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http://hdl.handle.net/1942/24225
Title: | Evaluation of Different Lane Separation Techniques Using Driving Simulator | Authors: | AWAN, Hammad BRIJS, Tom PIRDAVANI, Ali DECLERCQ, Katrien Alhajyaseen, Wael |
Issue Date: | 2017 | Source: | RSS2017 (Road Safety & Simulation International Conference), The Hague, The Netherlands, 17-19/10/2017 | Abstract: | In different countries, hard separation is adopted as a technique to separate express and local lanes. However, the use of hard separation can result in tiresome traffic jams in case of blockage. Emergency services are then required instantly to remove the blockage which might take a long time and possibly, affect the traffic in adjacent lanes as well. In this paper, a flexible approach which can be less susceptible to traffic jams called ‘soft separation’ which ensures the steady flow of traffic, is proposed and presented. Since, the evaluation of different traffic separations in the real world is difficult and requires considerable resources, an artificial environment using driving simulator is developed to evaluate the proposed treatment. It is an effective, efficient and economical approach to evaluate and compare different road design solutions. The primary variable of interest in this study was to observe drivers’ response during blockage of express lanes through the evaluation of drivers’ temptations to cross different types of soft separations during the traffic jam. Four types of separations were tested in the driving simulator: (1) solid double line (2) cross hatch marking (3) tubular delineators and (4) vegetation or grass strip. From a behavioral point of view, this study suggests that tubular delineators and a vegetation strip are the most effective types of separation in restricting drivers to cross. | Keywords: | managed lanes; soft separation; driving simulator | Document URI: | http://hdl.handle.net/1942/24225 | Category: | C2 | Type: | Conference Material |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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RSS2017_paper_56.pdf Restricted Access | Conference material | 1.32 MB | Adobe PDF | View/Open Request a copy |
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