Iterative algorithm for lane reservation problem on transportation network

International audienceIn this paper, we study an NP-hard lane reservation problem on transportation network. By selecting lanes to be reserved on the existing transportation network under some special situations, the transportation tasks can be accomplished on the reserved lanes with satisfying the condition of time or safety. Lane reservation strategy is a flexible and economic method for traffic management. However, reserving lanes has impact on the normal traffic because the reserved lanes can only be passed by the special tasks. It should be well considered choosing reserved lanes to minimize the total traffic impact when applying the lane reservation strategy for the transportation tasks. In this paper, an integer linear program model is formulated for the considered problem and an optimal algorithm based on the cut-and-solve method is proposed. Some new techniques are developed for the cut-and-solve method to accelerate the convergence of the proposed algorithm. Numerical computation results of 125 randomly generated instances show that the proposed algorithm is much faster than a MIP solver of commercial software CPLEX 12.1 to find optimal solutions on average computing time

US Highway Privatization and Heterogeneous Preferences

Abstract: We assess the welfare effects of highway privatization accounting for government’s behavior in setting the sale price, firms’ strategic behavior in setting tolls in various competitive environments, and motorists’ heterogeneous preferences for speedy and reliable travel. We conclude motorists can benefit from privatization if they are able to negotiate aggressively with a private provider to obtain tolls and service that align with their varying preferences. Surprisingly, motorists are likely to be better off negotiating with a monopolist than with duopoly providers or under public-private competition. Toll regulation may be counterproductive because it would treat motorists as homogeneous. Revised June 2009.Security Breach Costs; Financial Distress; Insurance; Resource Allocation.

Real scenario and simulations on GLOSA traffic light system for reduced CO2 emissions, waiting time and travel time

Cooperative ITS is enabling vehicles to communicate with the infrastructure to provide improvements in traffic control. A promising approach consists in anticipating the road profile and the upcoming dynamic events like traffic lights. This topic has been addressed in the French public project Co-Drive through functions developed by Valeo named Green Light Optimal Speed Advisor (GLOSA). The system advises the optimal speed to pass the next traffic light without stopping. This paper presents results of its performance in different scenarios through simulations and real driving measurements. A scaling is done in an urban area, with different penetration rates in vehicle and infrastructure equipment for vehicular communication. Our simulation results indicate that GLOSA can reduce CO2 emissions, waiting time and travel time, both in experimental conditions and in real traffic conditions.Comment: in 22nd ITS World Congress, Oct 2015, Bordeaux, France. 201