Development of an Optimization Methodology for Adaptive Traffic Signal Control at Diamond Interchanges

This research develops a methodology and a corresponding implementation algorithm to provide optimal signal control of diamond interchanges in response to real-time traffic fluctuations. The problem is formulated as to find a phase sequencing decision with a phase duration that makes a prespecified performance measure minimized over a finite horizon that rolls forward. The problem is solved by a forward dynamic programming (DP) method. The optimal signal switches over each 2.5 s interval are found for each horizon of 10 s. The optimization process is based on the advanced vehicle information obtained from loop detectors set back a certain distance from the stop line. Vehicle trajectories from detections till future arrivals and departures is modeled at the microscopic level to estimate the traffic flows at the stop-line for each horizon. The DP algorithm is coded in C $++$ language and dynamically linked to AIMSUN, a stochastic microsimulation package, for evaluation. The simulation results have exhibited that the DP algorithm is superior to PASSER III and TRANSYT-7F in handling demand fluctuations for medium to high flow scenarios when the field demand is increased from the one used in off-line optimization. The performance of the three algorithms is almost identical if the simulation demand is similar to off-line demand situation and does not vary much.