Road Capacity Research Articles

An Improved Longitudinal Driving Car-Following System Considering the Safe Time Domain Strategy.

Car-following models are crucial in adaptive cruise control systems, making them essential for developing intelligent transportation systems. This study investigates the characteristics of high-speed traffic flow by analyzing the relationship between headway distance and dynamic desired distance. Building upon the optimal velocity model theory, this paper proposes a novel traffic car-following computing system in the time domain by incorporating an absolutely safe time headway strategy and a relatively safe time headway strategy to adapt to the dynamic changes in high-speed traffic flow. The interpretable physical law of motion is used to compute and analyze the car-following behavior of the vehicle. Three different types of car-following behaviors are modeled, and the calculation relationship is optimized to reduce the number of parameters required in the model's adjustment. Furthermore, we improved the calculation of dynamic expected distance in the Intelligent Driver Model (IDM) to better suit actual road traffic conditions. The improved model was then calibrated through simulations that replicated changes in traffic flow. The calibration results demonstrate significant advantages of our new model in improving average traffic flow speed and vehicle speed stability. Compared to the classic car-following model IDM, our proposed model increases road capacity by 8.9%. These findings highlight its potential for widespread application within future intelligent transportation systems. This study optimizes the theoretical framework of car-following models and provides robust technical support for enhancing efficiency within high-speed transportation systems.

Evaluasi Kinerja APILL di Simpang Empat Bundaran Burung Kota Palangka Raya

Burung Roundabout is an important roundabout for mobilizing the activities of people entering and leaving the city of Palangka Raya, with the increase in population and the rise in community activities the density of vehicles also increases significantly every year. Traffic problems can occur if there is a lack of coordination in each arm of the roundabout. The research objective is to know the performance of Weaving Area and the performance of APILL at Burung Roundabout. The obtained data consists of quantitative data from field survey data. The data is analyzed using Indonesian Road Capacity Manual (MKJI, 1997). The research result using the calculations from (MKJI, 1997) for the Weaving Area section show that the maximum Capacity (C) obtained is 11,125 smp/h at the DA section. The average traffic delay at the roundabout is 0,77 second/smp with the highest delay index (DS) is 0,22 at the CD section. Consequently the service level during peak hours is classified as grade A. The analysis of APILL at Burung roundabout has good traffic flow result. The highest capacity on the southern arm is 1566 smp/hour and the highest delay is 21 second/smp. The highest queue length is 22 meters on the Southern with a highest saturation degree of 0,44 on the Southern with indicates level of service index C.

Integrating vision and lidar based hyperlocal metadata for optimal capacity expansion planning in hillside road networks

The rapidly expanding population and scarcity of affordable housing in many urban areas, such as Los Angeles, have resulted in large inventories of structures in hilly landscapes. Such urbanization has also rendered road capacities inadequate in many instances, with hazards such as floods, fires, and earthquakes posing additional risks to such inventory. Planning construction activities such as widening, structural, and geotechnical retrofits to increase capacity and resiliency by cutting through slopes and incorporating landslide protection measures requires hyperlocal information for road segments in hillside areas. Performing traditional surveys for large areas of such road networks can be both time-consuming and cost prohibitive. At the same time, data acquired from satellites may not provide the required spatial resolution for planning, especially regarding road-adjacent features such as slopes. This paper proposes a novel framework to fuse hyperlocal data regarding road and adjacent slopes gathered from the street-level mobile mapper equipped with cameras and lidar into the network design problem (NDP) to develop an optimal road width expansion plan. The hyperlocal features are derived from a colorized point cloud map and deep learning techniques to estimate the relevant features in hillside landscapes. Specifically, a deep learning-based segmentation and detection algorithms combined with novel point cloud processing techniques are used to obtain a spatially dense profile of the road and the adjacent slope. By leveraging such hyperlocal information, we explore all the potential road capacity and improvement options for road capacity expansion. Furthermore, we demonstrate the advantages of our proposed method over conventional techniques, particularly working with budget constraints. In terms of novel contributions, incorporating hyperlocal information into NDP for hillside road capacity expansion is novel, as well as algorithms to automatically detect and characterize relevant roadside features from remotely sensed lidar point clouds.

