Main Lane Research Articles

Highway Main Lane Vehicles Driving Behavior Prediction Based on Residual-Transformer

Highway Main Lane Vehicles Driving Behavior Prediction Based on Residual-Transformer

Performance Evaluation of Ekantakuna Intersection

Majority of the intersections in Kathmandu valley are unsignalized and hence traffic management becomes one of the emerging issues for traffic police and traffic designers. The number of vehicles in Kathmandu Valley is increasing at the rate of 12% annually (Department of Transport Management, 2018). The manual traffic management is very tedious and hectic nowadays. The consequence leads to traffic congestion and sometimes crashes too. Hence, the performance evaluation of such unsignalized intersection is essential and considering the real time situations, scenario analysis should be done. The research was carried out in Ekantakuna Intersection. The data's were collected in Ekantakuna Intersection through video-graphic surveying during weekdays: Monday to Friday both morning and evening during peak hours (9 to 11 AM in morning and 4 to 6 PM in evening).The model was developed in PTV VISSIM ( Micro-simulation software ) and thus the developed model was calibrated and validated using traffic volume. The relationship between field volume (actual volume) and VISSIM volume (Simulated Volume) was found with the help of R2 Value (Coefficient of Determination) which is found to be 0.9993 which indicates that variance of VISSIM output explains 99.9 percentage of variance in field data's. Pedestrian movement was not given priority and hence pedestrian simulation is not considered. Total three scenario analysis were performed in base case scenario. Among them the best scenario analysis was found to be scenario 1 which indicates the restriction of vehicles from service lanes to main lanes and allowing the movement of vehicles from Balkhu(service) to Satdobato(service) and Jawalakhel lanes, and Satdobato(service) to Balkhu(service ) and Bhaisepati lane.

Automatic Lane-Changing System on Congested Highway

This study proposes an autonomous lane-changing system for congested merging areas. Manual and autonomous vehicles are expected to coexist until all vehicles are substituted by autonomous vehicles. Therefore, interactions between humans and autonomous driving systems should be discussed. This study assumed a scenario in which an autonomous vehicle performed a lane change to a congested main lane, where all vehicles were manual. The proposed system estimated the possibility of changing lanes without collisions. A driving simulator was used to measure the lane-changing operations of human drivers in a congested merging area, and the proposed method was developed based on the experimental results. Simulations demonstrated that the proposed method could safely change lanes.

ЗАПРОВАДЖЕННЯ НАЦІОНАЛЬНОЇ СИСТЕМИ ОБЛІКУ ДОВЖИНИ АВТОМОБІЛЬНИХ ДОРІГ В ОДНОСМУГОВОМУ ОБЧИСЛЕННІ

Introduction. The use of geographical spatial data of the public road network has led to the question of the feasibility of applying existing methods of road length accounting and the need to introduce single-lane road length accounting. Problem statement. The search for alternative ways to account for the length of a road calls for improving the principles of forming road titles, which have certain solutions for accounting for sections with more than one lane in each direction and establishing the lengths of traffic interchanges, additional lanes on ascents, external and internal transitional high-speed lanes, dedicated (channelized) lanes, etc. Objective. To improve the system of accounting for the length of public roads of national importance. Materials and methods. The principles of road titling introduced in [1] have certain solutions for accounting for sections with more than 1 lane in each direction and establishing the lengths of traffic interchanges, which were rational at the time of adoption, but without further improvement may be ineffective and increasingly lead to contradictions. The need to introduce the term "length of a public road in single-lane calculation" is due to the fact that there are fundamental differences between the lengths of roads approved by the Resolution of the Cabinet of Ministers of Ukraine "On Approval of the List of Public Roads of National Importance" of December 15, 2023 No. 1318 [2] and the actual length (area) of lanes subject to repair and maintenance, since the road may have a different number of main lanes along its length, additional lanes on ascents, external and internal transitional high-speed lanes, dedicated (channelized) lanes, and exits may have several lanes in one direction.

