Road Network Performance Research Articles

Dynamic Evaluation of Road Network Resilience to Traffic Accidents: An Emergency Management Perspective for Sustainable Cities in China

When assessing road network resilience, emergency management behavior should be considered, as this represents the road network’s capacity to adapt to and recover from traffic accidents. Given the timeliness and variability of emergency management behavior, deterministic approaches seem inadequate to represent real road network performance. Thus, this paper innovatively designs an emergency management perspective-based dynamic evaluation method of road network resilience to traffic accidents. Firstly, based on four stages of emergency management, a road network resilience evaluation index system encompassing resilience capabilities, resilience attributes and traffic accident emergency management ability indicators is constructed. Afterwards, the gray relational technique for order preference by similarity to the ideal solution (GRA-TOPSIS) evaluation method based on combination weighting, which integrates factor analysis with hesitant intuitionistic fuzzy expert scoring, is designed to quantify resilience. Finally, the obstacle degree model is utilized for identifying resilience constraints as the input of a long short-term memory (LSTM) model to predict the resilience variation trend. The fast road network of Shanghai in China is adopted as a case study, and the results indicate that road network resilience embodies significant spatial distribution characteristics. Road length, number of tractors, perception and response and disposal time of traffic accidents cast notable effects on resilience. Additionally, some roads are forecast to show descending resilience. The proposed method is valuable for helping policymakers identify current and potential vulnerable roads and to formulate proposals to effectively improve the resilience of urban agglomerations and promote sustainable cities.

A novel interval rough model for optimizing road network performance and safety

This paper introduces a novel Integrated Interval Rough Pivot Pairwise Relative Criteria Importance Assessment (IRN PIPRECIA) model combined with Interval Rough Combined Compromise Solution (IRN CoCoSo), marking a significant advancement in sustainable traffic flow management for commercial vehicles. This innovative merger is a first in literature, methodologically enhancing the evaluation of road sections based on critical parameters including passenger car equivalent (PCE) 85%, AADT, road conditions, and accident data. Our model systematically fills the research gap in holistic traffic performance analysis, providing a unique tool for prioritizing road safety and efficiency. The key scientific contribution is the model’s ability to integrate causal and consequential traffic factors into a single framework, offering a novel multi-criteria decision-making (MCDM) approach. Results, validated through various verification models, show the integrated model’s effectiveness in real-world scenarios, confirming its robustness and stability. With strong engineering application potential, our work supports urban planners and traffic managers in making informed, sustainable decisions. The model extends beyond traditional traffic analysis, promising a shift towards more adaptive, data-driven infrastructure management. Future research will aim to refine the criteria basis and explore real-time decision-making through advanced MCDM applications.

Co-evolutionary traffic signal control using reinforcement learning for road networks under stochastic capacity

A co-evolutionary traffic signal control using reinforcement learning approach (CORLA) is proposed for time-varying road networks under stochastic capacity. Classic reinforcement learning based traffic signal control cannot effectively reduce traffic congestion for large-scale road networks while standard evolutionary metaheuristics often suffer from significantly high computational cost. A co-evolutionary decomposition algorithm (CODA) is proposed to improve traffic mobility for urban road networks with time-varying traffic flow. To capture time-varying spatial evolution of traffic flow inside road links, a stochastic traffic model is presented. To fully consider road users’ response, a stochastic bi-level optimization problem (SBOP) is given where road users’ route choice can be fully taken into account. To efficiently implement CORLA in a large-scale road network against high-consequence realization for stochastic capacity, a coordinated co-evolutionary two phase control (CCTPC) is proposed. Numerical experiments are performed at a real-data city road network and various sizable traffic grids. As compared to state-of-the-art traffic signal control for various traffic conditions, obtained results showed that CCTPC exhibits sufficient gain of achieving road network performance and suffers from the least computational cost in all cases.

