Road Capacity Research Articles

Analysis of Road Network Performance in Pontianak at Jalan Sepakat 2 Reformasi, Padat Karya Using PTV VISUM

Jalan Sepakat 2, Reformasi, and Padat Karya are routes connecting strategic locations and educational institutions in Pontianak. As the population and economic activities grow, traffic volume increases, so a road performance analysis is needed to ensure the infrastructure can accommodate transportation needs and reduce potential congestion. This research uses primary data, such as road geometric data, traffic volume, and vehicle speed. Secondary data included location maps, population, motor vehicle numbers, trip generation, and attraction data. The analysis was based on the Indonesian Road Capacity Guidelines (PKJI) 2023 and PTV VISUM software. The analysis results 2024 showed a V/C Ratio of 0.59 with a service level of C and a speed of 31.18 km/hour. The 2029 projection shows a decline in performance with a V/C Ratio of 0.74, a service level of E, and a speed of 27.54 km/h. Jalan Reformasi was widened from 7.85 meters to 11 meters to improve performance, and Jalan Padat Karya from 6.25 meters to 8 meters. After the capacity increase, the 2029 projection shows improved performance, with the V/C Ratio decreasing to 0.63, the service level increasing to C, and the speed increasing to 31.27 km/h.

Satisfaction-Based Optimal Lane Change Modelling of Mixed Traffic Flow and Intersection Vehicle Guidance Control Method in an Intelligent and Connected Environment

The information interaction characteristics of connected vehicles are distinct from those of non-connected vehicles, thereby exerting an influence on the conventional traffic flow model. The original lane-changing model for non-connected vehicles is no longer applicable in the context of the new traffic flow environment. The modelling of the new hybrid traffic flow, comprising both connected and ordinary vehicles, is set to be a pivotal research topic in the coming years. The objective of this paper is to present a methodology for optimal mixed traffic flow dynamic modelling and cooperative control in intelligent and connected environments (ICE). The study utilizes the real-time perception and information interaction of connected vehicles for traffic information, taking into account the access characteristics of both connected and non-connected vehicles. The satisfaction-based free lane-changing and mandatory lane-changing models of connected vehicles are designed. Secondly, a mixed traffic flow lane-changing model based on influence characteristics is constructed for the influence area of connected vehicles. This model takes into account the degree of influence that connected vehicles have on non-connected vehicles, with different distances being considered respectively. Subsequently, a vehicle guidance strategy for mixed traffic flows comprising grid-connected and conventional vehicles is proposed. A variety of speed guidance scenarios are considered, with an in-depth analysis of the speed optimization of connected vehicles and the movement law of non-connected vehicles. This comprehensive analysis forms the foundation for the development of a vehicle guidance strategy for mixed traffic flows, with the overarching objective being to minimize the average delay of vehicles. In order to evaluate the effectiveness of the proposed method, the intersection of Gaota Road and Fangshui North Street in Yanqing District, Beijing, has been selected for analysis. The results of the study demonstrate that by modifying the density of the mixed traffic flow, the overall average speed of the mixed traffic flow declines as the density of vehicles increases. The findings reported in this study reflect the role of connected vehicles in enhancing road capacity, maximizing intersection capacity and mitigating the occurrence of queuing phenomena, and improving travel speed through the mixed traffic flow lane-changing model based on impact characteristics. This study also provides some guidance for future control of the mixed traffic flow formed by emergency vehicles and social vehicles and for realizing a smart city.

A Microscopic Traffic Model to Investigate the Effect of Connected Autonomous Vehicles at Bottlenecks and the Impact of Cyberattacks