Spatial heterogeneity among different-sized port communities in directed-weighted global liner shipping network

Global liner shipping network (GLSN) serves as the backbone of international commerce. In the context of the COVID-19 pandemic and regional integration, regionalization has become one of the dominant trends of the GLSN's structure. This study detected 27 practical relevant port communities within the directed-weighted GLSN using the Infomap algorithm. Based on the community structure of the GLSN, we identified the provincial, gateway, and connector hubs, considering the balance and intensity of the inbound and outbound shipping routes. To highlight the smaller communities obtained in this study, those practical relevant port communities are further differentiated into 7 large and 20 small port communities. The spatial heterogeneity among different-sized port communities is investigated regarding geographical distribution, topological properties, functional characteristics, etc. The large port community is typically formed in major trading regions with well-developed hub-and-spoke networks. They are the principal market in which most liner operators participate in it. Some small port communities lying along the main lane of seaborne container trades also play pivotal roles in the GLSN with many liner companies involved. While other small port communities located peripherally only connect to a few surrounding port communities. The spatial heterogeneity among different-sized port communities is mainly caused by the unbalanced distribution of seaborne container trades. These findings offer new insights into the community structure and its spatial heterogeneity within the GLSN, which can provide stakeholders with practical implications.

Redesign of The Overpass Bridge Structure at Km 839+450 Toll Road Pasuruan-Probolinggo Using Parker Type Truss Bridge

The Overpass Bridge Km 839+450 Pasuruan - Probolinggo Toll Road which is located in Leces District, Probolinggo Regency, East Java has a total span length of 144 meters with a Girder I bridge type. This bridge has 5 spans with 4 pillars. The writer want to redesign the bridge into 2 spans to increase the free space under the bridge overpass. The Parker truss bridge type was chosen because it has the lightest self-weight compared to other types of steel truss bridges. This parker type steel truss bridge is planned with a length of 72 m, a width of 12 m, and a height of 13 m. The bridge is designed for 1 lane which has 2 main lanes and 1 emergency lane. From the analysis carried out, the thickness of the vehicle floor plate is 20 cm with concrete fc 30 MPa and reinforcement Fy 410 MPa. The steel structure uses BJ 41 steel quality with profile dimensions on longitudinal girders WF 300.300.10.15, transverse girder profile dimensions using WF 700.300.13.24, main frame girder dimensions using WF 552.500.50.50 & WF 552.475.25.30, transverse wind ties using WF 294.200.8.12, as well as cross wind ties using the L 250.250.35. For the connection, high-strength bolts of type A325 with Fy 820 MPa are used with a diameter of 24 mm and a connection plate which is L 100.100.10, L 120.120.12, and a 25 mm thick plate. on the main frame connection. The placement of the bridge uses the placement of Typer Elastomeric Bearings coated with steel plates with dimensions of 600x600x150 mm. Steel truss bridge parker type has the advantage that the upperstructure's own weight is lighter than the existing bridge, the difference in weight reaches 33,07 %.

Research on Cooperative Control for On-Ramp Merging with Multiple Lanes in Connected and Automated Environments

This paper addresses the issue of on-ramp merging in multi-lane freeways and proposes a cooperative control method based on connected and automated vehicles. Focusing on a two-main-lane freeway scenario, the method consists of two key models: a merging sequence decision model and a motion planning model. The merging sequence decision model prioritizes collision avoidance by predicting the motion state and lane-changing trajectory of vehicles in the merging area. The motion planning model utilizes longitudinal and lateral cooperation to control the main lane vehicles to generate the merging gap through coordinated adjustments in the longitudinal speed or by performing lane changes. The optimal merging trajectory is determined using the entropy weight method, and a fast optimization method based on neural networks is employed. Through simulations considering different traffic density combinations, the proposed method is compared with traditional control schemes. Results demonstrate its superiority in improving traffic flow stability, rapidity, and overall efficiency.

