Unsignalized Intersections Research Articles

Navigating Unsignalized Intersections: A Predictive Approach for Safe and Cautious Autonomous Driving

Navigating Unsignalized Intersections: A Predictive Approach for Safe and Cautious Autonomous Driving

Efficient Mixed Traffic Intersection Management under Uncertainty

Despite the extensive amount of research that exists regarding intersection crossing of Connected and Autonomous Vehicles, implementation of most of the already proposed theoretical algorithms is currently not realistic due to either their computational complexity, or strong assumptions about traffic data acquisition. An intermediary step would be to consider mixed traffic. Motivated by these facts, we study an unsignalized intersection crossing problem with mixed traffic and develop an online, safety-critical optimization scheme under localization and detection uncertainties. The centralized controller follows an Enhanced First-In-First-Out reservation policy and with the use of sequential optimization it ensures no more than one vehicle is present inside the protected zone of the intersection in order to avoid collisions, even when noisy measurements are present. Comparisons are made between different control and protected zone sizes and conclusions are drawn about the impact of uncertainties on the efficiency and robustness of the system.

Transportation Model In The Revitalization Of Segiri Stadium, Samarinda City

Samarinda Segiri Stadium area is one of the landmarks of Samarinda City. The condition of the Segiri Stadium area over time is getting shabby and unkempt. As one of the strategic areas of the city, the Samarinda City Government plans to revitalize the Segiri Stadium area. With the revitalization of the Segiri Stadium area, it will have an impact on existing transportation conditions. This study will model the transportation conditions in the area. The method used in this analysis is the MKJI 1997 method and modeling with Vissim software. The results of the analysis of the need for Parking Space Units (SRP) based on the Decree of the Director General of Land Transportation Number: 272/HK.105/DRJD/96 required as many as 2,148 SRP passenger car units. Analysis of unsignalized intersections in existing conditions (year 2022) LOS conditions are in the range of A to C which means the conditions are still safe. Modeling in 2030 the signalized intersection conditions are at LOS between A and D, which means there is already the potential for congestion. Analysis of signalized intersections in existing conditions (year 2022) the LOS conditions of the intersection are in the range of D to F, which means that congestion occurs in existing conditions. Modeling in 2030, LOS conditions are in the E to F range, which means that congestion is getting worse with a queue length value of more than 100 meters. Severe congestion occurs at the Dishub intersection and the Abul Hasan intersection. The results of the road section performance analysis show the LOS value between D to F, which means that it has experienced congestion. Modeling in 2030 shows LOS conditions in D to F conditions, which means that conditions are increasingly congested. Recommendations for these problems are to rearrange the traffic light phase cycle, remove side obstacles to improve the performance of sections and intersections, conduct traffic engineering and utilize Internet of Thing (IoT) technology.

Signalized and Unsignalized Road Traffic Intersection Models: A Comprehensive Benchmark Analysis

Road traffic flow models allow the development and testing of intelligent transportation solutions. Macroscopic intersection models are especially relevant for the simulation of large traffic networks. In this article, we study four first-order signalized and unsignalized intersection models. The two unsignalized approaches are the first-in-first-out (FIFO) model (roundabout-type intersection) and an optimal non-FIFO model (highway-type intersection). The optimal control operates upstream for the first signalized intersection model. It occurs downstream for the second signalized model. All four models satisfy the expected physical constraints of vehicle conservation, traffic demand, and assignment. The models are minimal and allow a comprehensible analysis of the results. We determine mathematical relationships between the intersection models and empirically analyze the performances using Monte Carlo simulations. The numerical simulations assume random demand, supply, and assignment. Besides average performances, the approach accounts for the flow ranges of variation. A benchmark analysis compares the intersection models. We observe that the optimal signalized intersection models overcome the performances of the FIFO model in congested states. They may even reach the performances of the idealistic non-FIFO model. Further applications for the four intersection models are discussed.

