Traffic Operational Performance Research Articles

Potential risk and efficiency analysis of decision-making dilemmas in connected dual-vehicle interactions at uncontrolled intersections

In dual-vehicle interactive scenarios, drivers often encounter decision-making dilemmas, even with connected information, thus posing significant risk challenges to traffic operations. This study explored the impact of such dilemmas on decision-making and traffic operations for drivers involved in straight-going (SG) and left-turning (LT) vehicles at uncontrolled intersections. Employing driving simulation technology, a decision-making experiment incorporating preemptive (P) and yielding (Y) strategies was conducted with 72 S G and 72 L T drivers under connected information provision. By analyzing joint decisions (P-P, Y-P, and Y-Y) made by drivers on both sides, we investigated implications for traffic operational safety and efficiency. Furthermore, recognizing the diversity in individual characteristics and time pressure, we developed a random parameters multinomial logit model to examine the relationship between potential traffic operational performance (both safety and efficiency) and various contributing factors. Moreover, we calculated the marginal effects of these contributing factors. By assessing the probability change of Y-P joint decisions balancing safety and efficiency, we identified reference values for each contributing factor that promote effective interactive operations. The findings suggest that: (1) Regarding interactive dilemmas conditions, Conditions where the SG vehicle had higher speed and farther distance than the LT vehicle were more likely to result in heterogeneous Y-P joint decisions, in which one driver chooses to yield and the other party passes quickly, thereby improving traffic performance. (2) Time pressure increased the likelihood of heterogeneous Y-P joint decisions but also increased P-P joint decisions. (3) heterogeneous individual attributes did not always lead to higher heterogeneous decisions. Overall, this study provides insights into factors influencing joint decisions and traffic operational performance under connected information provision, considering individual heterogeneity and time pressure, aiming to the advancement of more efficient and safer vehicle-connected transportation systems.

Comparative Assessment of Expected Safety Performance of Freeway Automated Vehicle Managed Lanes

The use of dedicated lanes, known as managed lanes (MLs), on freeways is an established traffic management strategy to reduce congestion. Allowing automated vehicles (AVs) in existing MLs or dedicating MLs for AVs, referred to as AVMLs, has been suggested in the literature as a tool to improve traffic operation and safety performance as AVs and driver-operated vehicles (DVs) coexist in a mixed-vehicle environment. This paper focuses on investigating the safety impacts of deploying AVMLs on freeways by repurposing general-purpose lanes (GPLs). Four ML strategies considering different lane positions and access controls were implemented in a traffic microsimulation under different AV market adoption rates (MARs) and traffic demand levels, and trajectories were used to extract rear-end and lane change conflicts. The time-to-collision (TTC) surrogate safety measure was used to identify critical conflicts using a time threshold dependent on the type of following vehicle. Rates of conflicts involving different vehicle types for all ML strategies were compared to the case of heterogeneous traffic. The results indicated that the rates of rear-end conflicts involving the same vehicle type as the lead and following vehicle, namely DV-DV and AV-AV conflicts, increased with ML implementation as more vehicles of the same type traveled in the same lane(s). By comparing the aggregated conflict rates, the design options that were deemed to negatively impact traffic efficiency and capacity were also found to negatively impact traffic safety. However, other ML options were found to be feasible in terms of traffic operation and safety performance, especially at traffic demand levels below capacity. Specifically, one left-side AVML with continuous access was found to have lower or comparable aggregated conflict rates compared to heterogenous traffic at 25% and 50% MARs, and, thus, it is expected to have positive or neutral safety impacts.

Analyzing the Traffic Operational Performance of School Pick-Up and Drop-Off Dynamics in Saudi Arabia

In seeking sustainable, safe, and efficient school commuting tours as non-recurring sources of congestion, it is essential to investigate the dynamic interaction between school students’ pick-up and drop-off (P&D) movements and the traffic operational performance of the surrounding area. This study investigates the traffic operational performance in the vicinity of schools at various P&D time intervals. The Travel and Planning Time indices (TTI, PTI), along with the Level of Service (LOS) are utilized as traffic operational performance indices in this article. A Python script was developed to employ the Google API for estimating the travel times from a real traffic dataset comprising 40 schools distributed across six cities in the Kingdom of Saudi Arabia (KSA). The results indicate that LOS varies from C to D for all cities except Riyadh, which exhibits the poorest traffic performance during P&D time intervals. This paper serves as a guideline for city planners and policymakers seeking to provide valuable insights to enhance traffic operational performance in Saudi Arabia.