Design Hourly Volume Estimation at Freeway Nodes From Short-Term Traffic Counts

This paper extends the concept of a design hourly volume (DHV) which is derived from the “ nth hour” to a concept based on the nth highest saturated hour. To calculate this nth highest saturated hour at each ramp junction of a node, it is necessary to have permanent traffic counts (PTC) on all ramps and the main lanes. In practice, such counts are often not available. For such cases, the German Highway Capacity Manual proposes a method that enables the estimation of DHV through short-term traffic counts (STCs) and the extrapolation of the results using available PTC in the vicinity. This study examines how accurately the required nth highest saturated hour can be estimated with this method and similar concepts. Furthermore, we investigate to what extent the number and the location of the available PTC affect the accuracy of the estimation. Scenarios without PTC are also considered. The evaluation is based on a database with a total of 72 freeway nodes for which PTC data from three years (2017–2019) are processed. The results show that the estimation of the nth highest saturated hour with the method of the German Highway Capacity Manual works accurately, even if only one PTC is available on each inflowing approach. The results further indicate that STC are crucial to achieve accurate results when few PTCs are available. Acceptable results are also obtained by STC of one week, even without a projection at a PTC.

Operational Analysis to Establish Guidelines for Designing Auxiliary Lanes on Frontage Roads

Auxiliary lanes (ALs) provide significant operational benefits by spreading merging or weaving movements over a long distance or by providing an extra lane of capacity through a freeway bottleneck or signalized intersection. However, if ALs are not long enough, they may produce merge bottlenecks and queue spillbacks onto the main lanes of the freeway or arterial, creating operational and safety concerns. While there is literature or guidance for ALs on freeways, there is minimal design guidance for ALs on frontage roads. This study systematically examines various design elements of ALs on frontage roads and the design parameters that influence these design elements by leveraging microsimulation. The key purpose of this study is to develop recommendations for the length of ALs in six common frontage road design configurations based on the selected nine design parameters. More than 3,000 simulation runs were performed to develop and compare guidance with the existing design manuals. The results reveal new insights that would complement existing design guidance.

Spring–Mass–Damper-Based Platooning Logic for Automated Vehicles

This paper applies a classical physics-based model to control platooning autonomous vehicles (AVs) in a commercial traffic simulation software. In the spring–mass–damper (SMD) model, each vehicle is assumed as a mass coupled with its preceding vehicle with a spring and a damper: the spring constant and damper coefficient control spacing and speed adoption between vehicles. Limitations on the platooning-oriented communication range and number of vehicles in each platoon are applied to the model to reflect real-world circumstances and avoid overlengthened platoons. The SMD model controls both intra-platoon and inter-platoon interactions. Initial evaluation of the model reveals that it does not cause a negative spacing error between AVs in a harsh deceleration scenario, guaranteeing safety. Besides that, the SMD model produces a smaller positive average spacing error than the VISSIM built-in platooning module, which prevents maximum throughput drop. The simulation result for a regular highway section reveals that the proposed platooning algorithm increases the maximum throughput by 10%, 29%, and 63% under 10%, 50%, and full market penetration rate (MPR) of AVs, respectively, with a 0.5 s response time. A merging section with different volume combinations on the main section and merging section and different MPRs of AVs is also modeled to test inter-platoon spacing policy effectiveness in accommodating merging vehicles. Travel time reductions of 20% and 4% are gained under a low MPR of AVs on the main lane and merging lane, respectively. Meanwhile, a more noticeable travel time reduction is observed in both main lane and merging lanes and under all volume combinations in higher AV MPRs.

Game Theoretic Merging Behavior Control for Autonomous Vehicle at Highway On-Ramp

In the most of previous studies, social interactions between vehicles are not considered explicitly when designing decision making and motion planning module. Nevertheless, the strong interaction exists in the most of driving scenarios, especially in highway junction. This paper presents a game theoretic merging behavior control system for autonomous vehicle at on-ramp junction considering the interaction between the merging vehicle and following vehicle in the main lane. In this work, a driving style estimation is proposed to deal with the heterogeneity of driving style. Then we adopt a model predictive control (MPC) method to plan the optimal merging trajectory based on the game theoretic decision making result. Finally, simulation and Human-in-the-loop (HIL) experiment result shows the effectiveness of our approach in on-ramp merging scenario.