Proposing an effective approach for traffic safety assessment on heterogeneous traffic conditions using surrogate safety measures and speed of the involved vehicles

Objective The vehicular traffic in the cities is becoming more complex in developing countries like India due to the rising population and rapid urbanization. With the annually increasing road accidents, a study on the effective safety assessment of heterogeneous traffic conditions is needed. The study aims to evaluate the safety of heterogeneous traffic by spotting the critical conflicts with respect to the speed of the involved vehicles. Methods The current study proposed Critical Following Speed instead of using a single threshold value for safety assessment in mixed traffic. Critical Following Speed was proposed by comparing the stopping and the available distances between the involved vehicles and used to identify the critical conflicts. With this, the study uses the speeds of both the leading and the following vehicles to judge the nature of the conflict. Three unsignalized four-legged intersections (S-1, S-2, and S-3) and two straight road sections (S-4 and S-5) were selected as the study area in Trichy, India. Post Encroachment Time (PET) and Time to Collison (TTC) were used as surrogate indicators to assess the crossing or merging and rear-end conflicts, respectively. Results The average PET and TTC values were between 1.25 and 1.73 s in the study locations. The overall percentage of critical conflicts indicated the non-safer crossing and merging maneuvers in three locations. The other two locations were experiencing safe rear-end conflicts, as the percentages of critical conflicts were below 4%. Various combinations of leading and following vehicle types were examined for the contribution of critical conflicts. The proposed methodology was validated with the 4-year accident data and a good relation was obtained. Conclusions Fast-moving vehicles were responsible for the less safe maneuvers with a higher collision probability in all the study locations. The correlation between critical conflicts and road accidents shows the effectiveness of the proposed approach in the traffic safety assessments for mixed traffic. This approach could be employed even in countries with homogenous traffic conditions instead of using a single threshold value. The correlations also show the potential of the proposed Critical Following Speed as a surrogate safety indicator for safety evaluation in the future.

Analisis Kinerja Simpang Taman Tirto Agung Semarang

The development of transportation in the city of Semarang, especially in the Banyumanik area, has an impact on increasing the movement of people, stuff and services. this greatly encourages an increase in transportation facilities and infrastructure in the Banyumanik area. An increase in the number of vehicles that is not matched by the development of infrastructure will cause conflicts on the road, especially at intersections or roundabouts. So far, on roads in the Banyumanik area, at certain hours there is often an ineffective traffic rush with road performance being an important infrastructure in transportation. This study used calculations based on MKJI 1997. The data collection was carried out by survey directly at the intersection location in this study determined 5 days and 3 observation sessions every day. It was found that the tirto agung intersection had 322 types of intersection and the highest traffic was on Wednesday 21 June 2023 with a traffic flow value of 3528 pcu/hour, capacity 2722 pcu/hour, degree of saturation 1.296, intersection delay 92.938 sec/pcu, queue probability 69.225% - 143.302%. Based on the research results, the performance value of the Tirto Agung intersection does not meet the 1997 MKJI requirements where the degree of saturation allowed for the unsignalized intersection type is <0.75, it is necessary to have a physical intersection engineering (APILL) or non-physical (Traffic Engineering) at the intersection location.

EVALUASI TUNDAAN PADA SIMPANG EMPAT TAK BERSINYAL DI KOTA MATARAM (STUDI KASUS : SIMPANG JALAN PEJANGGIK DAN SIMPANG JALAN CATURWARGA)

Pejanggik intersection and Caturwarga intersection are unsignalized intersections in Mataram City. Both intersections have the same characteristics, namely they both have four arms. The location of the two intersections close together causes frequent traffic delays. For this reason, research is needed to optimize the performance of these two unsignalized intersections.The method used to analyze the two intersections is the Indonesian Road Capacity Manual (1997). The data used is primary and secondary data, such as traffic volume, capacity, degree of saturation, delays and queuing opportunities. Results of performance analysis of the Jalan Pejanggik intersection in existing conditions DS = 1.086, delay = 24.2 seconds/pcu, and queuing opportunity = 47.6%. Performance of the Caturwarga Road Intersection in existing conditions DS = 0.97, delay = 18.1 seconds/pcu and queuing opportunity = 38.54%. To improve unsignalized intersections, several alternatives are provided. The first alternative is Jalan Pejanggik Intersection DS = 1.00. delay = 19 seconds/smp and chance of queuing = 40.20%, Jalan Caturwarga DS intersection = 0.95. delay = 17 seconds/smp and chance of queuing = 36.92%. Second alternative Pejanggik Road Intersection DS = 0.97. delay = 18 seconds/smp and chance of queuing = 38.44%, Jalan Caturwarga DS intersection = 0.91. delay = 15.9 seconds/smp and chance of queuing = 33.7%

