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Urban traffic management utilizing soft measures: A case study of Volos city
dc.creator | Karatsoli M., Karakikes I., Nathanail E. | en |
dc.date.accessioned | 2023-01-31T08:31:53Z | |
dc.date.available | 2023-01-31T08:31:53Z | |
dc.date.issued | 2019 | |
dc.identifier | 10.1007/978-3-030-02305-8_79 | |
dc.identifier.isbn | 9783030023041 | |
dc.identifier.issn | 21945357 | |
dc.identifier.uri | http://hdl.handle.net/11615/74467 | |
dc.description.abstract | This paper examines the current and the future performance of the traffic network around the center of the city of Volos in Greece, after the implementation of local traffic management measures and the introduction of innovative Intelligent Transportation System (ITS) services. The study focuses on the urban road of two main streets Iasonos (up to Fillelinon street) and Dimitriados (section between Fillelinon and Athanasiou Diakou streets) where during the peak hours, congestion results in high delays, bottlenecks and conflicts. System performance is based on specific indicators, which have been set to evaluate the traffic situation in the three main areas of interest: traffic quality, safety and environment. An investigation on the current and potential problems of the study area has been performed, by modeling the current situation (base scenario) in the microsimulation software VISSIM and using the “Surrogate Safety Assessment Model” (SSAM) to assess the traffic safety. The findings were low quality of signal control, low compliance of drivers to traffic laws (illegal and unregulated parking, trespassing of the bus lane), critical safety hotspots and increased emissions. “Soft” countermeasures are simulated and evaluated in VISSIM. Such “soft” countermeasures are the ban of access to Urban Freight Transport (UFT) vehicles during the peak hours, the adoption of ITS to prevent illegal parking, the adjustment of the coordination time offset. Apart from evaluating the impact of the countermeasures, the paper constitutes also a roadmap for achieving overall improvement of an urban traffic network without resulting into the construction of new transport infrastructure. © Springer Nature Switzerland AG 2019. | en |
dc.language.iso | en | en |
dc.source | Advances in Intelligent Systems and Computing | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059021212&doi=10.1007%2f978-3-030-02305-8_79&partnerID=40&md5=2e694e1d7de54fac1a6854f307461ec7 | |
dc.subject | Accident prevention | en |
dc.subject | Advanced traffic management systems | en |
dc.subject | Compliance control | en |
dc.subject | Crime | en |
dc.subject | Freight transportation | en |
dc.subject | Intelligent systems | en |
dc.subject | Network performance | en |
dc.subject | Quality control | en |
dc.subject | Traffic congestion | en |
dc.subject | Traffic signals | en |
dc.subject | Traffic surveys | en |
dc.subject | Assessment | en |
dc.subject | Intelligent transportation systems | en |
dc.subject | Traffic flow | en |
dc.subject | Traffic safety | en |
dc.subject | Transport infrastructure | en |
dc.subject | Urban freight transport | en |
dc.subject | Urban traffic management | en |
dc.subject | Urban traffic networks | en |
dc.subject | Urban transportation | en |
dc.subject | Springer Verlag | en |
dc.title | Urban traffic management utilizing soft measures: A case study of Volos city | en |
dc.type | conferenceItem | en |
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