Bottlenecks reduce both traffic safety and efficiency, resulting in congestion and collisions. The introduction of connected autonomous vehicles (CAVs) has had a significant impact on road networks and can improve traffic efficiency at bottlenecks. This paper proposes a microscopic traffic model to investigate CAV behavior at bottlenecks and examine the effect of cyberattacks. The model is developed using data collected from a roadside sensor node. It is implemented in MATLAB using the Euler scheme to simulate a platoon of vehicles on a circular road of length 1 km. The performance is compared with the intelligent driver (ID) model. The results obtained indicate that the road capacity with the proposed model is 1.4 times higher than with the ID model. Further, the proposed model results in nearly constant speeds with small variations, which is realistic. Conversely, the ID model produces large speed variations that are unrealistic. In addition, the proposed model results in less acceleration and deceleration, which leads to lower vehicle emissions and pollution. The efficiency is better than with the ID model due to CAV communication and coordination, so queues dissipate faster. The traffic flow with the proposed model increases as the density decreases, which is consistent with traffic dynamics. It is also shown that the proposed model can characterize CAV behavior under cyberattacks that cause disruptions in the data. Thus, it can be employed for traffic control and forecasting when bottleneck conditions exist and there is malicious behavior.

Analysis of Operational Efficiency at Unsignalized Intersections in Pontianak City

Congestion in Pontianak City significantly impacts traffic flow, affecting both efficiency and comfort of road transit. The city's unsignalized intersections, crucial for managing vehicle flow from multiple directions, are under scrutiny for their performance. A study using the Indonesian Road Capacity Guidelines (IRCG) has assessed intersections, that the degree of saturation often exceeds acceptable limits, leading to congestion and increased delays. The research highlights that the current capacity of these intersections is insufficient to handle the growing traffic demand. For instance, under maximum traffic flow conditions, one intersection recorded a total traffic flow of 2,978.20 pcu/hour against a capacity of 2,716.40 pcu/hour, resulting in a degree of saturation of 1.096. This indicates a need for interventions like installing traffic signals or modifying road geometry to enhance flow efficiency. Despite these findings, the analysis of existing conditions specific unsignalized intersections showed a level of service value of E and F, suggesting that these intersections currently require immediate improvements. However, to further improve intersection performance, recommendations include reducing side obstacles, enhancing road geometry, and installing two-phase traffic signals, which offer the highest capacity with minimal delay. These measures aim to ensure that Pontianak City's transportation infrastructure can effectively.

Enhancing Mixed Traffic Flow with Platoon Control and Lane Management for Connected and Autonomous Vehicles

As autonomous driving technology advances, connected and autonomous vehicles (CAVs) will coexist with human-driven vehicles (HDVs) for an extended period. The deployment of CAVs will alter traffic flow characteristics, making it crucial to investigate their impacts on mixed traffic. This study develops a hybrid control framework that integrates a platoon control strategy based on the “catch-up” mechanism with lane management for CAVs. The impacts of the proposed hybrid control framework on mixed traffic flow are evaluated through a series of macroscopic simulations, focusing on fundamental diagrams, traffic oscillations, and safety. The results illustrate a notable increase in road capacity with the rising market penetration rate (MPR) of CAVs, with significant improvements under the hybrid control framework, particularly at high MPRs. Additionally, traffic oscillations are mitigated, reducing shockwave propagation and enhancing efficiency under the hybrid control framework. Four surrogate safety measures, namely time to collision (TTC), criticality index function (CIF), deceleration rate to avoid a crash (DRAC), and total exposure time (TET), are utilized to evaluate traffic safety. The results indicate that collision risk is significantly reduced at high MPRs. The findings of this study provide valuable insights into the deployment of CAVs, using control strategies to improve mixed traffic flow operations.

A Flow-Speed Model for Motorways in England: Analysis Under Various Weather Conditions

This work proposes a single regime speed–flow model to fit the speed–flow relationship on the M25, London’s main motorway which is recurrently congested, especially near Heathrow Airport. The proposed model had a better performance compared with the existing classic models. A whole year’s field data on various sites of the M25 motorway were collected by the National Highways MIDAS (Motorway Incident Detection and Automatic Signalling) system and analysed. The proposed model was fitter on both four-lane and lane-by-lane conditions than the existing models, in terms of lower relative error and RMSE values and higher R2 values (minimum R2 = 0.79), which means the proposed model captured the speed–flow relationship better. In addition, the proposed model was used to fit traffic characteristics under different weather conditions and decided the threshold of the CM algorithms using the Gaussian function. The results showed that both free-flow speed and road capacity were significantly reduced by up to 7% and 11%, respectively, under different rainfall conditions, and that congestion management should be triggered in advance on rainy days. Further analysis of extensive data over a wider space and time is required to test the transferability of these findings to other contexts.

