waits for tram or FLAIT train;
- the destination street ID where the group alights
4.3.3. Flexible Platooning
5. Results and Analyses
5.1. Average Waiting Time per Passenger
5.2. Maximum Waiting Time of a Single Passenger
5.3. Average In-Vehicle Time per Passenger
5.4. Daily Transportation Productivity
5.4.1. Mornings
5.4.2. Afternoons
5.4.3. Whole Day
5.5. Total Annual Service Provider’s Costs
6. Conclusions and Outlook
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Tram | Known On-Demand Transit | Taxi | FLAIT-Train | PRT | |
---|---|---|---|---|---|
Route | fixed | flexible | flexible | fixed | fixed |
Stop | fixed | w/o | w/o | w/o | fixed |
Schedule | fixed | by request | by request | by request | by request |
Ticket Cost | low | medium | high | low | low |
Mode | shared | shared | non-shared | shared 1 | shared 1 |
Seating Capacity | >100 | <50 | <7 | 2 | 2–4 |
Autonomous Level | no | no | no | automated | fully |
Track Usage | exclusive | mixed | mixed | exclusive | exclusive |
Reservation | not needed | often needed | not needed | not needed 2 | not needed |
Avg. Speed [kph] | 33.5 3 | 23 4 | 23 4 | 32 | 60 5 |
DVG GT-10 NC-DU | FLAIT | |
---|---|---|
Passenger Capacity | 176 | 2 |
Maximum Speed | 70 kph | 80 kph |
Normal Acceleration | 1.3 m/s2 | 2.5 m/s2 |
Normal Deceleration | −1.1 m/s2 | −2.5 m/s2 |
Name | Hourly Percentage Passenger Distribution [%] | ||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | |
TGw2_PKW [57] | 0.3 | 0.4 | 1.2 | 4.6 | 7.5 | 6.7 | 5.3 | 5.1 | 5.1 | 5.3 | 5.4 | 5.7 | 6.8 | 8.5 | 8.7 | 7.5 | 5.1 | 4.0 | 3.1 | 2.1 | 1.6 |
DU-MUE | 0.0 | 0.7 | 1.5 | 3.0 | 11.1 | 7.4 | 5.6 | 4.9 | 5.0 | 6.0 | 8.4 | 7.7 | 8.2 | 9.6 | 7.5 | 5.4 | 3.6 | 2.1 | 1.0 | 0.9 | 0.4 |
Tram | FLAIT-Train | |
---|---|---|
Pros |
|
|
Cons |
|
|
Time Period | Tram | 170 FLAIT-Train | |
---|---|---|---|
Passenger Capacity per Vehicle | - | 176 | 2 |
Average Waiting Time [min] | Mornings | 6.7 | 4.7 |
Afternoons | 7.0 | 3.9 | |
Whole Day | 6.9 | 4.2 | |
Maximum Waiting Time [min] | Mornings | 18 | 28.9 |
Afternoons | 30 | 26.5 | |
Whole Day | 30 | 28.9 | |
Average In-Vehicle Time [min] | Mornings | 7.7 | 5.2 |
Afternoons | 6.9 | 4.7 | |
Whole Day | 7.2 | 4.9 | |
Daily Transportation Productivity [Persons∙km/day] | Mornings | 511,146 | 724,937 |
Afternoons | 555,478 | 796,563 | |
Whole Day | 537,181 | 767,002 | |
Total Annual Costs [k€] | - | 9,278 | 2,956 |
Operator’s Annual Operating Costs [€/km] | - | 66.9 1 | 39.3 |
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Wang, S.; Weber, T.; Schramm, D. Simulative Study of an Innovative On-Demand Transport System Using a Realistic German Urban Scenario. Future Transp. 2023, 3, 38-56. https://doi.org/10.3390/futuretransp3010003
Wang S, Weber T, Schramm D. Simulative Study of an Innovative On-Demand Transport System Using a Realistic German Urban Scenario. Future Transportation. 2023; 3(1):38-56. https://doi.org/10.3390/futuretransp3010003
Chicago/Turabian StyleWang, Shen, Thomas Weber, and Dieter Schramm. 2023. "Simulative Study of an Innovative On-Demand Transport System Using a Realistic German Urban Scenario" Future Transportation 3, no. 1: 38-56. https://doi.org/10.3390/futuretransp3010003