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No description available.

Traffic congestion on urban road networks has been recognized as one of the most serious problems with which modern cities are confronted. It is generally anticipated that Dynamic Route Guidance Systems (DRGS) will play an important role in reducing urban traffic congestion and improving traffic flows and safety. One of the most critical issues in designing these systems is in the development of optimal routing strategies that would maximize the benefits to overall system as well as individual users. Infrastructure based DRGS have advantage of pursuing system optimal routing strategy, which is more essential under abnormal traffic conditions such as non-recurrent congestion and natural disaster. However user compliance could be a problem under such a strategy, particularly when some of equipped drivers are urged not to choose minimum travel time path for the sake of improving the total network travel time. On the other hand, In-vehicle based DRGS can utilize the user-specified route selection criteria to avoid "Braess Paradox" under normal traffic conditions. However, it may be of little use under abnormal traffic conditions and high DRGS market penetration. In conducting the comparative analysis between system optimal strategy and user equilibrium strategy, significant differences were found within the mid-range traffic demand. The maximum total travel time difference occurs when the level of traffic demand is half of the system capacity. At this point, system optimal route guidance strategy can save more than 11% of the total travel time of user equilibrium route guidance strategy. The research proposes an adaptive routing strategy as an efficient dynamic route guidance under non-recurrent traffic congestion. Computation results show that there is no need to implement system optimal routing strategy at the initial stage of the incident. However, it is critical to use system optimal routing strategy as freeway and arterial are getting congested and the queue delay in freeway increases. The adaptive routing strategy is evaluated using Traffic simulation model, INTEGRATION. According to simulation results using an ideal network, the travel time saving ratio is maximum when both arterial and freeway have normal traffic demand under incident. In case of a realistic network, the adaptive routing strategy also proved to save the total travel time between 3% to 10% over the traditional user equilibrium routing strategy. The reduction of total travel time increases as the incident duration increases. Consequently, it is concluded that the adaptive routing strategy for DRGS is more efficient than using user equilibrium routing strategy alone. / Ph. D.

Les conditions de circulation sur un réseau routier subissent souvent de la congestion. Selon ses sources, la congestion routière peut être classée en deux catégories : la congestion récurrente déterminée par les lois de trafic et la congestion non-récurrente due aux incidents, accidents ou autres aléas sur la route. Grâce à l'avancement des technologies, notamment en informatique, communication et techniques de traitement des données, l'exploitant est devenu capable de détecter les perturbations, de mesurer les effets et même d'anticiper l'état du trafic afin de mieux adapter ses actions d'exploitation. L'information dynamique concernant les conditions de trafic permet aux usagers de réduire l'inconfort et d'effectuer leur choix d'itinéraire de manière plus raisonnable. Pour l'exploitant, le service d'information aux usagers peut servir à la gestion du trafic. Nous avons étudié la contribution potentielle de l'information dynamique au profit individuel des usagers et à la performance collective du système en prenant en compte : i) la congestion récurrente et non-récurrente ; ii) des différents comportements de choix d'itinéraire en fonction de l'accessibilité à l'information ; iii) d'autres actions de gestion du trafic menées par l'exploitant. Un modèle théorique avec une application analytique sur un réseau élémentaire de deux routes parallèles, une paire origine-destination et deux classes d'usagers respectivement informée ou non-informée nous a permis de retirer de nombreuses indications : i) la diffusion excessive de l'information avec un contenu « neutre » dégrade à la fois le profit individuel et la performance du système ; ii) l'information dynamique avec certain contenu « coopératif » peut contribuer l'optimisation du système sans causer le problème d'acceptabilité ; iii) l'information dynamique et d'autres mesures de gestion dynamique s'interagissent de manière complémentaire à l'optimisation du trafic / Traffic conditions on a road network often suffer from congestion. According to sources, the traffic congestion can be classified into two categories : recurrent congestion determined by the physic laws of traffic and non-recurrent congestion due to incidents, accidents or other hazards on the road. Thanks to the advancement of technologies, including computers, communications and data processing, the traffic operator is now able to detect disturbances, to measure the effects and even to anticipate traffic conditions to better match traffic management activities. Dynamic information on traffic conditions enables users to reduce discomfort and make their route choice decision more reasonable. For the operator, the service user information may be used as a traffic management tool. We investigated the potential contribution of dynamic traffic information for the benefit of individual users and system performance by taking into account : i) recurring congestion and non-recurring ; ii) different route choice behaviours based on accessibility to information service ; iii) other traffic management actions taken by the traffic operator. A theoretical model with an analytical application on a simple two-parallel-road network, an origin-destination pairs and two user classes, respectively-informed or non-informed has given many conclusions : i) an excessive distribution of traffic information with a « neutral » content damages both the individual profit and system performance ; ii) traffic information with some « cooperative » content may help optimize the system performance without causing acceptability problem ; and iii) dynamic information and other traffic management tools interplay in a complementary manner to optimize the traffic