Simulation Exploration of the Potential of Connected Vehicles in Mitigating Secondary Crashes

Secondary crashes (SCs) on freeways are a major concern for traffic incident management systems. Studies have shown that their occurrence is significant and can lead to deterioration of traffic flow conditions on freeways in addition to injury and fatalities, albeit their magnitudes are relatively low when compared to primary crashes. Due to the limited nature of crash data in analyzing freeway SCs, surrogate measures provide an alternative for safety analysis for freeway analysis using conflict analysis. Connected Vehicles (CVs) have seen compelling technological advancements since the concept was introduced in the 1990s. In recent years, CVs have emerged as a feasible application with many safety benefits especially in the urban areas, that can be deployed in masses imminently. This study used a freeway model of a road segment in Florida’s Turnpike system in VISSIM microscopic simulation software to generate trajectory files for conflict analysis in SSAM software, to analyze potential benefits of CVs in mitigating SCs. The results showed how SCs could potentially be reduced with traffic conflicts being decreased by up to 90% at full 100% composition of CVs in the traffic stream. The results also portrayed how at only 25% CV composition, there was a significant reduction of conflicts up to 70% in low traffic volumes and up to 50% in higher traffic volumes. The statistical analysis showed that the difference in average time-to-collision surrogate measure used in deriving conflicts was significant at all levels of CV composition

Investigation Of Free-Flow Speed At Basic Segment Expressways For Level Terrain In Malaysia

Free-flow speed (FFS) is an important parameter in the speed-flow relationship, analyses of capacity and level of service (LOS) for basic segment expressways. Relevant authorities in Malaysia have been referring to the ArahanTeknik (Jalan) 8/86 to estimate LOS for basic segment expressways based on v/c ratio. However, due to the technological advancement and the surge of vehicle numbers on roads, the values obtained in the study may not show the actual resemblance of current Malaysian traffic conditions in Malaysia. There are several FFS models presented in major references and previous studies throughout the world. However, the suitability of these models for Malaysian traffic conditions is limited to some extent. Therefore, this study was conducted to understand in more detail about FFS at basic segment expressways and to develop FFS model based on current local standards. Six FFS models are developed based on regression analysis. However, one final model is selected as the best FFS model through the performance indicators. In this study, FFS of vehicles without motorcycles using headway (≥ 8 s) is selected as the best FFS model. Sensitivity analysis had also been performed in order to measure the sensitivity of each parameter for the developed FFS model. Thus, the outcome of this study is valuable for local traffic engineers and highway authorities in Malaysia for better understanding of the FFS and to estimate LOS at basic segment expressways

Analyzing Benefits of Connected Vehicle Technologies During Incidents on Freeways and Diversion Strategies Implementation: A Microsimulation-Based Case Study of Florida\u27s Turnpike

The full utilization of connected vehicles (CVs) is highly anticipated to become a reality soon. As CVs become increasingly prevalent in our roadway network, connected technologies have enormous potential to improve safety. This study conducted a microscopic simulation to quantify the benefits of CVs in improving freeway safety along a 7.8-mile section on Florida’s Turnpike (SR-91) system. The simulation incorporated driver compliance behavior in a CV environment. The simulation was implemented via an existing VISSIM network model partially developed by the Florida Department of Transportation (FDOT). In addition, the study analyzed how CVs would assist in detour operations as a strategy for congestion management during traffic incidents on freeways. The Surrogate Safety Assessment Model (SSAM) software was used to evaluate the benefits of CVs based on time-to-collision (TTC) as the performance measure. The TTC was evaluated at various CV market penetration rates (MPRs) of 0%, 25%, 50%, 75%, and 100%. The results showed a decreasing trend of conflicts for morning and evening peak hours, especially from 25% to 100% CV MPRs. The benefits were statistically significant at a 95% confidence level for high CV MPR (above 25%). Upon an incident on the freeway, at higher CV MPRs simulations, the detour strategy seemed to reduce travel time on the freeway. Besides, the detour strategy was more helpful when the incident clearance duration lasted more than 30 minutes. Findings from this study may help the incident management process prepare for detour strategies based on the severity of the incident at hand and could explain the importance of CVs in supporting warning and management strategies for drivers to improve safety on freeways. Keywords: Conflicts, Connected Vehicles, Driver Compliance Rate, Detour, Incident Modeling, Safety Surrogate Measure