Data-driven evacuation and rescue traffic optimization with rescue contraflow control

In response to local sudden disasters, e.g., high-rise office or residential building fire disasters, road occupation can cause conflicts, and traffic directions may be opposite between evacuation vehicles and rescue vehicles; moreover, lane contraflow can be adopted to meet these surge traffic demands. However, lane contraflow that provides more roads for rescue vehicles reduces the traffic supply in the evacuation direction. It is unclear how to control the number of contraflow roads used by rescue vehicles to coordinate evacuation and rescue traffic operations. Here, we adjust the critical rescue traffic volume of reversing the normal road traffic direction to control rescue contraflow. Additionally, we propose a multiobjective mixed integer linear programming formulation for evacuation and rescue traffic optimization. Additionally, considering that the upper limit of the critical rescue traffic volume is unknown and that the proposed formulation includes multiple objectives and multi-priority vehicle classes, a three-stage solving algorithm is developed. Next, a large-scale evacuation and rescue traffic optimization result dataset is obtained for the Nguyen–Dupuis road network, and the impact of different rescue contraflow control plans on evacuation and rescue traffic is studied based on data-driven statistical analysis. The results show that by adjusting the optimal rescue traffic route, the critical rescue traffic volume for reversing the normal road traffic direction can reduce the interference of rescue traffic to evacuation traffic operation performance without reducing rescue traffic operation performance, and can be used to coordinate evacuation and rescue traffic operation under rescue contraflow.

Impact of Pavement Defects on Traffic Operational Performance

The present research investigates the influence of pavement distresses on traffic operational performance in terms of speed and capacity. The pavement distresses are expressed by the pavement condition index (PCI). Three roads of multi-lane highways located on the road network of Kafrelsheikh governorate, Egypt, were chosen as a case study. Road geometry, pavement condition characteristics, and traffic volume were collected manually from 23 sections for field data surveys. For speed measurements, spot speed data were gathered using the stopwatch method under the free-flow conditions, and the percentile speeds (V50% and V85%) have been calculated for different vehicles classes. Traffic capacity was determined via extrapolation of the quadratic function. Regression analysis models were created to express the relationships of both the percentile speeds and traffic capacity as dependent variables, and three independent variables (PCI, lane, and shoulder widths). These empirical mathematical relations help in developing road design and maintenance works on multi-lane highways. The main conclusion of the study demonstrated that traffic operational performance was more significantly affected by pavement distresses than road geometry. Moreover, the results indicated that pavement distresses have a significant impact on light vehicles more than heavy ones.

Evaluating Traffic Operation Conditions during Wildfire Evacuation Using Connected Vehicles Data

With climate change and the resulting rise in temperatures, wildfire risk is increasing all over the world, particularly in the Western United States. Communities in wildland–urban interface (WUI) areas are at the greatest risk of fire. Such fires cause mass evacuations and can result in traffic congestion, endangering the lives of both citizens and first responders. While existing wildfire evacuation research focuses on social science surveys and fire spread modeling, they lack data on traffic operations during such incidents. Additionally, traditional traffic data collection methods are unable to gather large sets of data on historical wildfire events. However, the recent availability of connected vehicle (CV) data containing lane-level precision historical vehicle movement data has enabled researchers to assess traffic operational performance at the region and timeframe of interest. To address this gap, this study utilized a CV dataset to analyze traffic operations during a short-notice evacuation event caused by a wildfire, demonstrating that the CV dataset is an effective tool for accurately assessing traffic delays and overall traffic operation conditions during the selected fire incident. The findings also showed that the selected CV dataset provides high temporal coverage and similar travel time estimates as compared to an alternate method of travel time estimation. The study thus emphasized the importance of utilizing advanced technologies, such as CV data, to develop effective evacuation strategies and improve emergency management.

The Effect of One-Way Urban Street on Traffic Operation Performance

Traffic congestion has become a serious problem affecting citizens' daily life. Many adopted strategies are studied and applied to alleviate this problem and reduce traffic pressure on street networks. Some are costly, and others are unsuccessful in solving the problem due to higher demand. The one-way traffic movement with circulation modification is adopted in this work which promotes the capacity of streets to sustain higher demand. The study area is identified with the most congested signalized intersection (Al-Nakhala, Al-Sakhara, and Beirut) along the urban corridor. The obtained results suggest using one-way traffic movement with a circulation network that significantly improves traffic operation and reduces congestion to a great extent. Control delays of selected signalized intersections are reduced from about 95%, and v/c is reduced to 0.69 (Al-Nakhala), 0.59 (Al-Sakhara), and 0.99 (Beirut) intersections. The results of modified traffic movement show excessive delays are not experienced, and the traffic movement modification ensures the sufficiency of the signalized corridor to accommodate the traffic demand. The traffic one-way movement can solve the problem of traffic congestion in the study area and improve the level of service from (F) to (A) and (B).