Impact of Toll Road on Performance of Road Network and Emissions: Case Study of Sragen Regency

Impact of Toll Road on Performance of Road Network and Emissions: Case Study of Sragen Regency

A novel regional traffic control strategy for mixed traffic system with the construction of congestion warning communities

Large-scale congestion can lead to traffic paralysis, which severely hampers the flow of vehicles and disrupts the normal functioning of urban traffic. Traffic optimization strategies can effectively improve the performance of road networks, but often ignore the impact of regional traffic conditions and equity. This paper presents a novel traffic strategy to solve regional traffic congestion in large cities, particularly focusing on mixed traffic scenarios of connected and non-connected vehicles. The proposed method involves monitoring the traffic condition of the congestion warning community and adjusting the internal access flow within each region. The problem is formulated as a Stackelberg game, with traffic policymakers and road users as the key players. The upper layer aims to control traffic access by issuing a community warning index, with the objective of minimizing congestion warning conditions within the community. This information is then disseminated to connected vehicles which utilize it to generate personalized route guidance, while non-connected vehicles remain unaffected. The lower-level objective is to allocate vehicles in the transportation network in a user-optimal manner. To solve the bi-level programming model, the paper introduces a variable neighborhood search approach based on graph theory. The Frank-Wolfe algorithm is used to solve the lower-level model, with a penalty function introduced to transform the constrained traffic assignment problem (TAP) into an unconstrained TAP. The proposed method is applied using the data of Beijing urban road network and a sensitivity analysis is conducted to examine the impacts of critical parameters, such as regional partitioning and mixed traffic proportion. The results show that the method exhibits improved optimization performance across different parameter settings, effectively utilizing idle links and contributing to a reduction in the occurrence of traffic warning regions.

Optimized Bridge Maintenance Strategies: A System Reliability–Based Approach to Enhancing Road Network Performance

Optimized Bridge Maintenance Strategies: A System Reliability–Based Approach to Enhancing Road Network Performance

Enhancing Urban Intersection Efficiency: Visible Light Communication and Learning-Based Control for Traffic Signal Optimization and Vehicle Management

This paper introduces a novel approach, Visible Light Communication (VLC), to optimize urban intersections by integrating VLC localization services with learning-based traffic signal control. The system enhances communication between connected vehicles and infrastructure using headlights, streetlights, and traffic signals to transmit information. Through Vehicle-to-Vehicle (V2V) and Infrastructure-to-Vehicle (I2V) interactions, joint data transmission and collection occur via mobile optical receivers. The goal is to reduce waiting times for pedestrians and vehicles, enhancing overall traffic safety by employing flexible and adaptive measures accommodating diverse traffic movements. VLC cooperative mechanisms, transmission range, relative pose concepts, and queue/request/response interactions help balance traffic flow and improve road network performance. Evaluation in the SUMO urban mobility simulator demonstrates advantages, reducing waiting and travel times for both vehicles and pedestrians. The system employs a reinforcement learning scheme for effective traffic signal scheduling, utilizing VLC-ready vehicles to communicate positions, destinations, and routes. Agents at intersections calculate optimal strategies, communicating to optimize overall traffic flow. The proposed decentralized and scalable approach, especially suitable for multi-intersection scenarios, showcases the feasibility of applying reinforcement learning in real-world traffic scenarios.

Road Maintenance Planning of the Fier-Vlore Road Axis, based on the Assessment and Forecast of AADT and Los Service Level

The relevance of this study lies in the fact that maintaining roads in good condition is an important condition for ensuring the safety and comfort of road traffic, as well as the economic development of the region. The aim of the study is to develop a method for planning road maintenance along the Fier-Vlore axis based on the assessment and forecast of the level of service AADT and LOS in order to improve the quality and safety of road traffic. The AADT and LOS service level estimation and forecast method is used to determine the performance of road networks and identify problem areas. The results of this study indicate that in the next 10 years, the level of service on this section of the road will be satisfactory and will be classified as “C”. However, after 2027 until 2032, the service level is expected to decline to category “D” and “E”, which could potentially lead to restrictions in manoeuvring and an increase in traffic accidents. In addition to reducing the distance, the construction of this Fier-Vlore Road has a significant impact both in reducing transport costs and in reducing the stress and anxiety caused by the old road. The main goal of the road is to provide comfort, safety, minimum cost and sustainability to the environment. In general, the use of the AADT and LOS Service level estimation and forecast method has significant practical value for planning investments in road maintenance and road infrastructure improvement.