Performance Evaluation of Urban Road Sections on The Taman - Sepanjang Highway

munity activities which are dominated by shops, offices and education activities and are directly adjacent to dense residential communities. The volume of vehicles passing through this road is quite dense, such as motorbikes, light vehicles and heavy vehicles, plus side obstacles that disrupt the smooth flow of traffic, especially during peak hours. The method used for this research is the 1997 Indonesian Road Capacity Manual (MKJI) method and the main indicator is the degree of saturation (DS). The results of the analysis show that the performance of the Taman - Sepanjang Highway sections (Highway Kalijaten Segment and Ngelom Segment) in existing conditions does not meet the 1997 MKJI feasibility standards. The degree of saturation value for highway Kalijaten is 1.00 and highway Ngelom is 0.87. So both roads need to improve road performance. The alternatives are widening the road, the saturation degree (DS), widening the road and removing side obstacles, become a one-way road. By implementing those alternative, Taman - Sepanjang Highway was expected to meet degree of saturation by MKJI standard.

Integrated Parking Spaces Arrangement in Commercial Areas (Case Study: Cirebon City)

The effect of on street parking in urban commercial areas can cause a degradation of road performance. Therefore, the development of an integrated parking system is crucial to be carried out in commercial areas so that the performance of road sections does not degrade and does not cause heavy congestion. This study aims to provide recommendations for integrated parking locations based on existing parking conditions in the study area, so that they can be integrated and combined in one location. The method used is a primary survey that refers to the guidelines of the Indonesian Road Capacity Manual (IRCM) 1997 in analyzing traffic performance, and refer to the Guidelines for the Implementation of Parking Facilities 1997 in analyzing parking conditions. Meanwhile, for recommendations in determining alternative parking locations using SWOT analysis. The result of this research is the proposed location for integrated parking at Pasar Balong with the recommendation of a 4-floor building. The SWOT analysis showed that its strengths are its strategic location and high parking demand, its weaknesses are land limitations and lack of integrated parking management, its opportunities are potential for revenue and increased traffic flow, and its threats are resistance from local businesses and significant investment needs. The implication of this study is to provide a solution to the problem of roadside parking in commercial areas that interfere with traffic flow, improve the efficiency and accessibility of parking facilities for the community, and become a reference for further research on integrated parking management in other commercial areas.

Graph-Based Traffic Forecasting with the Dynamics of Road Symmetry and Capacity Performance

Symmetry in traffic patterns is a fundamental aspect of intelligent transportation systems, aiming to precisely predict traffic flow in real time despite the complex interplay of spatial and temporal factors. This paper presents a novel method of traffic forecasting that incorporates parameters related to road symmetry into a Graph Convolution Network model. Our model is crafted to dynamically adjust to real-time changes in road conditions, including the presence of symmetric and asymmetric road layouts, which substantially influence traffic flow. We have developed a GCN model that not only accounts for standard traffic flow metrics but also integrates a matrix representing road symmetry. The model undergoes training and validation on the METR-LA dataset, showcasing a significant enhancement in prediction accuracy. In the comparative analysis of state-of-the-art methods, our model demonstrated a significant enhancement in performance, achieving 30.68% improvement in Mean Squared Error (MSE) and a 24.28% improvement in Mean Absolute Error (MAE) over the best-performing method. The implications of our research are profound for urban planners, traffic management systems, and navigation service providers, as it offers a more dependable tool for forecasting traffic conditions, aiding in road design, and refining route planning strategies based on the symmetry of road networks.

Comparative Analysis of Mlipahan Signaling Intersection Performance Using Vissim Ptv Software and Mkji Method 1997