Road Capacity Management Training as An Effort to Strengthen Competence of the Transportation Workforce: A Collaborative Community Service Program

Road Capacity Management Training as An Effort to Strengthen Competence of the Transportation Workforce: A Collaborative Community Service Program

Mechatronics Application and Performance Analysis in Intelligent Transportation Systems

This paper presents a comprehensive analysis of the integration of mechatronics in intelligent transportation systems (ITS), elucidating its functional capabilities and limitations. As urbanization accelerates and traffic demand rises, the ITS has emerged as vital solutions for addressing traffic congestion and safety issues. In this regard, mechatronics technology plays a key role by enhancing the intelligence of traffic management, thereby improving the overall efficiency and safety of transportation networks. Thus, the paper provides a detailed analysis of the mechatronics application in intelligent traffic signal control, road condition monitoring and management, and vehicle positioning and navigation. In the domain of intelligent traffic signal control, mechatronics technology facilitates adaptive signal adjustments through real-time data collection and analysis, effectively alleviating traffic congestion and enhancing road capacity. In the field of road condition monitoring and management, this technology combines advanced sensors and monitoring equipment to realize accurate identification and dynamic monitoring of vehicles, providing powerful support for traffic management and law enforcement. In addition, the use of mechatronics technology in critical areas such as vehicle positioning and navigation markedly enhances road utilization, effectively mitigates traffic congestion, as well as supports sustainable urban development initiatives. Meanwhile, the performance of mechatronics in ITS, including real-time, intelligence, safety and reliability, is analyzed, highlighting its remarkable effect in enhancing the overall performance of ITS.

Analysis and Research on the Intelligent Control System of Comprehensive Traffic Signals

The existing urban traffic signal control system exhibits certain inefficiencies, including prolonged waiting times and frequent traffic congestion. Research indicates that the integration of neural networks can enhance the effectiveness of intelligent traffic control systems, potentially improving overall traffic flow and reducing delays. Neural network is a highly parallel, nonlinear and highly redundant system. Meanwhile, the self-learning and self-organizing capabilities of neural network have unique advantages for those systems that cannot establish accurate mathematical models. According to the characteristics of complex, variable and random traffic conditions at urban intersections, this paper analyzes the traffic signal control by using neural network control method. This paper introduces a design method of intelligent traffic light based on dynamic time adjustment of traffic flow. By detecting the traffic flow on site, and then allocating the green time of each lane according to the neural network algorithm, the traffic flow dynamic adjustment can be realized, and the traffic capacity of the intersection can be effectively improved. This kind of intelligent control traffic lights can effectively control traffic, and has obvious effects on dreading traffic flow, improving road capacity and reducing traffic accidents.

Effect of building designation on parking characteristics, road performance, and zoning regulation

If the capacity of the parking zone on buildings with great trip attractiveness rates is inadequate, it usually triggers on-street parking activity and its unintended derived impacts. Unfortunately, although this unintended situation may decrease traffic and road environmental quality, a similar situation always occurs. The initial field observation's result indicates that a change in building utilization may have influenced it. So, this study aims to assess the effect of parking accumulation rates due to a change in building utilization on the parking index and its impacts on road performance, including traffic accident risk. The existing parking index is influenced by parking accumulation and capacity, while the planning parking index is determined by comparing the parking accumulation and standardized parking space. In addition, the effect of on-street and road performance was assessed using results from similar previous studies. It was found that a change in building function significantly impacts the existing parking index value. It could not accommodate the increased trip rate, resulting in on-street parking activity. It influences a decrease in road capacity, travel speed, air pollutants, and sight distance (increasing accident risk level). This indicates that an institutional strengthening capability represented in an appropriate zoning regulation, which describes the type, number, and scale of activities allowed to be built in a particular corridor, is a compulsory requirement. Consequently, the ladder of urban land use planning should be re-reviewed. Implementing this new concept should be considered, especially in an urban fast-growth corridor.

