Modelling speed reduction behaviour on variable speed limit-controlled highways considering surrounding traffic pressure: A random parameters duration modelling approach

Variable speed limit (VSL) systems are important active traffic management tools that are being deployed across the U.S. and indeed around the world for relieving congestion and improving safety. Oregon’s first variable advisory speed limit signs were activated along Oregon Highway 217 in the summer of 2014. The variable advisory speed system is responsive to both congestion and weather conditions. This seven-mile corridor stretches around Western Portland and has suffered from high crash rates and peak period congestion in the past. VSL systems are often deployed to address safety, mobility and sustainability related performance. This research seeks to determine whether the newly implemented variable advisory speed limit system has had measurable impacts on traffic safety and what the scale of the impact has been. The research utilizes a before-after crash analysis with three years of data prior to implementation and around 16 months after. Statistical analysis using an Empirical Bayes (EB) approach will aim to separate the direct impacts of the variable advisory speed limit signs from the long term trends on the highway. In addition, the analysis corrects for the changes in traffic volumes over the study period. Three data sources will be utilized including Washington County 911 call data, Oregon incident reports, and official Oregon Department of Transportation crash data reports. The analysis results are compared between data sources to determine the reliability of 911 call data as a proxy for crash statistics. The conclusions should be able to provide an indication of whether variable advisory speed limits can provide increased safety along high crash corridors.

In this paper, we present several fusion approaches to merge speed limits reported in digital maps with detected speed limit signs using an onboard camera. Digital maps holding speed limits signs are required to be updated to cover speed limit changes and are unable to support variable speed limits. On the other hand, a camera system placed onboard a vehicular can detect variable speed limits as well as temporary speed limits at construction sites. However, an onboard camera cannot detect implicit speed limits. As such, a combination of digital map and camera system can provide more accurate speed limit information for driver assistance and support vehicle safety features. In this paper, the digital map and camera system are fused to obtain the desired more accurate speed limit information. The fused speed limits as well as those from the individual sources are compared with ground truth data obtained from an extensive measurement campaign spanning over 15000 km driving distance in five European countries. Specifically, five fusion approaches are defined, modeled and evaluated. Four of them are based on prioritizing information while the remaining approach is based on the classical Dempster-Shafer data fusion technique. The performance of the approaches are presented in terms of the percentage of correct speed limit detection with respect to the driving distance. The obtained results clearly show that fusion techniques can significantly increase the amount of correctly detected speed limits. A MATLAB based graphical user interface was designed to load test data, evaluate and present the results as fast and as efficient as possible.

A variable speed limit model for freeway bridges considering the influence of both traffic service level and visibility in fog

Recent research has investigated the effects of var iable speed limits (VSL) on traffic flow processes. Findings show that VSL profoundly impact lane flow distribution (LFD) and increase the use of the slow lane by reducing the speed difference between the slow lane and the overtaking lanes. Finally, VSL reduce the capacity drop phenomenon on multi-lane sections and significantly increase the proportion of flow on the slow lane. These results highlight the major impact of LFD on the ca pacity of multi-lane sections. The paper presents a new analytical model that esti mates the capacity of multi-lane sections and repro duces the capacity-drop caused by LFD characteristics. It can be applied to estimate the capacity of motorway se ctions with two or three lanes under common traffic condit ions; it can also estimate the impact of VSL on the capacity of multi-lane sections. The multi-lane capacity model is coupled with a dyn amic mesoscopic traffic flow model initially design ed for network applications: the meso-LWR model. The resulting dynamic traffic flow model is relevant for mot orway network applications and VSL evaluation. The dynamic model is implemented on a French motorway site. The results show the ability of the model to reproduce actual traffic situations (capacity, congestion per iod, etc.) without VSL, including the amplitude of capacity dr op phenomenon caused by the under-use of the slow lane. It also shows the ability of the model to estimate the effect of VSL on future traffic flow conditions.