Stability Analysis and Speed-Coordinated Control of Mixed Traffic Flow in Expressway Merging Area

This paper considers the stability of mixed traffic flow and the necessity of speed control to achieve safety and efficiency goals. Therefore, a speed-coordinated control model is proposed for mixed traffic flow based on stability analysis at an expressway merging area. Firstly, stability intervals are obtained by using an intracluster stability analysis in an intercluster. Secondly, a speed-coordinated control model is set up considering the stability characteristics in a merging area. Finally, an objective function is developed, which considers time-to-collision (TTC), dynamic space occupancy (DSO), and vehicle specific power (VSP). A numerical simulation is built up to analyze the traffic conditions and stability by using the proposed model against a null scenario without using the proposed model. The analysis results indicate that the stability of the intracluster has two regions, and the stability of the intercluster is mainly affected by the speed fluctuation and the distance between the merging cluster and the vehicles on the main road. Secondly, the proposed model tends to gradually achieve a steady state when the position reaches 180 m. Meanwhile, the efficiency of the model is found to be the best when the minimum safe-distance interval is set at (18, 27). In addition, the volatility of TTC drops by 5% and the DSO has reached 11.99% in the acceleration lane optimization together with 18.37% in the main lane optimization. The frequency is found to be the highest when the VSP reaches (10, 20), and the optimized efficiency reaches 45%–50%. The model proposed in this paper will effectively analyze the stability characteristics of mixed traffic flow and provides a research foundation for the stability of mixed traffic flow. Moreover, this model builds up a multi-objective-oriented speed-coordinated control scheme for high-efficiency operations in the merging area and provides technical support for traffic management in the future.

Guest editorial: Decision making and control for connected and automated vehicles

Guest editorial: Decision making and control for connected and automated vehicles

An integrated two‐dimensional merging trajectory optimization model for automated vehicles considering mixed traffic flow

Recently, automated vehicles have been recognized as a promising tool to address the problem of on-ramp merging. However, the complexity of the problem includes ignorance of the vehicle's lateral dynamics, the limitation of the fixed merging point, the mismatch problem caused by the sequential optimization scheme, and the fixed terminal states assumption. These factors make it intractable in practical driving scenarios. This paper proposed an integrated optimization model for on-ramp automated vehicles, which can guide the vehicle to complete the merging behaviour from the ramp lane to the main lane safely and efficiently. A merging path is first constructed in the two-dimensional plane with two critical parameters recommended by a neural network predictor, enabling it to incorporate both longitudinal and lateral dynamics. Then, an integrated Mixed Integer Quadratic Program (MIQP) model is built to determine the optimal velocity profiles and merging gap simultaneously while considering the safety and efficiency factors. Specifically, with the introduction of discretization and linearization techniques, linear collision avoidance constraints and smooth transition constraints can be built, which can address the challenging computational problem. The effectiveness of the proposed model is validated through the microscopic and macroscopic numerical results under different levels of mixed traffic.

Modeling the heterogeneous traffic flow considering mean expected velocity field and effect of two-lane communication under connected environment

With the increasing popularity of the autonomous vehicles, heterogeneous traffic flow of autonomous vehicles (AVs) and human-driving vehicles (HDVs) will exist for long time. Based on single-lane mean expected velocity field model (MEV model), an improved two-lane heterogeneous car-following model (MEVTC model) is proposed which considers the mean expected velocity field of main lane and mean velocity field of adjacent lane in a connected environment. The strength factor of two fields are key parameters. Linear and nonlinear methods are used to reveal the basic characteristics of traffic flow under the new model. Theoretical results show that greater parameters mean larger stability regions. The MEVTC model is verified by numerical simulation, the results show that comparing with MEV model, MEVTC model can reduce the headway fluctuation by 11.2% and increase the traffic flow by 4.2%. With increased strength factor of two fields, the traffic flow becomes more stable However, the influence of the adjacent lane field on vehicle driving is dramatically smaller than main lane field. In addition, the higher penetration rate of the AVs is also good for the stability of traffic flow.