The growth of motor vehicles in Surakarta from year to year always increases while road capacity does not develop. Therefore, there are often traffic jams everywhere. The discipline of every road user also plays an important role in overcoming congestion on the highway. Stages carried out from problem formulation, research objectives, and literature review, Then preliminary surveys, geometric surveys, vehicle volume surveys, and vehicle speed surveysMonday saturation degrees (DS) decreased after changing the cycle time. This means that the traffic volume at the Mlipahan intersection has decreased due to the resetting of traffic lights on Monday Road capacity: north 1,647 smp / hour, south 1,610 smp / hour, west 786 smp / hour, east 1,348 smp / hour. Saturation Degrees: North 1.15, South 1.12, West 1.15, and East 1.13. Queue Length: North 203 m, South 195 m, West 93 m, and East 145 m. obtained a value of 210 sec/smp. Sunday obtained Road capacity: North 1,763 smp / hour, South 1,549 smp / hour, West 818 smp / hour, and East 1,050 smp / hour. Saturation Degree: North 0.54, South 0.51, West 0.95, and East 0.91. Queue Length: North 92 m, South 89 m, West 87 m, and East 104 m. And the delay was obtained at 36 sec/smp. With PTV-VISSIM software, the queue length is obtained: North 97 m, South 129 m, West 198 m, and East 83 m. The delay was obtained at 72 sec/skr. And Service Level Intersection F or poor.

Analysis of Mixed Traffic Flow Characteristics Based on Fleet Composition

In urban road networks, the integration of connected and autonomous vehicles (CAV) significantly influences traffic flow patterns, with the Fleet Composition—representing the positioning of these vehicles within convoys—being crucial in dictating the symmetry of information exchange amongst them. First, the vehicle composition of the mixed traffic flow is analyzed, and the mathematical analytical expressions of the random distribution characteristics of different types of vehicles are constructed. Second, we analyze the vehicle according to human characteristics in different situations. Then, consider the following characteristics and reaction times of manual drivers, establish a mixed traffic flow following model, and validate the established following. Finally, the basic graph model considering Fleet Composition is derived, and the effects of reaction time, Fleet Composition, driver following characteristics, and other parameters on road capacity under different penetration rates of CAV are analyzed by a Python and SUMO joint simulation. Finally, the characteristics of mixed traffic flow at intersections were analyzed.

Theory-data dual driven car following model in traffic flow mixed of AVs and HDVs

To model the car following (CF) behavior of mixed traffic flow composed of autonomous vehicles (AVs) and human-driving vehicles (HDVs) in the future, this paper calibrated the lower control algorithm of AVs and proposed a model named theory-data dual driven stochastically generative adversarial networks (TDS-GAN) to describe the CF behavior of HDVs based on experimental data from mixed traffic flow. Firstly, the experimental scenario and collected data were introduced. Secondly, two transfer functions for the lower control algorithm of AVs were compared. Then, to account for the stochasticity of HDVs, the idea of physics-informed deep learning (PIDL) was used to improve generative adversarial networks (GAN) and integrate it with two-dimensional intelligent driver model (2D-IDM). Finally, the effectiveness of the model was verified from both a micro prediction and a macro simulation perspective. The influence of AVs on the stability of mixed traffic flow at different Market Penetration Rate (MPR) was also observed. The results show that TDS-GAN can effectively describe the following behavior and stochasticity of HDVs. When combined with CF model of AVs, it can depict the evolution of mixed traffic flow more accurately. Additionally, AVs can improve traffic flow stability under different penetration rates, and the effect is more significant with higher MPR. However, the introduction of AVs may not necessarily be positive in terms of road capacity.

Studi Kapasitas Dan Tingkat Pelayanan Jalan

Mr. Muhammad Hasan is street one of the entrance gates to Banda Aceh City. The condition of the road is in steady condition, with a two-lane, two-way type divided with a median of 1.5 m wide. The role of this road is very strategic, considering that if a tsunami occurs, this road is one of the community's escaped roads. The results of initial observations of this road are still in a comfortable condition to drive, but it is necessary to research the level of service to anticipate its role as an escape road. Based on that, we want to know how the level of service on Jalan Mr. Muhammad Hasan. The purpose of this study was to determine the level of service Jalan Mr. Muhammad Hasan using the 1997 MKJI method. Data were collected through a survey of traffic volume and speed for 3 (three) days, namely Thursday, Friday and Sunday. The duration of the survey is 07.00-18.00 with 8 (eight) surveyors. The traffic volume is multiplied by the number emp, so we get the amount of flow at peak hours in the morning, afternoon and evening. The result of recording speed in m/second is converted to km/hour. Furthermore, the capacity of city roads, free flow speed and degree of saturation is calculated. Based on the value of capacity, speed and degree of saturation, the value of road service level is obtained. Based on the calculation results, the highest peak hours on observation day occurred in the afternoon, namely Thursday at 15.45-16.45 (2144 p.m./hour), Friday at 16.15-17.15 (2295 p.m./hour) and Sunday at 17.00-18.00 as many as 1698 smp/hour. hour. The capacity of the road on the three observation days was 6178 pcu/hour and the speed was 53.01 km/hour. The lowest degree of saturation occurred on Sunday afternoon at 0.18 and the highest occurred on Friday at 0.54 and overall it was still below 0.75 so there was no need for a scenario. The level of service in the morning and afternoon (Thursday, Friday, Sunday) still shows a value of A, while on Monday afternoon it becomes C and on Friday and Sunday it slightly decreases to B.

