• International Journal of Highway Engineering
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• v.17 no.6
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• pp.97-104
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• 2015

PURPOSES : Expressways experience chronic and recurring congestion, especially during weekends and holidays, because of the increased demands for leisure-related travel. The alternatives to solve chronic and recurring congestion may be three-fold: (1) physical expansion of expressway capacities, (2) road pricing, and (3) temporal and spatial distribution of traffic demands. Among these, the third alternative may be the most cost-effective method for the Korea Expressway Corporation (KEC) that can be achieved by using the existing ITS infrastructure. METHODS : KEC initiated a pilot study in which the traffic on congested expressways was managed by providing traffic condition information (i.e., travel times) of neighboring national highways for taking detours via variable message signs (VMS). This study aimed to estimate the detour rate, and the two pilot studies on Seohaean and Yeongdong expressways yielded many benefits. RESULTS : It was revealed that the total length of congestion segments decreased by 7.8 km, and the average travel speed increased by 5.3 km/h. CONCLUSIONS : Based on these findings, it was concluded that the propagation of detour information via VMSs during congestion hours can help reduce congestion on expressways and increase the benefits of the entire network.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.167-176
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• 2011

This study's purpose is to analyse factors of determination about detouring for makinga standard model in regard of unfavorableness and uncertainty when unspecified individual recipients make a decision at the time of course detour. In order to achieve this, we surveyed SP investigation whether making a detour or not for drivers as a target who take a high way and National highway. Based on this result, we analysed detour determination factors of drivers, establishing a combination model of Decision Tree and Neural Network model. The result demonstrates the effected factors on drivers' detour determination are in ordering of the recognition of alternative routevs, reliable and frequency of using traffic information, frequency of transition routes and age. Moreover, from the outcome in comparison with an existing model and prediction through undistributed data, the rate of combination model 8.7% illustrates the most predictable way in contrast with logit model 12.8%, and Individual Model of Decision Tree 13.8% which are existed. This reveals that the analysis of drivers' detour determination factors is valid to apply. Hence, overall study considers as a practical foundation to make effective detour strategies for increasing the utility of route networking and dispersion in the volume of traffic from now on.