Assessing airport ground access interventions: An integrated approach combining mode choice modeling and microscopic traffic simulation

Airport ground accessibility is an important and integral part of airport planning, which significantly impacts airport attractiveness and its environmental sustainability. In this paper, we propose the combined use of road micro-simulation with meso-scope discrete choice modeling to support the evaluation of airport access interventions. The proposed integrated framework allows us to appraise mode choice and infrastructural interventions simultaneously to accurately assess the performance of airport access road networks in accommodating larger traffic. We validate and demonstrate the benefits of the proposed approach by applying it to a real-world case study based on the Milan–Bergamo Airport (BGY), in which (i) we conduct an ex-post counterfactual analysis to assess the impact of the interventions undertaken to mitigate the large growth (54.6%) in the years 2013–2019, and (ii) evaluate future scenarios up to 2030 considering the additional expected growth and introduction of direct rail services. Results indicate that BGY’s ground access interventions have contributed to effectively accommodating traffic growth by significantly mitigating road congestion and associated pollutant emissions. Results also inform on the need and effectiveness of additional interventions to meet the substantial expected future growth.

Traffic Performance Analysis in The Traditional Market Area

Traffic performance is quantitative measurement that describes condition on a road. Congestion is caused high levels of activity, such as parking on the road and public transportation that drops off and picks up passengers, pedestrians walk on the road because there are no pedestrian facilities available, so that side obstacles become high. This research aims to improve traffic performance in Cibarusah Market Area. Traffic performance calculations based on PKJI 2023 and road network performance using PTV Vissim Modelling. Congestion that occurs can be seen from road performance indicators, namely VC Ratio 0,75, Speed 21.56 km/h with LOS F, and density 73.7 PCU/km. Meanwhile, intersection performance is assessed from 3 indicators, namely DS 0.82, queue opportunities 27 – 54%, and delay 25.09 sec/PCU with LOS D. The analytical methods used in this research are road performance analysis, intersection analysis, road network analysis, parking analysis, and pedestrian analysis. The results of the road performance increase with LOS E. Furthermore, intersection performance also increases with LOS C. Road network performance also improves, based on delay average from 25.27 to 11.02 seconds, speed average from 26.21 to 39.67 km/h, distance total from 22.997.28 to 23.401.59 km, and travel time total from 877.28 to 589.96 hours.

Enhancing Urban Traffic Management with Visible Light Communication and Reinforcement Learning

This paper introduces Visible Light Communication (VLC) to enhance traffic signal efficiency and vehicle trajectory management at urban intersections. A multi-intersection traffic control system is proposed, integrating VLC localization services with learning-based traffic signal control. VLC facilitates communication between connected vehicles and infrastructure using headlights, streetlights, and traffic signals to transmit information. By leveraging vehicle-to-vehicle (V2V) and infrastructure-to-vehicle (I2V) interactions, joint transmission and data collection are achieved via mobile optical receivers. The system aims to reduce waiting times for pedestrians and vehicles while improving overall traffic safety. It is designed to be flexible and adaptive, accommodating diverse traffic movements during multiple signal phases. VLC cooperative mechanisms, transmission range, relative pose concepts, and queue/request/response interactions help balance traffic flow between intersections, enhancing the overall road network performance.

Day-to-Day Road Pricing and Network Performance Analysis via Output Stability

Day-to-Day Road Pricing and Network Performance Analysis via Output Stability

Unlocking Traffic Control: Exploring Intersection Dynamics with Visible Light Communication

This paper introduces the use of Visible Light Communication (VLC) to enhance traffic signal efficiency and vehicle trajectory management at urban intersections. By integrating VLC localization with learning-based traffic signal control, a multi-intersection traffic system is proposed. VLC enables communication between connected vehicles and infrastructure through mobile optical receivers. The primary objectives are to reduce waiting times and improve overall traffic safety by accommodating diverse traffic movements during multiple signal phases. Cooperative mechanisms and queue/response interactions balance traffic flow between intersections, enhancing road network performance. A reinforcement learning scheme optimally schedules traffic signals, with agents at each intersection using VLC-enabled vehicle communication to improve traffic flow and overall system optimization. Evaluated using the SUMO urban mobility simulator, the system demonstrates reduced waiting and travel times. The decentralized and scalable nature of this approach highlights its potential applicability in real-world traffic scenarios.