Pengaruh Proporsi Kendaraan Terhadap Kecepatan Arus Lalu Lintas

Transportation is the movement of people or goods from one place to another using a vehicle driven by humans or machines. Along with its development, the number of vehicles in Banda Aceh is increasing. On the Tgk Chik Ditiro road, traffic jams often occur, because there are schools, offices, many traders who trade on the shoulder of the road and the sidewalk, there are several vehicles against the flow, and vehicles parked carelessly, there are delays or movement of traffic flow especially at the hour busy. Based on observations in the field, traffic flow at busy times is dominated by two wheels and four wheels, so that it affects the speed on the Tgk Chik Ditiro road in Banda Aceh City. The purpose of this research is to find out what percentage of the effect of the proportion of vehicles on road traffic flow and to get the value of the proportion of vehicles on the road. The results obtained for the highest traffic volume were obtained on Thursday 26 September 2019 at 17.00-18.00 amounting to 6669.60 pcu / hour, the value of road capacity was 4938 pcu / hour, while the level of road service with the degree of saturation obtained was 1.35 means the Jalan Tgk. Chik Ditiro Kota Banda Aceh is included in category F, where the flow is blocked, the speed is low, the volume is above capacity, and there is a delay. The results of traffic volume for 3 (three) days obtained the maximum proportion of two-wheeled vehicles on Thursday 26 September 2019 at 08.00-09.00 WIB with a value of 48.43%. For the Maximum Proportion of four-wheeled vehicles (LV) on Thursday 26 September 2019 at 17.00-18.00 WIB with a value of 74.77%. In the research, it can be seen that the dominant light vehicle growth affects these roads.

Integrated Optimization of Production Scheduling and Haulage Route Planning in Open-Pit Mines

In mining, deposits are divided into blocks, forming the basis for open-pit mine planning, covering production and haulage route planning. Current studies often stage optimization and lack the consideration of road capacity, leading to suboptimal solutions. A novel approach integrates production scheduling and haulage route planning through a bilevel optimization model. The upper-level model integrates ore mining constraints to establish a mixed-integer production scheduling model, minimizing haulage costs. Spatiotemporal correlation constraints for block mining are determined using a two-stage algorithm. The lower-level model incorporates road capacity, forming a haulage route optimization model based on multicommodity network flow. A solution algorithm with a distance penalty strategy facilitates feedback between the upper and lower levels, achieving optimal solutions. Tested on a real open-pit coal mine with over 5 million blocks, this approach reduces haulage costs by 10.06% compared to stage optimization. Additionally, this approach allows for adjusting haulage demand in both temporal and spatial dimensions, effectively preventing road congestion. This study advances rational mining processes and enhances the efficiency of open-pit mining haulage systems.

