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Left turns may generate efficiency problems, which can be solved by appropriately prohibiting left turns. The goal of this paper is to propose a method for purpose of minimizing total travel times in urban road networks by prohibiting left turns. With left turn prohibition, the signal timing plan is optimized with the lane-based method because the method can adequately handle both signal timing optimization and lane assignment. The total travel time is calculated with link flows and link travel time being estimated with signal settings. As illustrated by numerical examples, prohibiting left turns reduces the total travel time of car traffic in road networks. As the left turn prohibition results can handle the randomness in the network, these results provide potential implications for congestion management.

The direct left turn at intersections increases delays and causes more accidents in certain conditions. Prohibiting left turns could increase the capacity of the road network and reduce the delays. This research aims to analyze which left turns should be prohibited in an urban road network to increase efficiency. Stochastic User Equilibrium (SUE), with left turn prohibition, is studied in this paper, by minimizing the travel time of the network. The left turn prohibition solution, the corresponding cycle time and green times are determined. A left turn prohibition filtering algorithm (LTPFA) is developed in this paper. The core of the algorithm is that the minor left turn flows have priority to be prohibited. The LTPFA succeeds to find optimal or near-optimal result of travel time in the shorter time compared with enumerating all left turn prohibition combinations. As the total traffic demands increase, the traffic network can benefit more from the left turn prohibition.

Urban road networks may benefit from left turn prohibition at signalized intersections regarding capacity, for particular traffic demand patterns. The objective of this paper is to propose a method for minimizing the total travel time by prohibiting left turns at intersections. With the flows obtained from the stochastic user equilibrium model, we were able to derive the stage generation, stage sequence, cycle length, and the green durations using a stage-based method which can handle the case that stages are sharing movements. The final output is a list of the prohibited left turns in the network and a new signal timing plan for every intersection. The optimal list of prohibited left turns was found using a genetic algorithm, and a combination of several algorithms was employed for the signal timing plan. The results show that left turn prohibition may lead to travel time reduction. Therefore, when designing a signal timing plan, left turn prohibition should be considered on a par with other left turn treatment options.