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Reducing the monotonous design in the worlds deepest and longest sub-sea road tunnel Rogfast, Norway
Published in Daniele Peila, Giulia Viggiani, Tarcisio Celestino, Tunnels and Underground Cities: Engineering and Innovation meet Archaeology, Architecture and Art, 2020
E39 Rogfast is a subsea tunnel that will pass below Boknafjorden in the south west of Norway between Harestad and Laupland, with a separate tunnel to the island Kvitsøy. The tunnel will become the worlds longest and deepest subsea road tunnel with a length of 26,7 km and its deepest point at approximately 392 meters below sea level. The 4 km long tunnel to Kvitsøy is connected by a two-level interchange at a depth of around 260 meters. E39 Rogfast is the first project to be constructed in the larger ambition to get a ferry-free highway along the European route E39 from Trondheim to Kristiansand. Upon completion the travel time between Stavanger and Bergen will be reduced by 40 minutes (StatensVegvesen, 2018). See Table 1 and Figure 1 for more information.
Reducing the monotonous design in the worlds deepest and longest sub-sea road tunnel Rogfast, Norway
Published in Daniele Peila, Giulia Viggiani, Tarcisio Celestino, Tunnels and Underground Cities: Engineering and Innovation meet Archaeology, Architecture and Art, 2019
E39 Rogfast is a subsea tunnel that will pass below Boknafjorden in the south west of Norway between Harestad and Laupland, with a separate tunnel to the island Kvitsøy. The tunnel will become the worlds longest and deepest subsea road tunnel with a length of 26,7 km and its deepest point at approximately 392 meters below sea level. The 4 km long tunnel to Kvitsøy is connected by a two-level interchange at a depth of around 260 meters. E39 Rogfast is the first project to be constructed in the larger ambition to get a ferry-free highway along the European route E39 from Trondheim to Kristiansand. Upon completion the travel time between Stavanger and Bergen will be reduced by 40 minutes (StatensVegvesen, 2018). See Table 1 and Figure 1 for more information.
Economic analysis of mobility improvements
Published in Zongzhi Li, Transportation Asset Management, 2018
Unconventional intersections: The search for innovative methods to improve traffic channelization at intersections begins with assessing existing unconventional intersection designs. The existing designs have primarily focused on improving left-turn traffic movements to flow and safety. They can be classified into two broad categories: unconventional at-grade intersection designs and unconventional overpass/underpass and interchange designs. Typical unconventional at-grade intersection design options include doublewide, continuous flow, median U-turn, and superstreet intersections.
How does interchange affect passengers’ route choices in urban rail transit? – a case study of the Shanghai Metro
Published in Transportation Letters, 2022
Yan Cheng, Xiafei Ye, Taku Fujiyama
Interchange provides more flexibility as passengers potentially have more feasible routes to choose from. For some OD station pairs having direct routes, routes with interchange are also competitive thanks to less time and/or crowdedness. However, it cannot be denied that interchange itself still causes inconvenience, which may lessen the appetite of passengers to use such routes (Lam and Xie 2002). The influence of interchange is mainly quantified at single-interchange and route levels. Weighted walking time between services, weighted waiting time for the connection and pure penalty, i.e. the inconvenience and risks involved in interchange, are commonly distinguished as three components of interchange disutility (Wardman and Hine 2000). Two major issues with this conception are its simplification of the pure penalty and neglect of the influence of passenger perception.
Identification of contributing factors for interchange crashes based on a quasi-induced exposure method
Published in Journal of Transportation Safety & Security, 2022
Xin Gu, Mohamed Abdel-Aty, Jaeyoung Lee, Qiaojun Xiang, Yongfeng Ma
Interchanges are one of the most important highway facilities in connecting two or more major highways with an uninterrupted traffic flow. However, interchanges on freeways/expressways have been considered more dangerous than other basic segments because of drivers’ decision-making to stay or exit, weaving, variations in speeds, etc. (Gu, Abdel-Aty, Xiang, Cai, & Yuan, 2019; Wang, Hu, & Zhang, 2016; Yang, Liu, Chan, Xu, & Guo, 2019; Yuan, Abdel-Aty, Cai, & Lee, 2019; Zhang, Chen, et al. 2018). Evidence shows that interchange-related fatal crashes constitute 21.8% of fatal crashes on or related to the freeway system (Torbic, Harwood, Gilmore, Richard, & Bared, 2009). Hence, it would be necessary to identify risk factors affecting crashes at interchanges and understand the impact of these factors, which is beneficial for the implementation of targeted countermeasures to improve the safety of interchanges.
Speed distribution and safety effects of license plate recognition: Analysis combining crash and toll record data in Hunan Province, China
Published in Journal of Transportation Safety & Security, 2021
Zeming Yu, Hanchu Zhou, Helai Huang, Ye Li, Jia Qu
In order to record vehicle driving routes intuitively, the visual expressway network in Hunan province is structured based on the ArcGIS software. Only toll plazas and interchanges are drawn as nodes on the map to divide the expressway network into different segments. The toll plaza is the only passageway between expressways and normal highways, and every vehicle has to pass a tollbooth to enter the expressway network. Like intersections, the interchange is built to connect different expressway segments. A total of 443 toll stations and 46 interchanges as nodes divide the network, which results in 529 segments. The only routes between different toll plazas are fixed as the shortest path. The Dijkstra algorithm was used to find the shortest paths between two toll plazas. Then the routes for toll records between toll plazas were transformed to the trajectories between toll nodes. The count of trajectories in each segment is used as the surrogate value of traffic volume. Figure 1 shows the records of vehicle travel. The colors of the line from green to red represent the vehicle volume summed from low to high.