A Framework for Estimating Future Traffic Operation and Safety Performance of Restricted Crossing U-Turn (RCUT) Intersections

Background: Despite numerous studies demonstrating the effectiveness of Restricted Crossing U-Turn (RCUT) intersection design, its implementation remains uneven and close to zero in some large states, including California. This paper provides a comprehensive framework to estimate the operational and safety performance of future RCUT designs. The framework is demonstrated for a geometrically constrained intersection located on a high-speed rural expressway. The operational evaluation relies on microscopic simulation models of existing TWSC and alternate RCUT designs used to estimate network-wide performance measures. Methods: Two approaches are demonstrated for future safety estimation; first, an HSM-prescribed Empirical Bayes (EB) approach that uses Safety Performance Function (SPF) predictions combined with the crash history of the site. For typical applications, EB estimates may be combined with CMFs for RCUT found in the literature. This approach remains the preferred option for safety estimation. However, for geometrically constrained locations where atypical RCUT designs need to be evaluated, a surrogate measure-based approach that uses trajectory data from the simulation model is described. Results: Surrogate measure-based safety analysis revelated that the RCUT design with no-left turn from mainline would be the most appropriate design for this location. Conclusion: The framework demonstrated here may be used by agencies to estimate the future benefits of the first-time application of treatments that have been successful elsewhere.

Simulating and assessing the effect of a protected intersection design for bicyclists on traffic operational performance and safety

The focus of this research is to simulate and assess the effect of a protected intersection design (PID) for bicyclists on traffic operational performance and safety. The PID was modelled and evaluated at the intersection of Tyvola Rd and South Blvd in Charlotte, North Carolina, USA. Traffic was modelled considering the existing intersection design and proposed PID using Vissim microscopic traffic simulation software under conditions of 0% bicycles to 15% bicycles. Safety was then analysed using Surrogate Safety Assessment Model (SSAM), and conflicts were defined as a 1.5-second intersection of two or more trajectories. There is no conclusive evidence that PID negatively effects operational performance (vehicle delay and level of service) at the selected study intersection. The type and total number of bicycle-related conflicts per bicycle varied with the percentage of bicycles. As much as an 80% reduction in the total number of bicycle-related conflicts could be observed if the percentage of bicycles exceed 10%. Benefits due to the implementation of PID could be greater at intersections with high bicycling activities. The findings support the hypothesis that the PID reduces the number of conflicts, and therefore improves safety.

Comparing travel time performance-based measures to assess the effect of a freeway road construction project on freeway and connecting arterial street links

ABSTRACT A road construction project has a significant effect on traffic congestion and operational performance of the project corridor and connecting street links. However, not many researchers focused on travel time performance-based measures to assess the effect of a road construction project on the project corridor and connecting street links. Therefore, travel time data for a freeway road resurfacing project on 100 links within its vicinity were gathered and processed to assess the effect on freeway and connecting arterial street links. A paired t-test was used to examine the differences in means between the before and during road resurfacing project period travel time performance-based measures. There is a significant difference in travel time performance-based measures before and during the road resurfacing project period on freeway links and connecting arterial links. Their significance varied by the time-of-the-day and day-of-the-week on the freeway and connecting arterial links. The average travel time, planning time, and travel time index can consistently explain the effect of a road resurfacing (construction) project on transportation system performance when compared to buffer time and buffer time index. The findings can be used to enhance temporary traffic control practices in the vicinity of road construction projects.

Evaluating the Performance of Signalized Intersection with Signal Countdown Timer

Signalized intersections are the interrupted traffic flow facility in a roadway network. The efficiency of traffic operations at the signalized intersection is expected to improve during inter-green intervals. To improve the quality of service at an intersection the traffic control devices are used widely over the world. The time intervals defined for traffic signal operation help to reduce severe traffic conflicts, delay, and improve driver’s decision for making turns. The present study evaluates the performance of traffic operations under with and without signal countdown timer (SCT) conditions based on field data collected at two signalized intersections in Hyderabad city, India. The vehicles speeding behavior and drivers complying with traffic regulation are also analyzed under different countdown timer conditions. It has been found that the average approaching speed of vehicles and red-light violations are found to be changed due to changes in the signal countdown timer conditions. The average startup loss time calculated in the field was found to be decreased when SCT was inactive. A significant increase in the capacity of signalized intersections has been observed when SCT was active. The traffic performance measures such as average control delay and queue lengths as estimated on the approaches were influenced due to the presence of STCs. The study finds that the signal countdown timer is an effective device that can enhance the traffic safety and operational performance of a signalized intersection.