Variable speed limits (VSLs) have a potential to improve mobility and safety of motorway through harmonisation of traffic flow. However, the success of VSL is highly dependent on drivers’ compliance to the displayed speed limits. Emerging technologies in the field of connected autonomous vehicles (CAVs) is likely to revolutionise the way VSL will be operated in the near future. VSL can be integrated with CAVs where CAVs will automatically obey the displayed speed limits. However, 100% penetration rate of CAVs is a long‐term goal. At the initial stage of deployment, CAVs will coexist with manually driven vehicles on motorways. This study explores ways to implement VSL under a mixed traffic condition where CAVs and manually driven vehicles coexist in the traffic stream. A hybrid approach combining particle swarm optimisation with proportional‐integrated‐derivative is proposed to improve VSL implementation under a range of mixed traffic conditions. The simulation results showed that the proposed method successfully achieved the desired speed limits and rapidly stabilised the system at the initial and transient points at penetration rates of 50 and 75%, whereas the method encountered serious overshoots at lower penetration rates.

The prevailing variable speed limit (VSL) systems as an effective strategy for traffic control on motorways have the disadvantage that they only work with static VSL zones. Under changing traffic conditions, VSL systems with static VSL zones may perform suboptimally. Therefore, the adaptive design of VSL zones is required in traffic scenarios where congestion characteristics vary widely over space and time. To address this problem, we propose a novel distributed spatial-temporal multi-agent VSL (DWL-ST-VSL) approach capable of dynamically adjusting the length and position of VSL zones to complement the adjustment of speed limits in current VSL control systems. To model DWL-ST-VSL, distributed W-learning (DWL), a reinforcement learning (RL)-based algorithm for collaborative agent-based self-optimization toward multiple policies, is used. Each agent uses RL to learn local policies, thereby maximizing travel speed and eliminating congestion. In addition to local policies, through the concept of remote policies, agents learn how their actions affect their immediate neighbours and which policy or action is preferred in a given situation. To assess the impact of deploying additional agents in the control loop and the different cooperation levels on the control process, DWL-ST-VSL is evaluated in a four-agent configuration (DWL4-ST-VSL). This evaluation is done via SUMO microscopic simulations using collaborative agents controlling four segments upstream of the congestion in traffic scenarios with medium and high traffic loads. DWL also allows for heterogeneity in agents’ policies; cooperating agents in DWL4-ST-VSL implement two speed limit sets with different granularity. DWL4-ST-VSL outperforms all baselines (W-learning-based VSL and simple proportional speed control), which use static VSL zones. Finally, our experiments yield insights into the new concept of VSL control. This may trigger further research on using advanced learning-based technology to design a new generation of adaptive traffic control systems to meet the requirements of operating in a nonstationary environment and at the leading edge of emerging connected and autonomous vehicles in general.

Variable Speed Limits (VSL) are primarily designed to enhance traffic safety on hazardous roadways by dynamically adjusting speed limits based on real-time traffic and weather conditions. Most previous studies have focused on using VSLs to improve safety, mitigate congestion, and reduce environmental impact, assuming a securely connected VSL network. But what would be the impact of cyberattacks on VSL systems on traffic safety and network efficiency. This paper investigates the impact of intentional disruptions on VSL signs within traffic networks. We present a threat model to identify vulnerabilities in the VSL communication network and potential access points for attackers. An analytical accident model was developed, and various VSL disruption scenarios were simulated using a case study of Highway 1 in British Columbia, Canada, in SUMO (Simulation of Urban MObility) to assess the potential for crashes and safety problems resulting from VSL disruptions. Surrogate Safety Measures (SSM) were employed as key measures of safety concerns. Our findings highlight notable risks, including up to 56% additional conflicts, posed by these intentional disruptions. A robustness assessment using Monte Carlo simulation runs of a scenario with heterogeneous driver behaviors demonstrated that the safety impact is consistent and not random seed-dependent. Across runs, intentional disruptions still yielded significant increases in conflicts, with an average rise of 24.95%, confirming the stability of the results. Various mitigation strategies are discussed to enhance traffic safety and resilience against VSL manipulation.

Author(s): Gao, Hang; Cheng, Shenyang; Zhang, Michael | Abstract: The model based variable speed limit (VSL) control has been proven effective to resolve capacity-drop and time delay at a single recurrent bottleneck in previous studies. This project applies VSL controls to the traffic corridors with multi-segment and multi-bottleneck with the objective of reducing fuel consumption and greenhouse gas emissions. Based on a comprehensive review of existing methods, we develop and compare two fuel consumption centered VSL control (FC-VSL) strategies: flow-based control versus density-based control. These control strategies are implemented in SUMO, a microscopic traffic simulation package, on a 10-mile long freeway section. Results show that the density-based control reduces fuel consumption and gas emissions significantly at the cost of slight increase of travel time. The flow-based control, in contrast, reduces congestion and emissions in the downstream segments but transfers the congestion to the segments upstream of the controlled segments, resulting in an overall performance that is worse than the density-based FC-VSL, and no better than imposing static speed limits.