A review of surrogate safety measures on road safety at unsignalized intersections in developing countries

In recent times, the assessment of unsignalized intersection safety has received significant research attention because of the complex and diverse traffic movements and driving behaviour at such locations. However, priority traffic regulations are not well followed in comparison to the unsignalized junctions, which leads to more conflicts. Additionally, the severity of conflicts increases with continuous traffic manoeuvres, including right-turns and through traffic, combined with different driving behaviours. Several studies have compared crash-based analysis to proactive traffic safety measures. Current research outcomes imply that surrogate safety measures (SSMs) have the potential to elucidate the sequence of events that result in collisions, their underlying causes, and their outcomes. Therefore, to further understand the appropriateness of SSMs, further study is required based on heterogeneity in traffic along with driver behaviour that incorporates turning vehicle factors. This study presents an all-inclusive evaluation of the recent advancements in SSMs and their practical implementation, with a particular emphasis on unsignalized intersections in developing nations. The findings of this investigation would be helpful in identifying the appropriate safety indicators for evaluating traffic safety at unsignalized intersections.

SIMULATION OF TRAFFIC MANAGEMENT AND ENGINEERING TO IMPROVE THE PERFORMANCE OF THE FIVE POINT INTERSECTION ON JALAN KEPUTIH SURABAYA

The five-point intersection on Keputih Street is one of the unsignaled intersections in the city of Surabaya with traffic problems. At certain times, especially rush hour, traffic problems will occur. At 07.00 WIB it was seen that several drivers were trying to cut through the traffic jam by squeezing in between other vehicles, this was done by road users to avoid long queues of vehicles. Queues can be approximately 1.2km long and the surrounding existing conditions are commercial or shopping areas, housing with several sides of the road used as a means for vehicles to stop or park as an additional congestion factor. Thus, there is a need for management planning and traffic engineering to improve the quality of intersections in serving road users. The method used for data analysis is based on existing data obtained directly from the field and processed according to PKJI 2023. The results obtained were that the degree of saturation at the intersection was much different before and after the traffic engineering planning was carried out. Projection results with the installation of traffic light signs and geometric widening of Keputih Tegal, the degree of saturation value obtained was 0.78 where previously DJ = 0.98 0.85. Keywords: Management and Traffic Engineering; PKJI 2023; Delay; Five-point Unsignalized Intersection in Keputih Surabaya.

Effects of smartwatch usage on Children’s street-crossing behavior and visual attention allocation: An experimental study on street crossing in a real road environment

