On the Effects of Various Measures of Performance Selections on Simulation Model Calibration Performance

Abstract

Objective. This paper examines the effects of various measures of performance (MOP) selections on simulation model calibration performance, in terms of reflecting actual traffic conditions and vehicle interactions. Method. Two intersections in Shanghai were selected for simulation model calibration, one for testing and another for validation. Three effective MOPs were utilized, including average travel time (i.e., time passing the intersection), average queue length, and vehicle headway distribution. The counts of three types of traffic conflicts (i.e., crossing, rear-end, and lane change) were used as safety MOPs. Those MOPs, as calibration objectives, were examined and compared. Results. The results of the testing site showed that different effective MOPs had their own advantages: average travel time appeared to be the best in reflecting lane change and rear-end conflicts while headway distribution performed the best consistency between simulated and actual crossing conflicts. Compared to the safety MOPs, average travel time and headway distribution still performed better, in terms of resulting in more similar simulated conflict metrics (e.g., TTC, PET) to actual ones. A multicriteria calibration strategy based on average travel time and headway distribution generally had better performances in reflecting actual traffic conditions and vehicle interactions than using any single effective or safety MOP. Similar results were found for the validation site. Conclusion. To simulate actual traffic conditions and vehicle interactions, multiple effective MOPs could be simultaneously considered for model calibration, instead of using safety MOPs.

Review of driving-behaviour simulation: VISSIM and artificial intelligence approach

“… (W74ax), (W74bxAdd), (W74bxMult). [ 36 ] W 74 ANOVA (GA) Use the calibrated parameters on another Intersection for validation (W74ax), (W74bxAdd), (W74bxMult). [ 37 ] W 99 (LHS) (GA) Compared the speed between the simulation and the field.…”

Exploring the effects of measures of performance and calibration strategies on calibrating traffic microsimulation model: A quantitative analysis approach

“…acceleration less than 1 m/s 2 ); the other is the CDF of the space headway of all vehicles on each intersection entrance lane. It should be pointed out that the average queue length is used as the MoP in many studies [27,54] because it reflects the spatial behaviour of vehicles to a certain extent. However, the queue length is susceptible to the arrival distribution of vehicles in each signal cycle.…”

“…For instance, Yu et al [25] and Mahmood et al [26] consider the actual flow and speed as the MoP combination. Wang et al [27] considered travel time and headway as the MoP combination. However, most solve this problem by the a priori method (that is, the multi-objective function is aggregated into a single-objective function through the weight coefficient).…”

“…The results show that average speed is an appropriate MoP in calibration. Wang et al [27] took one hour as the aggregate interval to compare the effects of average travel time, average queue length, headway distribution, and conflict counts on TMM calibration. The results show that conflict counts may not be the optimal MoP for TMM calibration.…”

A Bayesian Neural Network-Based Method to Calibrate Microscopic Traffic Simulators

“…For heterogeneous traffic, GA was suitable for obtaining optimized parameter sets [19]. When exploring the impact of different measures of performance on the calibration results, some scholars still preferred GA [20]. e above research shows that the GA-based method performs well in calibration.…”