Travel Demand Estimation for a Special Event using Pervasive Data: A Case Study of G20 Summit

Due to globalization and rapid development, the demand for travel and congestion are increasing, stressing the road networks. Furthermore, road networks are subjected to planned and unplanned disruptions, and these disruptions affect the road network performance by either damaging its components, fluctuating the travel demand, or doing both at the same time. Thus, assessing the change in travel demand and travel patterns during such disruptions is essential. Conventionally, travel demand has been estimated using a household travel survey (HTS). However, the HTS is not feasible for disrupted conditions because of its large sample size requirement and time-consuming methodology. However, with the advent of crowdsourced data, new methodologies have been proposed for estimating the travel demand, but most of these studies have focused on estimating demand for a typical day and not disrupted scenarios. Moreover, data sources utilized till now have low sample sizes or are unavailable for developing countries. To bridge this gap, the current study utilizes an automated planning tool called Rapidex to estimate the travel demand and pattern change for a planned disruption, i.e., the 18th G20 Summit, Delhi, using crowdsourced travel time data from TomTom API. Upon comparing the results of travel demand and travel patterns of typical days with G20 days, it was observed that travel demand was lower during G20. Moreover, it was observed that the zones where railway stations, interstate bus terminals, and G20 activities were focused had higher generation and attraction share than typical days. Other zones within the regulated area had lower generation and attraction rates, which can be because of travel restrictions imposed in these zones.

Kinerja Infrastruktur Pelayanan Jaringan Jalan Kabupaten di Wilayah Pengembangan Timur Kabupaten Bogor

The Eastern Development Region (WP Timur) of Bogor Regency, consisting of 7 districts, holds a strategic position and is experiencing rapid development. WP Timur is currently in the process of forming a new "Bogor Timur" Regency and is also the site of several national strategic projects. Infrastructure development, particularly road networks, must be able to anticipate the region's growth and changing needs. To improve the management of road infrastructure, an evaluation of the road network's performance is required.. The methodology involves (1) comparing the existing road variable values with the performance standards set by government regulations, (2) analyzing the connectivity index of the county road network, and (3) conducting an integrative assessment based on the analysis of various variables. The results of this research indicate that (1) Cariu District meets the standards for 8 road performance variables, including having good connectivity. Jonggol, Sukamakmur, and Tanjungsari Districts meet 5 variables with deficiencies in accessibility, mobility, road condition, and connectivity. Gunung Putri, Cileungsi, and Klapanunggal Districts meet only 3 variables with deficiencies in accessibility, mobility, and road condition. Gunung Putri and Cileungsi have low traffic loads, while Klapanunggal lacks connectivity. (2) New road construction is needed in Gunung Putri, Cileungsi, Klapanunggal, and Jonggol Districts based on Accessibility SPM, and in Gunung Putri, Cileungsi, Klapanunggal, Sukamakmur, and Tanjungsari Districts based on Mobility SPM. The construction of new roads aims to anticipate increased traffic volume and enhance connectivity. (3) Efforts are required to improve road conditions and maintenance in the 6 districts other than Cariu based on Road Condition SPM

Effect of Land Use Change to the Road Network Performance and Environmental Degradation

A change in land use or transport facilities is commonly known to be the factors behind the poor of urban transportation system quality. However, the result of field observation shown that the inadequate road performance as well as an environmental degradation due to the presence of Widya Mandira and Nusa Cencada universities and their supporting facilities and/or derived socio-economics' daily activities surrounding strongly indicate that there is a problem in the transportation system management quality. Therefore, the aim of this study is to evaluate the effect of daily large scale of activities of the two main campus to the road network performance and environmental quality surrounding, particularly around the Dusun I Village, Sub District of Penfui Timur, Kupang Regency, East Nusa Tenggara Province, Indonesia. It is hoped that the result could be used to increase the local authority capacity, especially in determining the priority program based on the functional condition of road infrastructure, and waste water and/or drainage system as well as trash management. Keywords: accessibility and mobility index; environment degradation; road capacity; traffic accident risk; transportation and land use integration

Improvement of road infrastructure on the example of the Center-South transport corridor of the Akchatau-Akzhal section