The Effect of On-Street Parking Road Performance (Case Study on Jenderal Sudirman Road, Samarinda City at STA 0+400 up to STA 0+600)

As time goes by, the increase in population results in increased movement of people, goods, and services. This is related to movement which cannot be separated from the system that supports transportation movements. Congestion is a condition where the traffic flow passing on a road section exceeds the planned capacity of the road, resulting in the free speed of the road section approaching 0 km/hour, causing queues. The phenomenon of traffic jams is an interesting thing to study. The research aims to analyze the impact of parking activities on traffic performance and to determine alternative efforts to control parking on roads around Jalan Jendral Sudirman, Samarinda City at STA 0+400 to STA 0+600.The variables in the research consist of: parking activity, side obstacles, traffic volume, road capacity, traffic density, and road service level. Data analysis was carried out both quantitatively in the form of analysis of parking and traffic characteristics, as well as qualitative analysis of physical conditions (parking conditions) and land use in the Jenderal Sudirman road corridor. The research results show that Jalan Jenderal Sudirman has a ratio to road capacity or degree of saturation below 1, which is at 0.90 on both Saturday and Sunday, which means that the traffic flow is dense, the speed is unstable, sometimes it stops, demand is approaching capacity, and the speed at the research location is lower than 40 Km/hour. Operation speed begins to be limited by other vehicles and obstacles begin to be felt by surrounding vehicles, this is due to the influence of side obstacles and use of the surrounding land.

Capacity Increase Plan Analysis by Adding Lane to the Jakarta-Cikampek Toll Road

The Jakarta-Cikampek Toll Road serves as a vital route, connecting Jakarta to its eastern suburbs and facilitating both passenger travel and logistics operations. However, persistent congestion along this stretch of highway has prompted the need for a comprehensive assessment of its capacity performance. This study aims to evaluate the Jakarta-Cikampek Toll Road's capacity performance using the V/C ratio metric. The analysis encompasses the calculation of V/C ratio values for the years 2022–2023, forecasting peak-hour daily traffic volumes for 2024 under three distinct scenarios: (i) no capacity expansion, (ii) capacity expansion through the addition of one lane, and (iii) traffic management intervention involving one-lane contraflow. The findings reveal that the highest V/C ratio values for peak hours in 2024, without lane additions, are 0.65 for Lane A and 0.71 for Lane B. However, these values decrease to 0.49 for Lane A and 0.53 for Lane B when considering capacity expansion through lane addition or contraflow implementation. Therefore, to ensure compliance with the Minimum Service Standards (SPM) until the end of the concession period, it is recommended that the toll road operator implement capacity enhancement by adding one lane in each route.

Impact of connected and autonomous vehicles on road network resilience in Belgium

The advent of Connected and Automated Vehicles (CAVs) has ushered in substantial changes in the transportation sector, particularly impacting the resilience of road networks. CAVs can exchange real-time information about road conditions, allowing them to bypass congestion and optimise their routes, thereby enhancing network resilience through dynamic rerouting. Additionally, these vehicles significantly affect road capacity, further bolstering the overall resilience of the network. As a result, it is essential to assess the impact of CAVs on road network resilience comprehensively. However, to the best of the authors’ knowledge, there is a notable gap in research that thoroughly evaluates the resilience of large-scale road networks, taking into account all dimensions of resilience, such as redundancy, robustness, and recovery speed. This paper aims to fill this gap by assessing the influence of CAVs on the resilience of a large-scale road network in Belgium. Utilising a simulation-based approach, the study quantifies the network's resilience triangle, addressing all facets of network resilience. The findings reveal that the integration of CAVs can markedly improve network resilience under various scenarios, with improvements ranging from 4.4% at a 10% penetration rate to 59.9% at full penetration. These insights are valuable for researchers and policymakers focused on the implementation of autonomous vehicles.