Impact on Road Safety and Operation of Rerouting Traffic in Rural Travel Time Information System.

The Travel Time Information System (TTIS) is an Intelligent Traffic Control System installed in Poland. As is common, travel time is the only factor in the decision about rerouting traffic, while a route recommendation may consider multiple criteria, including road safety. The aim of the paper is to analyze the safety level of the entire road network when traffic is rerouted on paths with different road categories, intersection types, road environments, and densities of access points. Furthermore, a comparison between traffic operation and road safety performance was carried out, considering travel time and delay, and we predicted the number of crashes for each possible route. The results of the present study allow for maximizing safety or traffic operation characteristics, providing an effective tool in the management of the rural road system. The paper provides a methodology that can be transferred to other TTISs for real-time management of the road network.

Operational Evaluation of Effectiveness of Connected Vehicle Smartphone Technology on a Signalized Corridor

Various connected vehicle (CV) technology applications reported in current literature have the potential to solve the challenges faced by the transportation sector. Over the last decade, extensive research efforts have focused on performance evaluation and the benefits of innovative CV applications; findings indicate that CV technology can effectively mitigate the safety, mobility, and environmental challenges experienced on today’s transportation networks. The majority of previous research has evaluated CV technology through simulation studies. However, a field study is the ideal method of assessing CV technology effectiveness. Field observational studies to validate previous research findings have not been conducted. Therefore, a field study to obtain the actual effectiveness of CV technology was warranted, not only to validate previous findings, but to add to the body of knowledge surrounding this topic. This research presents a field study evaluation of the effectiveness of CV smartphone technology on a 1.1-mi segment of State Road 121, containing five intersections, in Gainesville, Florida. Field observations were conducted using a CV application that uses a smartphone application, EnLighten (Connected Signals, Inc., Oregon, United States), to communicate intersection information to a driver’s smartphone, which serves as a vehicle on-board unit. Traffic operation performance was evaluated using a start-up lost time and discharge distribution model. Findings showed that the CV smartphone technology improved intersection performance with a reduction in start-up lost time of approximately 86%. The CV technology had no impact on the distribution model of position-dependent discharge headways.

Characterizing the Brazilian airspace structure and air traffic performance via trajectory data analytics

This paper presents a data-driven approach for multi-scale characterization of the Brazilian airspace structure and air traffic operational performance from aircraft tracking data recorded by surveillance systems. Unsupervised learning is performed with a flight trajectory clustering analysis to automatically identify spatial traffic patterns in both the terminal and the en route airspace for major origin-destination pairs of the Brazilian air transportation system. Based on the as-flown route structure learned, quantitative metrics are developed to describe the structural efficiency of the airspace and the operational efficiency of the traffic flows. For this, actual flight trajectories are projected onto reference nominal trajectories in space and time. The results allowed for cross-route comparisons of air traffic flow efficiency across multiple flight phases as well as for the identification of causal factors for trajectory deviations from nominal routes. An interactive data analytics tool is also created to output performance statistics and air traffic visualizations. With the provision of a systematic data-driven approach for characterizing actual air traffic operations, the analytics framework is envisioned to assist airspace design and performance monitoring processes and to provide the basis for developing predictive capabilities in support of traffic flow management.

A Novel Methodology for Estimating the Capacity and Level of Service for the New Mega Elliptical Roundabout Intersection

Mega elliptical roundabout is a new intersection on rural multilane highways. This intersection was developed in a previous paper using simulation data, and the authors found that it is better than interchange (full cloverleaf) in most scenarios of traffic flow. Basically, there are no guidelines or procedures for designing mega elliptical roundabout in AASHTO Green Book, Federal Highway Administration guides, and Highway Capacity Manual. Thus, the purpose of this study is to analyze the traffic operation performance and propose a methodology for calculating the capacity of mega elliptical roundabout and also the level of service by gap acceptance theory. Moreover, this research studied the influence of different values of truck ratios and also different values of a major highway speed on geometric design and traffic operation performance for mega elliptical roundabout. To validate the thoroughness of the proposed methodology, VISSIM simulations were conducted. This research will assist practitioners in determining the appropriate geometric design, assessing mega elliptical roundabout intersections, and making comparisons with other alternatives.