Optimizing guidance signage system to improve drivers’ lane-changing behavior at the expressway toll plaza

Although ETC (Electronic Toll Collection) has been widely implemented in vehicles in China in recent years, the channel guidance signage system on expressways has not been updated accordingly. Late lane-changing occurs when drivers are confused about the correct channel to enter, leading to increased crash risks and traffic congestion in front of the toll. The paper aims to optimize the current guidance signage systems, given the high proportion of ETC vehicles on Chinese expressways, and evaluate its effects on the drivers’ lane-changing behavior when passing through the expressway toll channels. A driving simulator experiment was conducted to test four scenarios: Original sign plan, Partial Manual Toll Collection (MTC) sign plan, Complete MTC sign plan and Complete MTC sign with Voice warning plan. Forty participants with a valid driver's license completed the four scenarios, and their behavior performances (e.g., decision-making of lane-changing, response time, average speed and deceleration) in the main lane in front of the toll booth were analyzed. The results showed that compared to the Original sign plan and Partial MTC sign plans, the Complete MTC sign plans (with and without voice warning) played a significant role in improving the MTC vehicle drivers’ lane-changing behaviors. The improvement included earlier initiated lane-changing, shortened response time, lower deceleration rate and extended lane-changing duration distance. The findings of this study have important implications for expressway designers and relevant management departments to optimize the current guidance signage and enhance traffic safety and efficiency at the toll plaza.

Modeling of Traffic Flow on Roundabouts

The aim of this research is to create the modeling of roundabouts. First of all, the three-arm roundabout is created for validation with the existing model. Then, the model is expanded to the four-arm roundabout. In the development of a modern intelligent transportation system, the effectiveness of dealing with the non-linear, time-varying and congested traffic flow is imperative in achieving traffic control and accuracy. In this paper, the roundabout is modelled as a circuit of 2×2 junction comprising a main lane and a secondary lane. The rotation of the roundabout is in the clockwise direction, as in the case of Malaysia. In mathematical modelling, the traffic flow is created, based on one-dimensional hyperbolic conservation laws which are represented by non-linear partial differential equations where the unknown variable is a conserved quantity. As a scheme used in the computation and analysis, the Godunov method computes the fluxes at the interfaces of each cell in order to advance the solution of a Riemann Problem. In addition, the Courant-Friedrichs-Levy (CFL) condition is proposed and used to ensure the stability and accuracy of the numerical algorithm where the time step is not a constant. The optimization on the roundabout for Total Travel Time and Total Waiting Time with several parameters is applied to generate numerous results which will assist in assessing the reasonableness of the roundabout. The comparison data of the three-arm roundabout with our model and the existing model are discussed. In comparison, our results show similar properties with higher readings than in other published papers because our calculations involved all arms and roads. In addition, the comparison data between three-arm and four-arm roundabouts are reasonable and logical. Lastly, our model is more flexible and realistic, as compared to the existing model.