Statistical and simulation methods for evaluating stationary and mobile work zone impacts

In 2014, nearly 10% of overall congestion on freeways was due to the presence of work zones (WZs), equivalent to 310 million gallons of fuel loss (FHWA, 2017a). In terms of safety, in the US, every 5.4 minutes, a WZ related crash occurred in 2015 (96,626 crashes annually) (FHWA, 2017b). Maintenance work involves both Stationary Work Zones (SWZs) and Mobile Work Zones (MWZs). There are many analytical and simulation-based tools available for analyzing the traffic impacts of SWZs. However, the existing traffic analysis tools are not designed to appropriately model MWZs traffic impacts. This study seeks to address this gap in existing knowledge through the use of data from MWZs to develop and calibrate traffic impact analysis tools. This objective is accomplished through data fusion from multiple sources of MWZ, probe vehicle and traffic detector data. The simulation tool VISSIM is calibrated for MWZs using information extracted from videos of MWZ operations. This is the first study that calibrated the simulation based on real driving behavior behind a MWZ. The three recommended calibration parameters are safety reduction factor of 0.7, minimum look ahead distance of 500 feet and the use of smooth closeup option. These calibration values can be used to compare MWZ scenarios. Also, the data collection framework and calibration methodology designed in this study could be used in future research. The operational analysis concluded that a moving work activity lasting one hour or more are suggested to be done when traffic volumes are under 1400 veh/hr/ln, and preferably under 1000 veh/hr/ln, due to the drastic increase in the number of conflicts. In addition, three data driven models were developed to predict traffic speed inside a MWZ: a linear regression model and two models that used Multi-Gene Genetic Programming (MGGP). The second objective is to develop models and tools for safety assessment of stationary work zones. In the WZ safety literature, few studies have quantified the safety impact of SWZ and almost no quantitative study assessing MWZ safety impact. Using Missouri data, this study introduces 20 new crash prediction models for SWZs on freeways, expressways, rural two lane highways, urban multi-lane highways, arterials, ramps, signalized intersections, and unsignalized intersections. All the models except freeway SWZs are proposed for the first time in the literature. The mentioned SWZ models are implemented in a user-friendly spreadsheet tool which automatically selects the most appropriate model based on user input. The tool predicts crashes by severity, and computes the crash costs. For MWZs, there is no crash data available to develop crash prediction models. Thus, this dissertation analyzed conflict measures as a surrogate for safety impacts of MWZs. Conflict measures were generated from the trajectories of traffic simulation model. The safety trade-off plots between conflicts and combination of MWZ's duration and traffic volume were introduced. A transportation agency can use these plots to determine, for example, if they should conduct a MWZ for a short duration when the volume is high or for a longer duration when the volume is lower.Includes bibliographical reference

TrafficMCTS: A Closed-Loop Traffic Flow Generation Framework with Group-Based Monte Carlo Tree Search

Digital twins for intelligent transportation systems are currently attracting great interests, in which generating realistic, diverse, and human-like traffic flow in simulations is a formidable challenge. Current approaches often hinge on predefined driver models, objective optimization, or reliance on pre-recorded driving datasets, imposing limitations on their scalability, versatility, and adaptability. In this paper, we introduce TrafficMCTS, an innovative framework that harnesses the synergy of groupbased Monte Carlo tree search (MCTS) and Social Value Orientation (SVO) to engender a multifaceted traffic flow replete with varying driving styles and cooperative tendencies. Anchored by a closed-loop architecture, our framework enables vehicles to dynamically adapt to their environment in real time, and ensure feasible collision-free trajectories. Through comprehensive comparisons with state-of-the-art methods, we illuminate the advantages of our approach in terms of computational efficiency, planning success rate, intent completion time, and diversity metrics. Besides, we simulate highway and roundabout scenarios to illustrate the effectiveness of the proposed framework and highlight its ability to induce diverse social behaviors within the traffic flow. Finally, we validate the scalability of TrafficMCTS by showcasing its prowess in simultaneously mass vehicles within a sprawling road network, cultivating a landscape of traffic flow that mirrors the intricacies of human behavior

