Traffic Survey Research Articles

Carbon Emission from Transportation in Higher Learning Institutions: A Case Study at Universiti Tun Hussein Onn Malaysia

The carbon emissions stemming from transportation within the campus environment pose a significant challenge to mitigating climate change and environmental degradation. At Universiti Tun Hussein Onn Malaysia (UTHM), transportation, particularly by staff and students, has been identified as the primary contributor to greenhouse gas emissions. This study aims to assess the total carbon emissions from transportation at UTHM and analyze trends over three consecutive years (2021 to 2023). Data were obtained from the Traffic Unit of the Security Department, encompassing vehicle counts and traffic surveys conducted across five roads within the UTHM Campus. The findings revealed a concerning escalation in carbon emissions over the study period. In 2021, transportation activities accounted for 947.64 tCO<sub>2</sub>e, which surged to 1568.42 tCO<sub>2</sub>e in 2022 and further increased to 1679.88 tCO2e in 2023. Notably, Persiaran Tun Ghazali Shafie emerged as a hotspot area for carbon emissions in 2023, experiencing a staggering 95.76% rise compared to 2021, with recorded emissions of 610 tCO<sub>2</sub>e. The average carbon emissions across the five surveyed roads in 2023 soared by 73.84% compared to 2021, indicating a persistent upward trajectory in emissions. These findings underscore the urgent need for sustained carbon emissions monitoring and mitigation efforts at UTHM. Continuous assessment by UTHM authorities is imperative to identify and implement effective strategies for curbing carbon emissions within the campus environment. UTHM can be pivotal in fostering a more sustainable and environmentally responsible campus community by prioritizing emission reduction initiatives.

Electric Vehicle Charging Load Demand Forecasting in Different Functional Areas of Cities with Weighted Measurement Fusion UKF Algorithm

The forecasting of charging demand for electric vehicles (EVs) plays a vital role in maintaining grid stability and optimizing energy distribution. Therefore, an innovative method for the prediction of EV charging load demand is proposed in this study to address the downside of the existing techniques in capturing the spatial–temporal heterogeneity of electric vehicle (EV) charging loads and predicting the charging demand of electric vehicles. Additionally, an innovative method of electric vehicle charging load demand forecasting is proposed, which is based on the weighted measurement fusion unscented Kalman filter (UKF) algorithm, to improve the accuracy and efficiency of forecasting. First, the data collected from OpenStreetMap and Amap are used to analyze the distribution of urban point-of-interest (POI), to accurately classify the functional areas of the city, and to determine the distribution of the urban road network, laying a foundation for modeling. Second, the travel chain theory was applied to thoroughly analyze the travel characteristics of EV users. The Improved Floyd (IFloyd) algorithm is used to determine the optimal route. Also, a Monte Carlo simulation is performed to estimate the charging load for electric vehicle users in a specific region. Then, a weighted measurement fusion UKF (WMF–UKF) state estimator is introduced to enhance the accuracy of prediction, which effectively integrates multi-source data and enables a more detailed prediction of the spatial–temporal distribution of load demand. Finally, the proposed method is validated comparatively against traffic survey data and the existing methods by conducting a simulation experiment in an urban area. The results show that the method proposed in this paper is applicable to predict the peak hours more accurately compared to the reference method, with the accuracy of first peak prediction improved by 53.53% and that of second peak prediction improved by 23.23%. The results not only demonstrate the high performance of the WMF–UKF prediction model in forecasting peak periods but also underscore its potential in supporting grid operations and management, which provides a new solution to improving the accuracy of EV load demand forecasting.

Data Source Importance Evaluation for Highway Networks: A Complex Network-Based Approach

Data collection technologies or data sources are critical for highway network management. However, due to the limitations on available management resources, determining the importance of these data sources is necessary to allocate these resources reasonably. This study proposes a complex network based method for evaluating the importance of multiple data sources in highway networks. This method includes mainly three steps. First, the business-data source relation will be identified and formulated for the highway network. Second, a business data source complex network is built from the previously identified business-data relationship. Third, an entropy weight method is used to compute and rank the importance of data source nodes by combining three indexes of degree centrality (DC), closeness centrality (CC) and structural holes (SC) computed based on the complex network. The proposed method is applied and illustrated using the highway network of Xuzhou City, Jiangsu Province, China. The results show that among the data sources, the most important data source is the continuous traffic survey station, followed by an automatic gantry-based station and vehicle detectors-based system. Discussions on the limitations, applications and future studies are provided for the proposed approach.

Vehicle Localization Using Crowdsourced Data Collected on Urban Roads.

Vehicle localization using mounted sensors is an essential technology for various applications, including autonomous vehicles and road mapping. Achieving high positioning accuracy through the fusion of low-cost sensors is a topic of considerable interest. Recently, applications based on crowdsourced data from a large number of vehicles have received significant attention. Equipping standard vehicles with low-cost onboard sensors offers the advantage of collecting data from multiple drives over extensive road networks at a low operational cost. These vehicle trajectories and road observations can be utilized for traffic surveys, road inspections, and mapping. However, data obtained from low-cost devices are likely to be highly inaccurate. On urban roads, unlike highways, complex road structures and GNSS signal obstructions caused by buildings are common. This study proposes a reliable vehicle localization method using a large amount of crowdsourced data collected from urban roads. The proposed localization method is designed with consideration for the high inaccuracy of the data, the complexity of road structures, and the partial use of high-definition (HD) maps that account for environmental changes. The high inaccuracy of sensor data affects the reliability of localization. Therefore, the proposed method includes a reliability assessment of the localized vehicle poses. The performance of the proposed method was evaluated using data collected from buses operating in Seoul, Korea. The data used for the evaluation were collected 18 months after the creation of the HD maps.