Impact of using indirect left-turns on signalized intersections’ performance

The majority of traffic delays in urban areas occur at signalized intersections. Due to the limited availability of space and right-of-way, many transportation agencies are considering unconventional traffic control systems for intersections to improve signal efficiency and reduce overall delays. Common unconventional left-turn treatments include the right-turn followed by a U-turn (RTUT) and a U-turn followed by a right-turn (UTRT). The main goal of this study is to determine the traffic operational performance of the three left-turn treatments under different traffic conditions. The results showed that unconventional left-turn control types have less delay and travel time compared to the direct left-turn (DLT), when the U-turn locations are 200 m away from the main intersection. Also, RTUT showed superior performance over the other left-turn control types, when the U-turn locations are 100 m away from the main intersection.

Classifying road network patterns using multinomial logit model

Road network patterns influence traffic operational performance and road safety. A precise description of road network patterns can provide useful guidance for both design and improvement of road systems. Most previous studies have classified road network patterns using a visual inspection method. Although visual inspection is valuable in practical applications, it can be subjective and time consuming. Hence, a more reliable, automated, and quantitative approach for the classification of road network patterns is required. The objective of this study is to develop and apply a quantitative method for network pattern classification. Data analyzed are from 718 traffic analysis zones (TAZs) in Florida's Hillsborough County. Six quantitative metrics, geometric and topologic, were analyzed, and their ability to classify different road network patterns were compared. Then, a multinomial logit model was developed to classify various network patterns using the six metrics. The results show that meshedness coefficient, proportion of cul-de-sacs, and proportion of 4-legged intersections were the three most significant variables in determining network patterns. Finally, this quantitative method was validated using TAZ data from Florida's Orange County, with an accuracy of 74.7%. This accuracy demonstrates the potential of the method in automatically and reliably classifying road network patterns.

English

Each year the demand of aviation services is increasing but the European airspace is still fragmented according to national borders. Delays of implementing Single European Sky are increasingly high. Consequently, each year the aviation industry loses a lot of money, among others, because of flight route extensions or higher fuel consumption. A comparison between Air Traffic Management-Related Operational Performance U.S./Europe shows how inefficient ATM is in Europe and how costly for the airspace users. This study also describes the benefits and costs of the SES full implementation.

Influences of Cross-Sectional Design Elements at Urban Arterial Driveway Locations

This paper presents a study on the influences of select cross-sectional design elements—specifically median configurations and bicycle lanes—and their impact on crash severity and type as well as the associated driver gap acceptance for turning maneuvers at midblock driveway locations on urban arterials. The primary goal of this research is to better understand how median and bicycle lane configurations can influence safety and operations at driveway locations. The authors used crash data, traffic data, and roadway information from driveway locations in Oregon, Arkansas, and Oklahoma. The data were supplemented with digital videos from field studies of the sites. These traffic videos helped to better understand how road features and traffic influenced driver behavior at selected urban arterial driveway locations. Gap acceptance studies were conducted to determine critical gaps for driveway locations at arterial roads with and without bicycle lanes. Four critical gap analysis methods were evaluated to estimate driveway operations and noted potential procedural biases associated with two of the techniques. The paper describes these field studies and summarizes how gap acceptance varied at different arterial driveway locations. Simulation analysis in CORSIM (Version 6.3) examined the influence of median type, traffic volume, and access density on traffic operational performance.

Urban Traffic Signal System Control Structural Optimization Based on Network Analysis

Advanced urban traffic signal control systems such as SCOOT and SCATS normally coordinate traffic network using multilevel hierarchical control mechanism. In this mechanism, several key intersections will be selected from traffic signal network and the network will be divided into different control subareas. Traditionally, key intersection selection and control subareas division are executed according to dynamic traffic counts and link length between intersections, which largely rely on traffic engineers’ experience. However, it omits important inherent characteristics of traffic network topology. In this paper, we will apply network analysis approach into these two aspects for traffic system control structure optimization. Firstly, the modified C-means clustering algorithm will be proposed to assess the importance of intersections in traffic network and furthermore determine the key intersections based on three indexes instead of merely on traffic counts in traditional methods. Secondly, the improved network community discovery method will be used to give more reasonable evidence in traffic control subarea division. Finally, to test the effectiveness of network analysis approach, a hardware-in-loop simulation environment composed of regional traffic control system, microsimulation software and signal controller hardware, will be built. Both traditional method and proposed approach will be implemented on simulation test bed to evaluate traffic operation performance indexes, for example, travel time, stop times, delay and average vehicle speed. Simulation results show that the proposed network analysis approach can improve the traffic control system operation performance effectively.