Multi-Criteria Evaluation in Support of the Decision-Making Process in Highway Construction Projects

The decision-making process in highway construction projects identifies and selects the optimal alternative based on the user requirements and evaluation criteria. The current practice of the decision-making process does not consider all construction impacts in an integrated decision-making process. This dissertation developed a multi-criteria evaluation framework to support the decision-making process in highway construction projects. In addition to the construction cost and mobility impacts, reliability, safety, and emission impacts are assessed at different evaluation levels and used as inputs to the decision-making process. Two levels of analysis, referred to as the planning level and operation level, are proposed in this research to provide input to a Multi-Criteria Decision-Making (MCDM) process that considers user prioritization of the assessed criteria. The planning level analysis provides faster and less detailed assessments of the inputs to the MCDM utilizing analytical tools, mainly in a spreadsheet format. The second level of analysis produces more detailed inputs to the MCDM and utilizes a combination of mesoscopic simulation-based dynamic traffic assignment tool, and microscopic simulation tool, combined with other utilities. The outputs generated from the two levels of analysis are used as inputs to a decision-making process based on present worth analysis and the Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Situation) MCDM method and the results are compared

The Feasibility of Closing Vehicle Crossings along St. Charles Avenue: A Study of Transit Safety and Performance

The St. Charles streetcar is an important transit line in the city of New Orleans, with about 65,000 people living within a ½ mile walking distance from it. However, the line experiences a very high streetcar/automobile crash rate due in large part to the large number of grade vehicle crossings over the tracks that lack signalization. Through traffic modeling, the closure of many of these vehicle crossings and the diversion of automotive traffic to the remaining, signalized crossings is analyzed to determine traffic impacts on street network. The result is a modest increase in traffic, about 7-8%, at the remaining signalized intersections

Bringing Diversity to Autonomous Vehicles: An Interpretable Multi-vehicle Decision-making and Planning Framework

With the development of autonomous driving, it is becoming increasingly common for autonomous vehicles (AVs) and human-driven vehicles (HVs) to travel on the same roads. Existing single-vehicle planning algorithms on board struggle to handle sophisticated social interactions in the real world. Decisions made by these methods are difficult to understand for humans, raising the risk of crashes and making them unlikely to be applied in practice. Moreover, vehicle flows produced by open-source traffic simulators suffer from being overly conservative and lacking behavioral diversity. We propose a hierarchical multi-vehicle decision-making and planning framework with several advantages. The framework jointly makes decisions for all vehicles within the flow and reacts promptly to the dynamic environment through a high-frequency planning module. The decision module produces interpretable action sequences that can explicitly communicate self-intent to the surrounding HVs. We also present the cooperation factor and trajectory weight set, bringing diversity to autonomous vehicles in traffic at both the social and individual levels. The superiority of our proposed framework is validated through experiments with multiple scenarios, and the diverse behaviors in the generated vehicle trajectories are demonstrated through closed-loop simulations

Driver’s Shy Away Effect in Urban Extra-Long Underwater Tunnel

For urban extra-long underwater tunnels, the obstacle space formed by the tunnel walls on both sides has an impact on the driver\u27s driving. The aim of this study is to investigate the shy away characteristics of drivers in urban extra-long underwater tunnels. Using trajectory offset and speed data obtained from real vehicle tests, the driving behaviour at different lanes of an urban extra-long underwater tunnel was investigated, and a theory of shy away effects and indicators of sidewall shy away deviation for quantitative analysis were proposed. The results show that the left-hand lane has the largest offset and driving speed from the sidewall compared to the other two lanes. In the centre lane there is a large fluctuation in the amount of deflection per 50 seconds of driving, increasing the risk of two-lane collisions. When the lateral clearances are increased from 0.5 m to 2.19 m on the left and 1.29 m on the right, the safety needs of drivers can be better met. The results of this study have implications for improving traffic safety in urban extra-long underwater tunnels and for the improvement of tunnel traffic safety facilities