The study investigates the enhancement of road infrastructure in the Center-South transport corridor of the Akchatau-Akzhal section, addressing the challenges posed by rapid road pavement deterioration due to increased traffic flow. By analyzing the natural and climatic conditions of the area, optimal concentrations of additives were determined to improve the properties of bitumen and asphalt concrete, with a focus on increasing strength and durability. Specifically, the addition of monoethanolamine to bitumen at a concentration of 0.08% led to notable improvements in key properties. The needle penetration depth at 25°C decreased from 80 to 71, indicating enhanced consistency. Moreover, the ring and ball softening point increased from 52 to 56, demonstrating increased resistance to temperature variations. Stretchability at 40 improved from 65 to 70, highlighting enhanced flexibility and durability. The study emphasizes the critical importance of quality construction and regular maintenance to ensure the durability and resilience of road networks to various factors. By utilizing innovative technologies and materials, such as modified binders with additives, the study showcases the potential to significantly enhance the performance, safety, and efficiency of road networks while reducing costs and environmental impact. The findings underscore the need for continued research and implementation of optimized solutions to improve road infrastructure sustainability and longevity.

Diffusion of connected and autonomous vehicles concerning mode choice, policy interventions and sustainability impacts: A system dynamics modelling study

Connected and autonomous vehicles (CAV) have seen a rapid development over the past decade. However, wide diffusion of high level CAVs is still decades to come, and will depend on many technological, policy and public acceptance factors. Merging a traditional Bass Diffusion Model with a discrete choice model in a system dynamics approach, this study modelled CAV diffusion from 2020 to 2070 in the UK, considering mode choices of CAV private car, CAV car/ride sharing and CAV bus, their possible impacts on road network performance and sustainability, and the feedback of these impacts to CAV diffusion. Results of this study suggest that without interventions CAV diffusion will start to increase rapidly from 2035, and reach market saturation of 98% in around 2057. CAV diffusion will lead to reductions in average travel time, average travel cost, carbon emission and traffic accident. Training campaign, which prepares the general public to be ready for CAVs, is more effective in accelerating CAV diffusion than marketing campaign, which mainly targets the innovators and early adopters. Promoting shared CAVs and CAV public transport can contribute to more sustainable and more affordable mobility with CAVs, although this may lead to smaller CAV market size in terms of CAV sale, and the market size may reduce at a higher rate than sustainability enhancement.

Resilience-oriented recovery of flooded road networks during mega-sport events: a novel framework

This research presents a novel framework that employs the resilience index and metrics, building on previous studies, to conduct a sequential evaluation of flooded road network performance at each timestep throughout the recovery stage. Subsequently, the mathematical integration of the performance-time diagram produces the Recovery Resilience Index (RRI) used to evaluate any recovery strategy/sequence. Furthermore, a sensitivity analysis ensures the consistency of the results. As a case study, this research evaluated three post-flood interventions: Flood-susceptibility-based; Centrality-based; and Critical-links-first recovery strategies, within the context of the FIFA World Cup in Qatar, 2018. The results showed that the best strategy to be dealing with the critical-links-first and flood-susceptibility strategy to be the worst. The suggested framework will expand the options for recovery planning and resource allocation. Also, it will provide the policymakers with a recommendation to improve the recovery process during FIFA World Cup in Qatar, 2018 and any future mega event.

The impact of road infrastructure on regional development in South Labuhanbatu Regency, North Sumatra Province, Indonesia

Good road network performance can make the economy of an area more developed. Likewise, South Labuhanbatu Regency, which was only formed in 2008, needs to measure the extent of the effectiveness of road infrastructure. This study aims to analyze the performance of road network connectivity and road network relationships in supporting the regional economy. This research was conducted by assessing the Road Infrastructure Index (RPI) and Minimum Service Standards (MSS) and analyzing the relationship with economic performance. The results of the analysis show that the RII value of South Labuhanbatu Regency until 2017 was worth 4.77, entering the medium category. Government spending on road sub-sectors does not have a consistent pattern but has resulted in an RII that has increased since 2013 and the value of GRDP per capita which has also increased every year. For road services, the Accessibility Index has met the MSS, the Mobility Index has not met the MSS, and the accident rate has reached 0.0012/100000km of roads. The government’s expenditure on the road sub-sector each year is insignificant but produces an increasing RII. The construction of road network infrastructure in South Labuhanbatu Regency shows a positive correlation with economic growth.