Driving Automation Systems Penetration and Traffic Safety: Implications for Infrastructure Design and Policy

The increasing penetration of autonomous vehicles (AVs) presents new challenges and opportunities for road safety. This study aims to evaluate the impact of AV penetration rates on traffic safety through the use of microscopic simulation scenarios based on the Villaverde network in Madrid. Eleven scenarios were simulated with SAE Level 5 AV market penetration rates (MPRs) ranging from 0% to 100% in 10% increments. Vehicle conflicts, defined as instances where the time to collision was less than 1.5 s, were analyzed along with traffic composition and roadway characteristics. Multiple linear and multinomial logistic regression models were applied to examine the relationships between time-to-collision (TTC), conflict numbers, maximum conflict speed, and critical influencing factors such as vehicle type and road capacity. The results indicate that higher AV penetration rates generally improve traffic safety, although the coexistence of conventional vehicles and vehicles equipped with driving automation systems introduces traffic heterogeneity, potentially influencing safety outcomes. These findings suggest that while AVs have a positive effect on road safety, further analysis is needed to address the complexities introduced by mixed-traffic conditions.

Change in traffic volumes in construction work zones

The problem of bottlenecks on the road network is relevant, especially in cities with radial and radial-ring schemes, since in case of their occurrence on arterial radial streets, it is difficult to choose an alternative route due to the low capacity of secondary streets. One of these bottlenecks is the repair work area, where, due to the closure of one street, the detour is carried out by parallel routes, which increases the load on local streets and driveways. Traffic flow volumes in the repair work areas are investigated in this paper. A site was selected where repairs were carried out in 2023. A citywide street of signalized traffic was closed due to repair work. The authors have forecasted the volumes of traffic flow that will be moving. After the start of the repair work, the actual traffic volume was determined by field surveys. The research was conducted over three months. The results showed that in the first week, the volumes were 2% higher than predicted; in the second week, they corresponded to the predicted values, and starting from the third week, they began to decrease. Approximately the same volumes were observed between the seventh and twelfth weeks of the study. They were 18% lower than forecasted at the beginning of the study. Since the research results showed that drivers need about a month to choose an alternative route to bypass the most congested sections of the road network, a recommendation was made to install road signs informing about the detour a month before the start of the repair work. In our opinion, this recommendation will allow drivers to plan and choose an alternative detour route in advance so that the detour section is less congested at the beginning of the repair work.

Predicting bearing capacity and trafficability classes of forest roads using road properties and surrounding terrain information

Mills wish to maintain a year-round continuous flow of fresh roundwood, which is a major challenge during low-bearing capacity seasons in Finland, as there are few forest roads in the current network that are suitable for year-round use. This study explores methods to predict the bearing capacity of forest roads in Finland, using easily measurable road and terrain characteristics which can be potentially obtained through remote sensing. Traditional manual assessments of road conditions are labor-intensive, highlighting the need for alternative methods. The study found that road width is the most influential factor in predicting bearing capacity, with LiDAR data being potentially useful for measuring this variable. Despite moderate model results (R 2 = 25−34%, RMSE% = 36−38%), the trafficability classification showed low accuracy, peaking at 38.7%. Gamma-ray data added limited value in predicting road capacity, indicating that its utility is minimal compared to other factors such as road width.

TRAFFIC AND ROAD STUDY IN CONSTANTINE CITY: ANALYSIS OF TRAFFIC IN CONSTANTINE CITY

This study primarily aims to shed light on the traffic and road conditions in the city of Constantine. As a crucial measure in the transportation sector, traffic and road studies play a pivotal role in evaluating the efficiency of existing road networks, determining current and future traffic volumes, identifying bottlenecks, and proposing solutions through traffic redistribution and planning. To assess the current state of traffic and roads in Constantine and their adequacy in relation to the city's area and population, this study was conducted. Constantine was chosen due to its unique position as a hub for numerous major roads with high traffic volumes. Six out of the seven national roads traversing the entire province pass through Constantine. To comprehensively address the subject, the research is divided into three main sections: - Section One: Provides essential definitions related to the topic, such as road network, road capacity, traffic volume, etc. - Section Two: Delves into the details of traffic volume, its types, methods, and the significance of its study. - Section Three: Conducts a detailed analysis of traffic volume and roads in Constantine. Initially, the study relies on the administrative classification of roads to identify those within the study area. Subsequently, it analyzes the average traffic volume and traffic density on these roads.