The use of smartwatches is facilitating the lives of children. However, smartwatch usage while crossing a street may lead to distractions and traffic safety hazards. The purpose of this study was to investigate the effects of smartwatch usage on the street-crossing behavior and visual strategies of children. Twenty-two children were recruited, and 220 street-crossing experiments were performed in real road environments, including at signalized and unsignalized intersections. ANOVA and Kruskal–Wallis H test calibrations were used to analyze the street-crossing behavior between the control group (who performed a task without smartwatch distraction) and the experimental group (who performed four different tasks with smartwatch distraction), and to visualize and compare the visual behavior data of children crossing the street. The results showed that children wearing smartwatches crossed the street more slowly and had a relatively narrow range of visual search, focusing on only a small area of the zebra crossing around them and the crosswalk area within their sight, whereas children who did not wear smartwatches additionally focused on areas with dangerous oncoming traffic on the left and right sides. Children wearing smartwatches were under various mental workloads and distraction levels as they performed the various distracting tasks, with listening to stories being the least distracting and least intensive, followed by answering phone calls and viewing images; a simple arithmetic operation was the most distracting and intensive task. Children while performing the distracting tasks showed a lower street-crossing speed and scanned left and right fewer times; viewing images and performing the simple arithmetic task also increased their fixation time on the smartwatches, further affecting their street-crossing behavior and thus increasing the risk of collision. At signalized intersections, children paid more attention to hazardous oncoming traffic areas and exhibited cautious crossing behaviors compared with that at unsignalized intersections. This study elucidated the characteristics of the effects of smartwatch usage on the street-crossing behavior of children and the influence pattern of the visual attention allocation and revealed the hazards of smartwatch usage on the street-crossing safety. It can contribute to improving the safety cognition of children distracted by smartwatch usage and reducing the occurrence of distracting behaviors while crossing streets. The results can provide a theoretical basis for scientific interventions and safety improvement measures.

A Game-Theoretic Approach on Conflict Resolution of Autonomous Vehicles at Unsignalized Intersections

In order to resolve the driving conflict and improve the safety and efficiency of autonomous vehicles at unsignalized intersections, a new decision-making method based on game theory with personalized driving preferences considered is proposed in this paper. In the decision-making method, the alterable game mode is constructed by combing the designed game entrying mechanism and replanning of game sequential order under different intersection conditions to ensure the adaptiveness and effectiveness of the decision-making algorithm. Besides, four payoff indicators and personalized payoff function are designed with the consideration of driving efficiency, safety and comfort requirement. The advantage of proposed method is that it not only reduces the complexity of game mode and improves the effectiveness at the same time, but also fully considers the personalized driving preferences to realize human-like driving and personalized decision while the existing methods usually neglect the difference among the drivers and its influence. Five different typical scenarios at the unsignalized intersection are given under co-simulation environment of Matlab and Prescan. The results show that the proposed decision-making method is able to resolve the driving conflict and ensure the safe passage of autonomous vehicles at unsignalized intersections, which verifies the effectiveness of the proposed method.

Transmission-Efficient RIS-Carrying UAV’s Auxiliary Communication Systems for Intelligent Connected Vehicle Platoons at the Unsignalized Intersection in Smart Cities

Numerous interaction demands for smart cities have arisen due to the explosive growth of the Internet of Things and mobile communication. Due to its passive low energy consumption and affordable deployment cost, reconfigurable intelligent surface (RIS) is a potential key technology to develop a novel paradigm of wireless communication at unsignalized intersections. This paper studies the signal interaction between multiple vehicle platoons in different paths before entering an unsignalized intersection supported by UAV, which is usually difficult to solve without the assistance of communication. Under the limitation of calculation and transmission resources, the objective is to optimize the system’s transmission efficiency. The joint resource scheduling model of communication time and transmission power includes the coupling effects of vehicle dynamics, onboard computing, signal transmission and reflection, and energy consumption. A method based on the quasi-Newton and sequential quadratic programming (SQP) algorithm is designed to carry out optimization iteration. Finally, the simulation results show that this method is generally efficient and outperforms the benchmark methods.

Self-Learned Autonomous Driving at Unsignalized Intersections: A Hierarchical Reinforced Learning Approach for Feasible Decision-Making

Reinforcement learning-based techniques, empowered by deep-structured neural nets, have demonstrated superiority over rule-based methods in terms of making high-level behavioral decisions due to qualities related to handling large state spaces. Nonetheless, their training time, sample efficiency and the feasibility of the learnt behaviors remain key concerns. In this paper, we propose a novel hierarchical reinforcement learning-based decision-making architecture for learning left-turn policies at unsignalized intersections with feasibility guarantees. The proposed technique is comprised of two layers; a high-level learning-based behavioral planning layer which adopts soft actor-critic (SAC) principles to learn high-level, non-conservative yet safe, driving behaviors, and a low-level motion planning layer that uses Model Predictive Control (MPC) framework to ensure feasibility of the two-dimensional left-turn maneuver. The high-level layer generates reference signals of velocity and yaw angles for the ego vehicle taking into account safety and collision avoidance with the intersection vehicles, whereas the low-level motion planning layer solves an optimization problem to track these reference commands taking into account several vehicle dynamic constraints and ride comfort. While training the behavioral SAC-based planning layer, We develop an adaptive entropy regularization technique that results in faster convergence, higher mean rewards, and lower collision rates. We validate the proposed decision-making scheme in simulated environments and compare with other model free Reinforcement Learning (RL) baselines. The results demonstrate that the proposed integrated framework possesses better training and navigation capabilities.

