Sustainable Transport: An Efficient Transportation Network—Case Study
Abstract
:1. Introduction
2. Literature Review
- Reduced travel needs
- Transport policy shift
- Distance reduction
- Technological innovation that would increase efficiency [14].
3. Materials and Methods
4. Results and Discussion
4.1. Examples of Model Transport Networks
4.2. Transport in Vilnius
4.3. Sustainable Transport Solutions for Vilnius
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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The Coventional Approach (Transport Planning and Engineering) | An Alternative Approach (Sustainable Mobility) |
---|---|
Physical dimensions | Social dimensions |
Mobility | Accessibility |
Traffic focus, particularly on the car | People focus, either in (or on) a vehicle or on foot |
Large in scale | Local in scale |
Street as a road | Street as a space |
Motorized transport | All modes of transport often in a hierarchy with pedestrians and cyclists at the top and car users at the bottom |
Forecasting traffic | Visioning on cities |
Modeling approaches | Scenario development and modeling |
Economic evaluation | Multicriteria analysis to take account of environmental and social concerns |
Travel as a derived demand | Travel as a values activity as well as a derived demand |
Demand based | Management based |
Speeding up traffic | Slowing movement down |
Travel time minimization | Reasonable travel times and travel time reliability |
Segregation of people and traffic | Integration of people and traffic |
Indicator | 1999 | 2005 |
---|---|---|
Street network density (km/km2) | 1.9 | 2.4 |
Public transport density (km/km2) | 0.55 | 0.62 |
Bicycle paths networks density (km/km2) | 0.10 | 0.16 |
Average traffic flow in peak hours (aut./h) | 1275 | 1521 |
Percentage of trucks in average flow | 3.4 | 2.4 |
Average speed in peek traffic flow (km/h) | 37.5 | 29.3 |
Modal split | ||
-pedestrian trips % | 31.3 | 34.8 |
-trips by bicycles % | 0.3 | 0.3 |
-trips by public transport % | 45.4 | 34.2 |
-trips by car % | 23.0 | 30.7 |
Maximum number of public transport passengers in peak hours | 5300 | 3600 |
Transit of trucks in peak hours % | 21.3 | 13.2 |
Number of traffic accidents for 1000 inhabitants | 1.07 | 1.77 |
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Ogryzek, M.; Adamska-Kmieć, D.; Klimach, A. Sustainable Transport: An Efficient Transportation Network—Case Study. Sustainability 2020, 12, 8274. https://doi.org/10.3390/su12198274
Ogryzek M, Adamska-Kmieć D, Klimach A. Sustainable Transport: An Efficient Transportation Network—Case Study. Sustainability. 2020; 12(19):8274. https://doi.org/10.3390/su12198274
Chicago/Turabian StyleOgryzek, Marek, Daria Adamska-Kmieć, and Anna Klimach. 2020. "Sustainable Transport: An Efficient Transportation Network—Case Study" Sustainability 12, no. 19: 8274. https://doi.org/10.3390/su12198274
APA StyleOgryzek, M., Adamska-Kmieć, D., & Klimach, A. (2020). Sustainable Transport: An Efficient Transportation Network—Case Study. Sustainability, 12(19), 8274. https://doi.org/10.3390/su12198274