Analysis of the Impact of Traffic on the Construction of the Jl. Underpass. Gatot Subroto, Medan City

Medan City, as the capital of North Sumatra Province, is facing severe traffic jams at the Jalan Gatot Subroto-Jalan Gagak Hitam intersection due to the rapid growth of vehicles. To overcome this problem, the Medan City Government plans to build an underpass to separate traffic flows and increase road capacity. This research aims to analyze the impact of traffic during the construction phase, by grouping vehicles into motorbikes, light vehicles and heavy vehicles, which are then converted into passenger cars (SMP). Research shows that the existing traffic volume is 2813.8 pcu/hour towards Jalan Ringroad and 2620.5 pcu/hour towards Jalan Asrama, which exceeds the road capacity. During the construction phase, traffic volume dropped significantly to 637.6 pcu/hour and 635.5 pcu/hour, which shows more stable traffic flow. construction of underpasses can effectively reduce future congestion, but careful planning is required to minimize negative impacts during the construction period. It is hoped that these results can provide important input in transportation planning in Medan City.

FAIRLANE: A multi-agent approach to priority lane management in diverse traffic composition

The rise of autonomous driving technologies prompts a reevaluation of traditional urban traffic control and lane management. Dedicated lanes for connected and autonomous vehicles (CAVs), with intermittent access for other vehicles, have been proven to enhance road capacity and reduce underutilization moderately. However, this assumes all non-CAVs are smart vehicles, which is different from the current baseline for the street vehicle mix. Presently, our streets feature a mix of CAVs, smart vehicles, and human-driven vehicles, and the research on dedicated lanes using the realistic mixed traffic environment is missing. In this paper, we investigate the enhancement of road utilization using realistic mixed traffic combinations and identify the penetration rate of CAVs and smart vehicles necessary to improve baseline utilization. Previous studies have focused on lane-management strategies in single-vehicle settings, neglecting the interaction of CAVs with neighboring CAVs and smart vehicles. Therefore, we propose a multi-agent reinforcement learning-based framework to facilitate fair utilization of priority lanes, considering driving comfort, traffic efficiency, and safety during lane-changing. Through multiple experiments on a realistic network, our results demonstrate that the proposed framework significantly improves traffic efficiency, particularly when the penetration rate of CAVs is below 40% and Semi-Autonomous Vehicles (SAVs) constitute 50% of the remaining vehicles. The framework outperforms traditional lane management strategies, reducing mean waiting time and increasing average speed. This study provides nuanced information on different vehicle penetration rates, enabling more informed decisions on when to install priority lanes. This highlights the importance of considering mixed traffic environments in designing autonomous vehicle infrastructure and sets the stage for future advancements in urban traffic management.

Analysis of Level of Service (LOS) of Urban Roads Using Multiple Linear Regression Models

Population growth and economic growth cause a person's mobility to increase. Sutomo Street, Pematangsiantar City is one of the roads that is quite congested because Sutomo Street is the center of Pematangsiantar city. The existence of the largest shopping center in the city of Pematangsiantar, which is Horas Market, causes a high level of community mobility around Horas Market. This research aims to determine the traffic volume, road capacity, and Road Level of Service (LoS) based on PKJI 2023, as well as knowing the relationship model and effect of traffic volume and road capacity on the Level of Service (LoS) of Sutomo Street, Pematangsiantar City using multiple linear regression methods with the help of IBM SPSS Statistics software. This research was carried out from Monday to Saturday at 07.00-19.00 WIB on Sutomo Street, Pematangsiantar City, which is precisely in front of the Pasar Horas, Building I, 200 meters long. Data collection on traffic volume and side obstacles is carried out with the help of cameras. From this research, it was found that the highest degree of saturation occurred on Saturday, 02 September 2023 at 12.00-13.00 WIB with a traffic volume of 2380.2 SMP/hour and a road capacity of 4161.6 SMP/hour so that the degree of saturation (Dj) was 0.57 with the road Level of Service (LoS) value being C (stable volume, speed influenced by traffic). The effect of variables X1 (traffic volume) and X2 (road capacity) can be explained simultaneously on the largest variable Y (degree of saturation) which is 99,8% with the multiple linear regression model equation, which is Y = 0,468 + 0,000222X1 – 0,000103X2. Based on partial and simultaneous hypothesis testing, Ho is rejected so that there is an effect of the independent variable on the dependent variable. This means that variables X1 and X2 effect variable Y.