This paper presents the systematic evaluation of Variable Speed Limit (VSL) system implemented on I-270 in St. Louis County. The system varies the speed limit in real time during periods of recurring and non-recurring congestion to prevent traffic from breaking down. The system was evaluated objectively and subjectively, and this paper describes the objective evaluation of the system. The objective evaluation was performed by comparing the traffic flow parameters during static speed limit (pre-VSL) with variable speed limit (post-VSL) by using five measures of performance: 1) speed, 2) volume, 3) occupancy, 4) travel time, and 5) congestion measures. Identification of congested segments and the time periods for the analyses were the initial steps for evaluating the system. Traffic data were provided by MoDOT collected using Remote Traffic Microwave Sensors. Average speed, volume and time occupancy profiles indicated that the VSL system change in traffic conditions including congestion. Preventing the highway from reaching its capacity and avoiding the traffic breakdown is one of the main objectives of VSL system initiation. It can be achieved by upstream drivers reducing speed, metering the upstream traffic and preventing traffic from breaking down. Congestion measures evaluation indicates change in Travel Time, Percentage of Congested Travel and reduction in duration, extent and intensity of congestion. The VSL system benefits were determined, which indicated that the system benefits will pay for the initial capital cost of the system over the years. This study can be used by Departments of Transportation for evaluation of active management systems.

Variable speed limits in the link transmission model using an information propagation method

Despite of the fact that the traffic control zone for maintenance work (work zone) has been recognized as one of major priorities to guarantee the traffic safety, only one conventional posted speed limit (PSL) strategy is applied into the organization and management. This article presents the strategy of the variable speed limit (VSL) on highway work zones that brings about gradual deceleration and low speed variance. To evaluate the safety of the proposed VSL strategy, this study uses the microscopic simulation software VISSM to estimate the traffic flow and adopt transversal and longitudinal coefficients of safety (MSDE and cv) to compare the different speed limit strategies. The results of simulation and analysis confirm that VSL yield a substantial decrease the traffic turbulence caused by speed limit and increase the traffic safety throughout work zones.

Dynamic areas strategy design for variable speed limiting at fixed freeway bottlenecks

The variable speed limit on roads and highways across the city is to ensure that the driver is not over speeding the vehicle and thus, a way to avoid any mishappening. It is evident that the persisting system is not able to resist the driver of crossing the speed limit on roads. Thus, through this paper a method is presented to reduce the driver indulgence over speed and ensuring the vehicle stays under speed limits. The electronic speed limiter model is simulated in Proteus-VSM through which variable speed control of BLDC motor is done using I2V communication and Arduino Uno as microcontroller. The speed limits are transmitted and received through Rf module interfaced with the microcontroller and PWM control technique is used to control the speed of the motor. The results showed that the method can control the speed under reference speed limits.

Hybrid model predictive control for freeway traffic using discrete speed limit signals

Variable Speed Limit (VSL) control contributes to potential crash risk reduction by suggesting a suitable dynamic speed limit to achieve more stable and uniform traffic flow. In recent studies, researchers adopted macroscopic traffic flow models and perform prediction-based optimal VSL control. The response of drivers to the advised VSL is one of the most critical parameters in VSL-controlled speed dynamics modeling, which significantly affects the accuracy of traffic state prediction as well as the control reliability and performance. Nevertheless, the variations of driver responses were not explicitly modeled. Thus, in this research, the authors proposed a dynamic driver response model to formulate how the drivers respond to the advised VSL during various traffic conditions. The model was established and calibrated using field data to quantitatively analyze the dynamics of drivers’ desired speed regarding the advised VSL and current traffic state variables. A proactive VSL control algorithm incorporating the established driver response model was designed and implemented in field-data-based simulation study. The design proactive control algorithm modifies VSL in real-time according to the traffic state prediction results, aiming to reduce potential crash risks over the experiment site. By taking into account the real-time driver response variations, the VSL-controlled traffic state dynamics was more accurately predicted. The experimental results illustrated that the proposed control algorithm effectively reduces the crash probabilities in the traffic network.