A variable speed limit model for freeway bridges considering the influence of both traffic service level and visibility in fog

Abstract

Fog often occurs on freeway bridges crossing rivers, reducing the drivers’ visibility and increasing the vehicles’ braking distance. Setting a reasonable speed limit under foggy conditions is required to ensure safe driving on freeway bridges. The traffic status also affects the speed limit in foggy conditions. Different from most existing variable speed limit (VSL) models that only considered the traffic condition or visibility in fog, this study modifies an existing VSL model by considering both traffic service level and visibility in fog on a river-crossing freeway bridge. The relationship between visibility and car-following distance is innovatively analyzed in our newly developed VSL model to meet the safe driving conditions more accurately. The E’dong Yangtze River Bridge is used as an example to evaluate the performance of our developed VSL model. The VISSIM simulation is applied to obtain the average and standard deviation of the speed difference of the VSL model. The standard deviation of following distance is included as the supplement to evaluate the safety benefits of the VSL model. The results of a multi-way ANOVA show that the new VSL strategy results in a lower average and standard deviation of the speed difference at a low traffic service level. The standard deviation of following distance indicates that the driver’s longitudinal maneuvering ability is improved under the new VSL model. Therefore, using the new VSL model can increase road traffic safety in fog. In addition, we preliminarily investigate the role of the model in reducing energy consumption and improving the operating efficiency using fuel consumption (FC) and traffic flow as indicators, respectively. The results show that the choice of speed limit strategy depends on the optimization objective. If environmental benefits are optimized, it is recommended to choose the new VSL strategy. If traffic efficiency is optimized, the new VSL strategy is suggested when the driving conditions are favorable (i.e., the visibility and traffic service level are high). In contrast, the strategy without VSL is a better choice for poor driving conditions (i.e., the visibility and traffic service level are low). This research provides a more scientific and reasonable VSL strategy in specific visibility and traffic service level conditions, thus is helpful for driving safety on freeway bridges.