ANALISA KINERJA LALU LINTAS JALAN JENDERAL AHMAD YANI KOTA PALEMBANG

Traffic performance refers to the evaluation of the service quality of a road segment relative to the traffic flow through it. Road traffic performance assessment is measured by the degree of saturation and travel speed. Road capacity (C) is the ability of a road section to accommodate traffic flow in a certain time unit. Road capacity is influenced by the type of side obstacles and the frequency of occurrence. This research was conducted on Jalan Jenderal Ahmad Yani Campus A, Muhammadiyah University of Palembang to calculate road capacity (C) and traffic performance on Jalan Jenderal Ahmad Yani. Data analysis was carried out using the 2023 Indonesian Road Capacity Guide where road capacity and degree of saturation are road traffic performance parameters so that the value of the level of service is known. Based on the results of research and analysis that has been carried out located on Jalan Jenderal Ahmad Yani, Palembang, the road capacity (C) is 2,924 PCU/hour and the free flow speed (VB) value is 49.59 Km/hour, while the road traffic performance and level of service on the Jalan Simpang 4 Jakabaring-Jalan Jenderal Ahmad Yani section is 0.81 and is classified as category D (Flow is close to stable, speed can still be controlled, traffic volume is approaching capacity), while from the direction of Jalan Jenderal Ahmad Yani -Intersection 4 Jakabaring obtained a service level of 0.94 and was classified as category E (Unstable flow and sometimes stopping, traffic volume approaching capacity, low speed and changing).

PEMILIHAN MODA TRANSPORTASI OLEH MAHASISWA MENUJU KAMPUS 1 UNIVERSITAS PGRI SEMARANG

Transportation activities themselves require facilities and infrastructure to be used by the community in carrying out transfer activities to their destination. Congestion is a transportation problem caused by the increasing volume of motorized vehicles without being matched by road capacity. The choice of transportation mode is a separate reason for each person and will reflect the interest of one of the modes of transportation itself. Data collection used an online questionnaire, namely via the Google form which was distributed randomly to students studying at Campus 1 Universitas PGRI Semarang. And data processing of travellers was analyzed using descriptive statistics, and vehicle modes were analyzed using a binary difference logit model with the help of multiple linear regression equations. And produce student profile data that has been obtained, that the dominant student is from the FTI faculty, the dominant one is traveling, namely semester 4. The sex is dominated by male, the dominant mode of vehicle used is motorcycle, and the dominant driver's license is SIM C. Characteristics of ability found that students travel based on the amount of pocket money, expenses or vehicle operations and considerations for traveling.

Analysis of Traffic Flow Performance and Capacity on Captain Ismail Street, Tegal City

Tegal City is among of the cities where the population density is rather high. This causes high vehicle volumes and congestion at several points on the road. Street Captain Ismail is a road with a high level of activity and traffic jams at spesific times. The objective of this is with the purpose to recognize the elements that contribute to traffic flow on Captain Ismail road, so that ways can be suggested to overcome traffic jams that arise. This study uses numerical data from traffic volume, road capacity, road width and speed as data processing material. This study employs a literature study methodology, wich entails a thorough examination of the relevant literature namely by conducting an analysis based on MKJI 1977. The results of the research show that vehicle volume will continue to increase during holidays because this road section becomes an alternative route to the center Tegal City. The side resistance class in this area is low with a side resistance value of 224.1. The planned hourly volume data is 48.11 and the average speed on this road section is 38.9 - 40 km/hour. Based on data obtained, the Street Captain Ismail section has a service level of A with a degree of saturation of 0.24.

A Study on the Road Capacity Reduction Rate of Freeway Tunnel Section

A Study on the Road Capacity Reduction Rate of Freeway Tunnel Section

Peningkatan Kinerja Simpang Ciceri, Kota Serang dengan Model Penerapan Ruang Henti Khusus

The Ciceri intersection is in a densely populated urban area characterized by heavy traffic, particularly motorbikes. This is due to the nearby educational institutions, shops, offices, and a shopping center. The intersection faces numerous traffic conflicts, including crowded vehicle queues, irregular queuing by motorbikes, and improper lane usage by two- and four-wheeled vehicles. The phase setting of traffic signaling devices (APILL) at the Ciceri intersection has been implemented but has not solved the problem. This research aims to analyze the use of RHK to improve the performance of the Ciceri intersection using the Vissim model. The method is to test or simulate various RHK models at the research location. The results obtained can be applied to the RHK at two intersection legs, namely east and west, with a box-type RHK measuring 8m long and 2 x 3.5m wide, increasing the level of Service (LOS) from E to F. The results show a reduction in queues of 5.64 m and delays of 1.52 seconds on the north leg, as well as a reduction in queues of 7.85 m and a delay of 13.48 seconds on the south leg. These results show that RHK can effectively improve the performance of intersections with high traffic volumes without the need to increase physical road capacity.

