Simulation-based analysis of variable speed limit for traffic performance and safety during incidents

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.

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

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.

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.

A deep reinforcement learning-based intelligent intervention framework for real-time proactive road safety management

Safety and congestion are ever present and increasingly severe transportation problems in urban areas throughout the nation and world. These phenomena can have wide-ranging consequences relating to safety, the economy, and the environment. Adverse weather conditions represent another significant challenge to safety and mobility on highways. Oregon is not immune from either of these global issues. Oregon Route (OR) 217, to the southwest of the downtown Portland, is one of the worst freeways for congestion in the state and is also subject to the Pacific Northwest's frequently inclement and unpredictable climate. High crash rates, severe recurrent bottlenecks and highly unreliable travel times continuously plague the corridor, making it a major headache for the thousands of commuters using it every day. In an effort to more effectively combat both congestion and adverse weather, transportation officials all over the world have been turning to increasingly technological strategies like Active Traffic Management (ATM). This can come in many forms, but among the most common are variable speed limit (VSL) systems which use real-time data to compute and display appropriate reduced speeds during congestion and/or adverse weather. After numerous studies and deliberations, Oregon Department of Transportation (ODOT) selected Oregon Route (OR) 217 as one of the first locations in the state to be implemented with an advisory VSL system, and that system began operation in the summer of 2014. This thesis seeks to evaluate the effectiveness of this VSL system through the first eight months of its operation through an in-depth and wide-ranging "before and after" analysis. Analysis of traffic flow and safety data for OR 217 from before the VSL system was implemented made clear some of the most prevalent issues which convinced ODOT to pursue VSL. Using those issues as a basis, a framework of seven specific evaluation questions relating to both performance and safety, as well as both congestion and adverse weather, was established to guide the "before and after" comparisons. Hypotheses, and measures of effectiveness for each question were developed, and data were obtained from a diverse array of sources including freeway detectors, ODOT's incident database, and the National Oceanic and Atmospheric Administration (NOAA). The results of the various "before and after" comparisons performed as a part of this thesis indicate that conditions have changed on OR 217 in a number of ways since the VSL system was activated. Many, but not all, of the findings were consistent with the

With the rapid urbanization during the past three decades in China, the urban expressway network has arisen with large numbers in many cities. However, the traffic conditions are becoming worse and worse. One of the main reasons is that the connected sections of main road and expressway do not have a coordination by the intersection signal and variable speed limits (VSL) on expressway. In this paper, a new cooperation optimization model of VSL on urban expressway and the intersection signal timing are proposed based on the mesoscopic traffic flow model. Its objective is to minimize the total delay and the number of parking. Its essence is adjusting traffic flow on the network in space-time so that the whole network can be in a state of equilibrium. It is effective to the control of local traffic congestion and can avoid the spread of congestion, thus improving traffic safety. Additionally, the optimal VSL strategy is proposed. And then a solution algorithm based on the simultaneous perturbation stochastic approximation (SPSA) is designed for the proposed model. In the end, a practical example of Yanshan overpass in Ji’nan elevated expressway is used to validate the effectiveness of the proposed method. The simulation results are satisfactory. The conclusions are very useful for traffic management department to implement reasonable traffic control strategy.

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.

This paper provides an overview of various variable speed limit (VSL) strategies developed over the last two decades. It first explains the theoretical background of VSL systems and how they can be used as dynamic traffic control devices to improve traffic conditions and increase safety. An overview of VSL control strategies, ranging from early rule-based approaches to the most advanced network-wide coordinated approach, is provided, followed by a discussion of their associated potential benefits and areas for improvement. The likely environmental benefits of VSL strategies are also discussed, along with some further related aspects of VSL application, such as driver compliance to VSL and the integration of a differential speed limit (DSL) with VSL. Finally, the paper presents a critical review, pointing out some key issues that were identified from the literature review and recommends some directions for future research that need to be addressed as recommendations for best practices to underpin further refinement, development, and application of VSL.

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.

Harmonization with Variable Speed Limits on Motorways

Exploring the impact of a coordinated variable speed limit control on congestion distribution in freeway

The variable speed limit (VSL) is a control instrument of emerging intelligent transportation systems used to help manage motorway traffic. The VSL has the potential to improve traffic safety and reduce both traffic congestion and emissions through better harmonisation of traffic flow. The VSL results in a reduction of speed variations among vehicles travelling along controlled sections. In this paper, a modified logic-tree-based algorithm is proposed to improve the mobility benefits of VSL controllers. The modified algorithm is assessed using a case study in Auckland, New Zealand. Analysis of the case study is based on a critical bottleneck section of the Auckland motorway using the Aimsun micro-simulator. The proposed algorithm is compared with a known algorithm proposed in the literature and used in practice. The simulation results of the case study show that the proposed logic-tree-based VSL control algorithm outperforms the existing method. Compared with a no-control scenario, it results in respective improvements of 6%, 11%, 3%, 9% and 3% in the capacity of the bottleneck section, the total travel time and emissions of carbon dioxide, carbon monoxide and nitrogen oxides.

Trajectory-level fog detection based on in-vehicle video camera with TensorFlow deep learning utilizing SHRP2 naturalistic driving data

Capacity effects of variable speed limits on German freeways