Congestion at motorway junctions is a traffic phenomenon that degrades operation of infrastructure and can lead to breakdown of traffic flow and associated reduction in capacity.Advanced communication technologies open new possibilities to prevent or at least delay this phenomenon, and innovative active traffic management systems have been developed in the recent years for better control of motorway traffic. This paper presents a review of control strategies for facilitating motorway on-ramp merging using intelligent vehicles. First, the concepts of the control algorithms are reviewed chronologically divided into three types of intelligent vehicle: completely automated, equipped with cooperative adaptive cruise control and equipped with on-board display. Then, a common structure is identified, and the algorithms are presented based on their characteristics in order to identify similarities, dissimilarities, trends and possible future research directions. Finally, using a similar approach, a review of the methods used to evaluate these control strategies identifies important aspects that should be considered by further research on this topic.

In the area of active traffic management, new technologies provide opportunities to improve the use of current infrastructure. Vehicles equipped with in-car communication systems are capable of exchanging messages with the infrastructure and other vehicles. This new capability offers many opportunities for traffic management. This paper presents a novel merging assistant strategy that exploits the communication capabilities of intelligent vehicles. The proposed control requires the cooperation of equipped vehicles on the main carriageway in order to create merging gaps for on-ramp vehicles released by a traffic light. The aim is to reduce disruptions to the traffic flow created by the merging vehicles. This paper focuses on the analytical formulation of the control algorithm, and the traffic flow theories used to define the strategy. The dynamics of the gap formation derived from theoretical considerations are validated using a microscopic simulation. The validation indicates that the control strategy mostly developed from macroscopic theory well approximates microscopic traffic behaviour. The results present encouraging capabilities of the system. The size and frequency of the gaps created on the main carriageway, and the space and time required for their creation are compatible with a real deployment of the system. Finally, we summarise the results of a previous study showing that the proposed merging strategy reduces the occurrence of congestion and the number of late-merging vehicles. This innovative control strategy shows the potential of using intelligent vehicles for facilitating the merging manoeuvre through use of emerging communications technologies.

Abstract-Emerging in-car communication technologies continually offer new communication capabilities between vehicles and infrastructure that, together with more accurate positioning systems, can be used to improve the use of current infrastructure. The aim of this paper is to present a novel merging assistant strategy that exploits cooperative systems to reduce congestion at motorway junctions. This new system, called Cooperative Merging Assistant, groups main carriageway vehicles together and collects the inter-vehicle spaces into gaps that are usable by merging traffic. These gaps will facilitate the coordinated entry of platoons of vehicles released by an on-ramp traffic signal. The performance of this new system is evaluated using microscopic simulation. Results show the reduction of late-merging vehicles, decrease in congestion and increase of merging capacity. This study shows how the use of cooperative systems can improve the the merging maneuver and so lead to a reduction of congestion on motorways.

A framework for assessing the usage and level-of-service of rail access facilities is presented. It consists of two parts. A dynamic demand estimator allows to obtain time-dependent origin-destination flows within pedestrian facilities. Using that demand, a traffic assignment model describes the propagation of pedestrians through the station, providing an estimate of prevalent traffic conditions in terms of flow, travel times, speed and density. The framework is discussed at the example of Lausanne railway station. For this train station, a rich set of data sources including travel surveys, pedestrian counts and trajectories has been collected in collaboration with the Swiss Federal Railways. Results show a good performance of the framework. Moreover, to underline its practical applicability, a six-step planning guideline is presented that can be used to design and optimize rail access facilities for new or existing train stations.