Improving Traffic State Prediction Model for Variable Speed Limit Control by Introducing Stochastic Supply and Demand

Abstract

Variable speed limit (VSL) is becoming recognized as an effective way to improve traffic throughput and road safety. In particular, methods based on traffic state prediction exhibit promising potential to prevent future traffic congestion and collisions. However, field observations indicate that the traffic state prediction model results in nonnegligible error that impacts the next step decision making of VSL. Thus, this paper investigates how to eliminate this prediction error within a VSL environment. In this study, the traffic state prediction model is a second-order traffic flow model named METANET, while the VSL control is model predictive control (MPC) based, and the VSL decision is discrete optimized choice. A simplified version of the switching mode stochastic cell transmission model (SCTM) is integrated with the METANET model to eliminate the prediction error. The performance of the proposed method is assessed using field data from a VSL pilot test in Edmonton, Canada, and is compared with the prediction results of the baseline METANET model during the road test. The results show that during the most congested period the proposed SCTM-METANET model significantly improves the prediction accuracy of regular METANET model.

Integrated Variable Speed Limits and User Information Strategy

“…Bie et al [19] developed a variation of the METANET model by integrating it with the Stochastic Cell Transmission Model (SCTM) for traffic prediction. A different objective function was determined in [20], whose formulation linked accident risk with the adoption of VSLs.…”

Research on Joint Control of On-Ramp Metering and Mainline Speed Guidance in the Urban Expressway Based on MPC and Connected Vehicles

“…However, MPC approach was widely used to ramp metering and speed guidance [9][10][11][12][13]. Moreover, dynamic speed limit control was jointly applied with other models, such as a traffic state prediction model [14][15][16]. From the literature review, it was found that the operational efficiency or capacity was used as the main optimization objective while traffic safety was rarely considered.…”

“…e volume equation for the on-ramp is shown in equations (13) and (14), where q i (ρ jam − ρ i (k))/(ρ jam − ρ cr ) indicates the merging volume to mainline and d i (k) + w i (k)/T indicates the on-ramp demand. Meanwhile, the final merging volume will also be subject to the on-ramp metering rate, r i (k).…”

Variable Speed Limit Control Method of Freeway Mainline in Intelligent Connected Environment

“…Kotsialos et al [11] used the second-order traffic flow METANET model as a core model, which had good expression characteristics for VSL control. ese experiment results showed that advanced models can effectively improve the traffic capacity of road congested sections, including SCTM-METANET [12], proactive VSL based on Dyna TAM-VSL [13], a variety of vehicles model [14], and predictive control based on the cell transmission model [15].…”