Determination of Motorcycle Equivalent Unit and Road Capacity: A Case Study of Selected Road Sections of Kathmandu Valley

The research focused on road congestion in Kathmandu Valley, Nepal, caused by the prevalence of small motorized vehicles, especially motorcycles. The objective of the study was to quantify the impact of different vehicle classes on congestion by calculating Motorcycle Equivalent Units (MEU) and determining roadway capacity using speed and effective space parameters. The field data collected over two locations in Kathmandu Valley were analyzed using Speed Estimation from Video Data (SEV) software that revealed a strong correlation between vehicle speed and effective space, represented by a quadratic non-linear model. MEU values were determined for different vehicle classes, and fundamental speed-flow-density relationships were used to calculate roadway capacity. Vehicles like motorcycles, standard cars, big cars, utility, minibusses, buses, light commercial vehicles, two/three-axle trucks, and multi-axle trucks had MEU values of 1, 3.32, 4.91, 4.65, 9.22, 12.22, 6.72, 13.57 and 18.04 respectively. The study indicated peak capacities during the evening hours on specific road sections. For instance, the Gatthaghar-Kaushaltar and Balkumari-Gwarko sections reached their maximum capacities at 12,335 and 20,589 (motorcycles per hour per direction), respectively. The study emphasized the significant influence of speed on effective space and roadway capacity, suggesting further exploration of additional factors like driver characteristics, gender, age, income, road geometry, and level of service using MEU, along with the potential for developing a motorcycle simulation model in Kathmandu valley.

Determination of Passenger Car Unit and Capacity at Grades of Two Lane Undivided Highway: A Case Study of Khurkot–Dhulikhel Section of BP Highway

The majority of Nepal’s National Highway and feeder road system comprises two-lane highways with heterogeneous traffic conditions. Factors such as lane width, gradient, lateral clearance, and shoulder conditions can influence the passenger car unit (PCU) and roadway capacity. Recognizing that grade magnitude (%) is an important yet unexplored roadway factor in Nepal, and the present study primarily aims to estimate the passenger car unit on two-lane undivided hilly roads with gradients under prevailing heterogonous traffic conditions. This study aims to determine the PCU values and roadway capacity at grade under mixed nature traffic flow for a two-lane undivided highway. In this research, the necessary data were collected at five sections of BP highways using a digital video recorder, which was then analyzed to assess traffic characteristics and calculate PCU values. Using the PCU values, the road capacity was estimated using Greenshield’s model. For capacity estimation, flow and density were addressed using dynamic PCU values. This study reveals that the PCU of all categorized vehicles increases linearly with the increase in gradient while roadway capacity decreases with an increase in grade. It was observed that PCU values obtained for two-wheelers in all sections are smaller than the PCU values specified in NRS 2013, whereas for buses, trucks, and LCVs, they are higher than the PCUs given in NRS 2013. The study highlights the impact of road grade on the PCU for different vehicle categories on a highway. Additionally, the study demonstrates that the developed capacity values are realistic and consistent with the values presented in the Highway Capacity Manual (HCM) of developing countries such as Indonesia and China. These results are expected to be beneficial for practitioners and the ongoing effort to develop a highway capacity manual.

A Novel Technology Stack for Automated Road Quality Assessment Framework using Deep Learning Techniques

Road infrastructure plays a pivotal role in supporting societal, economic, and cultural progress. The capacity of a road refers to its ability to handle vehicular volume. Inadequate road capacity and the presence of defects like potholes and cracks result in suboptimal travel conditions and pose significant safety risks for drivers, cyclists, and pedestrians. The regular evaluation of these road quality aspects is essential for effective maintenance. However, current methods for assessing road capacity are time-consuming, subjective, and heavily reliant on manual labor. Moreover, existing deep learning-based approaches for detecting road defects often lack accuracy. To overcome these challenges, a fully automated and accurate system for evaluating road quality is imperative. Thus, the objective of this research work is to propose a novel technology stack for a comprehensive Automated Road Quality Assessment (ARQA) framework designed to assess road quality. The experimental findings demonstrate that the suggested vehicle detection and pothole detection methods work effectively and exhibit enhancements of 18% and 6%, respectively, in comparison to existing approaches.