Multimodal Vehicular Trajectory Prediction With Inverse Reinforcement Learning and Risk Aversion at Urban Unsignalized Intersections

Multimodal Vehicular Trajectory Prediction With Inverse Reinforcement Learning and Risk Aversion at Urban Unsignalized Intersections

Exploratory analysis of evasion actions of powered two-wheeler conflicts at unsignalized intersection

The study investigates the braking and steering evasions of powered two-wheelers (PTWs) during severe conflicts observed at an unsignalized intersection. Traffic conflicts were detected using a surrogate safety indicator called anticipated collision time (ACT). Then the peak-over-threshold approach was used to identify the severe conflicts and the evasive actions. Conflicts between right-turning PTWs and through-moving vehicles, through-moving PTWs crossing through-moving vehicles, and merging/diverging PTWs were analyzed using the minimum ACT (ACTmin), maximum deceleration rate (DRmax), maximum yaw rate (YRmax), and time of evasive action (TEA). The evasive actions were classified into five categories: driver/rider error, no-evasion, braking-only, steering-only, and both braking and steering. Analysis reveals that right-turning PTWs experience higher crash risk (0.7 %) than the other movements. PTW riders primarily employ extreme steering maneuvers (greater than 13 degrees/s) to evade conflicts, whereas braking rates lie in the normal ranges (less than 1.5 m/s2). The time of evasive action varies between 2.04 and 2.44 s, with the right-turning PTW riders responding early. Through-moving riders commit errors while evading severe conflicts and perform fewer evasive actions than right-turning and merging/diverging riders. Right-turning riders perform more steering-only evasions than braking-only, whereas the riders involved in the other two conflicts execute more braking-only evasions. These findings suggest that conflict type influences riders' braking and steering responses. Hence, future applications in advanced driver/rider assistance systems and training programs should consider appropriate evasive action strategies for different conflict types.

Structural Equation Modeling of Right-Turn Motorists at Unsignalized Intersections: Road Safety Perspectives

Structural Equation Modeling of Right-Turn Motorists at Unsignalized Intersections: Road Safety Perspectives

Analysis of traffic conflicts with right-turning vehicles at unsignalized intersections in suburban areas

Right-turn collisions at intersections are one of the most dominant crash types in suburban areas, especially at unsignalized intersections. There is, however, a lack of comprehensive research on the speed patterns of vehicles during right-turn manoeuvres and their impact on crashes. To provide an in-depth investigation of the factors determining the safety of right-turn manoeuvres, driving behaviour data were collected through an instrumented vehicle study. Using this data, binary logistic regression models were developed to identify the factors affecting the probability of Vehicle-Vehicle (V-V) and Vehicle-Pedestrian (V-P) conflicts at six suburban intersections in Babol, Iran, during right-turn stage manoeuvres. In total, 1,456 V-V and V-P conflicts were identified from the data analysis. The results from the logistic regression model showed that the vehicle speed, the distance between road users, as well as driver and pedestrian distractions were associated with higher risk for vehicle-to-vehicle or vehicle-to-pedestrian conflicts. To estimate the safe right-turn speeds to be selected by the drivers at different stages of the right turn, i.e., at the start, during, and end of the movement, linear regression models were developed. The results showed that participants adjust their driving behaviour the same way toward pedestrians as they do toward vehicles. The findings of this study can be leveraged for the development of a robust advanced driving assistance system, the use of which can further improve the safety performance of right-turn manoeuvres.