How impressions of other drivers affect one’s behavior when merging lanes

In recent years, systems have been developed to realize automatic driving based on objective information such as the relative distance and relative speed between vehicles. However, humans still must drive in complex situations, for instance, when merging lanes. In such driving situations, it is possible that people make decisions based not only on objective information, but also on subjective information. This study examined how subjective information, specifically, a driver’s impression of the other vehicle, affects the decision to merge in front of or behind the other vehicle when merging lanes on a highway. Twenty participants (nmale = 10; nfemale = 10; Mage = 43.92 [SDage = 11.40]) joined two experiments, Days 1E and 2E, using a driving simulator. Two months after participating in Day 1E the participants joined Day 2E. In the Day 1E, they drove either on the merging lane or the main lane and merged lanes while considering the other vehicle driving along the adjacent lane. This experiment measured the probability that the participants drove in front of another vehicle upon merging, which is defined as “lead probability.” The Day 2E was similar to 1E, except for the manipulation of the participants’ impression of the other vehicle as being aggressive/cautious via acceleration/deceleration of the other vehicle, and through the contents of the instructions regarding the other vehicle’s driving characteristics. In the Day 2E, the participants were randomly assigned to two: Aggressive or Cautious conditions. As the result of comparing the lead probabilities, it was found that only when the participants were driving on the merging lane and had the impression that the other vehicle is aggressive, the impression lowered the lead probability. The result indicates that people make decisions based not only on objective information but also on subjective information for specific driving situations, such as merging lanes. These findings can help in the development of automated driving systems that allow safer merging.

Design and evaluation of cooperative human–machine interface for changing lanes in conditional driving automation

This study analyzes the impact of cooperative human–machine interface designs on drivers’ trust in and interaction with automated driving systems (ADSs) during lane changes on highways. While drivers’ inappropriate trust in ADSs can affect their behavior toward the system, capability to detect inadequate system performance, and perception of surrounding traffic disturbances, their engagement in the automated process can improve their comprehension of the system and traffic conditions, which is necessary for the safe practice of automated driving. Forty drivers practiced conditional driving automation in a driving simulator and encountered traffic congestion on the main lane of a two-lane highway. Four ADS designs were proposed to bypass the congestion. ADS-1 detects the congestion and synchronizes the speed accordingly. ADS-2 requests the driver to resume manual control and overtake the congestion. ADS-3 requests the driver to push a button to let the system overtakes the congestion automatically. ADS-4 overtakes the congestion automatically after informing the driver, while the driver can cancel it by pushing a button within 6 s. In all these conditions, driver intervention was optional. Although the drivers preferred and trusted ADS-1 and ADS-2 more than ADS-3 and ADS-4, the results indicate significant improvements in the driving performance and system usage under ADS-3 and ADS-4. Driving with ADS-3 improved drivers’ engagement and reduced the requirement for control transfer compared with other systems. However, the time headway between the subject and adjacent vehicles indicated that lane changes were more critical under ADS-3 and ADS-4 than ADS-1 and ADS-2. Such deficiency of alignment between driver perception and safe behaviors has implications for the design of future studies and systems that need to balance satisfaction and safety. These observations are likely to improve driver interaction with automated vehicles.

Proposing Lane and Obstacle Detection Algorithm Using YOLO to Control Self-Driving Cars on Advanced Networks

Developing self-driving cars is an important foundation for the development of intelligent transportation systems with advanced telecommunications network infrastructure such as 6G networks. The paper mentions two main problems, namely, lane detection and obstacle detection (road signs, traffic lights, vehicles ahead, etc.) through image processing algorithms. To solve problems such as low detection accuracy of traditional image processing methods and poor real-time performance of methods based on deep learning methods, lane and object detection algorithm barriers for smart traffic are proposed. We first convert the distorting image caused by the camera and use a threshold algorithm for the lane detection algorithm. The image with a top-down view is then determined through the extraction of a region of interest and inverse perspective transform. Finally, we implement the sliding window method to determine pixels belonging to each lane and adapt it to a quadratic equation. YOLO algorithm is suitable for identifying many types of obstacles for identification problems. Finally, we use real-time videos and the TuSimple dataset to perform simulations for the proposed algorithm. The simulation results show that the accuracy of the proposal for detecting lanes is 97.91% and the processing time is 0.0021 seconds. The accuracy of the proposal for detecting obstacles is 81.90%, and the processing time is 0.022 seconds. Compared with the traditional image processing method, the average accuracy and execution time of the proposed method are 89.90% and 0.024 seconds, which is a strong antinoise ability. The results prove that the proposed algorithm can be deployed for self-driving car systems with a high processing speed of the advanced network.