Adaptive and Simultaneous Trajectory Prediction for Heterogeneous Agents via Transferable Hierarchical Transformer Network

Simultaneously and accurately predicting trajectories of multiple heterogeneous agents is crucial for intelligent transportation systems (ITS) applications, e.g., connected and autonomous vehicles. Existing model-based and data-driven methods can achieve good prediction accuracy, but most of them neglect the domain shift issue and prevalent imperfect data problems, i.e., few-shot learning and zero-shot learning issues. To address these issues, we propose a multi-source transfer learning (TL) framework, transferable hierarchical Siamese Transformer network (T-HSTN), for trajectory prediction of multiple heterogeneous agents, e.g., vehicles, bicycles, and pedestrians, at urban unsignalized intersections under small data conditions. Specifically, by extending the self-attention mechanism and exploring feature representations of traffic scenes, a Transformer-based network that hierarchically extracts temporal/spatial features and map features is introduced as the basic prediction model. Moreover, a TL framework with adaptive learning and feature alignment modules is built to explore the feature representations of unfixed traffic scenes and align both statistical and deep features to learn domain-invariant knowledge. More challenging trajectory prediction experiments are designed, corresponding to newly-built or badly-instrumented intersections under real-world scenarios. Experimental results verify the proposed method’s high accuracy, transferability, and generability. Our work fills the gap in solutions and benchmarks for TL tasks in trajectory prediction for heterogeneous agents. The conducted TL experiments provide a more practical setting of considering imperfect data problems in trajectory prediction.

Traffic Behaviour Analysis using Logistic Regression Method (LRM) and Structural Equation Modelling (SEM)

This study aims to determine traffic behaviour at the selected unsignalized intersection and the development of right-turn motorists (RTM) by adopting the logistic regression method (LRM) and structural equation modelling (SEM).

Design of Traffic Lights at the Unsignalized Intersection of Narogong Highway-Pangkalan 5 Road Km. 13.5 Bekasi City, West Java

The intersection of Narogong Highway-Pangkalan road 5, Bantargebang , Bekasi city, is a four-arm intersection that connects Bekasi City with Bogor Regency and is the access to the Bantargebang TPA. The irregular and narrow traffic conditions at the intersection cause frequent traffic jams and are prone to accidents. Therefore, it is necessary to analyze the need for traffic light at the intersection so that a solution can be found in overcoming the problem of congestion and can help smooth the intersection. This analysis is based on the MKJI method (Indonesian Road Capacity Manual) 1997. The results of the analysis show that the intersection of Narogong Highway - Pangkalan road 5, Bekasi City is not able to serve the traffic flow to the maximum, this can be shown by the result of the calculation that has been carried out, so an analysis is needed to improve the performance of the intersection, from the existing calculations alternatives, selected 3 phase alternative with geometric widening, from this solution a cycle time of 80 seconds was obtained with a degree of saturation (DS) = 0.690 to 0.839, and a maximum queue length of 104 meters. The intersection of Jalan Raya Narogong - Jalan Pangkalan 5, Bantargebang , Bekasi City, is intersection four the arm that connects Bekasi City with regency Bogor as well as is access going to to Bantargebang landfill . Condition Then cross that doesn't regular and narrow at intersections the cause often happen congestion and danger happen accident . Therefore _ that is necessary Analysis Need for Traffic Lights at intersections so that obtained solution in overcome problem traffic jams and can help smoothness at intersections . Analysis This based on MKJI method ( Indonesian Road Capacity Manual) 1997. Analysis results is known that , the intersection of Jalan Raya Narogong - Jalan Pangkalan 5 Bekasi City is not capable serve current Then cross with maximum , p This can showed with results calculations that have been made done , so required analysis For increase performance intersection , from alternative existing calculations , selected _ 3 phase alternative with widening geometric , from solution This obtained time cycle by 80 seconds with mark degrees saturation (DS) = 0.690 to 0.839, and long queue maximum 104 meters