Regional Truck Travel Characteristics Analysis and Freight Volume Estimation: Support for the Sustainable Development of Freight

In the field of freight transport, the goal of sustainable development requires us to improve the efficiency of freight transport while reducing its negative impact on the environment, such as reducing carbon emissions and noise pollution. There is no doubt that changes in freight characteristics and volumes are compatible with the objectives of sustainable development. Thus, mining the travel distribution and freight volume of trucks has an important supporting role in the freight transport industry. In terms of truck travel, most of the traditional approaches are based on the subjective definition of parameters from the trajectory data to obtain trips for certain vehicle types. As for freight volume, it is mostly estimated through manual surveys, which are heavy and inaccurate. In this study, a data-driven approach is adopted to obtain trips from the trajectory data of heavy trucks. Combined with the traffic percentage of different vehicle types collected by highway traffic survey stations, the trips of heavy trucks are extended to all trucks. The inter-city and intra-city freight volumes are estimated based on the average truck loads collected at the motorway entrance. The results show a higher proportion of intra-city trips by trucks in port cities and a higher proportion of inter-city trips by trucks in inland cities. Truck loading and unloading times are focused in the early morning or at night, and freight demand in Shandong Province is more concentrated in the south. These results would provide strong support for optimizing freight structures, improving transportation efficiency, and reducing transportation costs.

Vehicle Stock Numbers and Survival Functions for On-Road Exhaust Emissions Analysis in India: 1993–2018

Road transport plays a crucial role in sustaining all the personal and freight movement needs of residential, commercial, and industrial activities, and in Indian cities, big and small, vehicle exhaust emissions and dust from vehicle movement on the roads contribute to as much as 50% of particulate matter pollution in a year. Therefore, effective management of vehicle exhaust emissions is vital not only for improving current air quality but also for ensuring the long-term benefits from efforts to reduce air pollution. In the approved clean air action plans for 131 cities under the national clean air program (NCAP), more than 50% of the implementable actions are transport-centric. Having a reliable and replicable vehicle exhaust emissions inventory is essential for effective planning, which can help establish a baseline, support scenario analysis, and allow for tracking progress in the sector. This process begins with accessing accurate vehicle stock numbers, typically obtained from vehicle registration databases, traffic surveys, and other governmental records. Often, in low- and middle-income countries like India, these numbers require extensive data cleaning before they can be used for emissions and pollution analysis. This paper presents a cleaned, open-access vehicle stock database for India and outlines a methodology to build and maintain an in-use vehicle age-mix database for future years. The database covers the years 1993 to 2018 for the entire country and individual states, along with estimates of the age distribution of vehicles using survival functions. By offering a comprehensive and reliable data source, this paper aims to support sustainable national and urban air quality management efforts, helping policymakers and stakeholders make informed decisions to improve air quality and public health.

Analysis of E-Scooter Crashes in the City of Bari

The remarkable impact that e-scooters have had on the transportation system drives research on this phenomenon. The widespread use of e-scooters also poses several new safety issues, which should be necessarily studied. The aim of this paper points in this direction, investigating the main contributing factors, causes, and patterns of recorded e-scooter crashes, considering also different crash types and severity, using the City of Bari (Italy) as a case study. The crash dataset based on police reports and referring to the period July 2020–November 2022 (i.e., the first period of e-scooter implementation in the City of Bari) was investigated. Crashes were clustered according to several variables. No fatal crashes occurred, even though crashes mostly resulted in injuries (70%). Considering road type, divided roads were found to be less safe than undivided ones, due to higher mean speeds than on other roads and to a less constrained e-scooter driving behavior. Calm (off-peak) daytime hours seem to lead to more frequent e-scooter crashes with respect to both peak and nighttime hours, even if the latter hours are associated with an increased severity. Once controlled for exposure, season, lighting conditions, and the private/sharing ratio do not seem influential. E-scooters are more prone to be involved in single-vehicle and pedestrian crashes at segments than other vehicles, but they show similar crash trends than other vehicles (i.e., angle crashes) at intersections. As emerged from traffic surveys, not all e-scooter users were found to use cycle paths. Combining this information with crash data, it seems that not using cycle paths is considerably less safe than using them. Besides engineering measures and policies, awareness campaigns should be promoted to elicit safe users’ behavior and to tackle the several violations and misbehaviors emerging from the crash data.

PEAK HOUR FACTOR AT URBAN ROAD NETWORK SYSTEM WITH FIXED HOURLY INTERVAL AND MOVING HOURLY INTERVAL (A CASE STUDY AT URBAN ROAD IN CIMAHI CITY)

The Peak Hour Factor (PHF) is an important variable for determining road capacity. The value of PHF will vary greatly depending on location characteristics and classification of road functions. This study aims to obtain the estimated value of PHF in the urban road network system with variations in the classification of functions and types of roads. In addition this study also aims to obtain a method of approaching the PHF value near to fluctuations in traffic flow which has limited resources for surveys based on the duration specified in the traffic survey guidelines in Indonesia. The method used is descriptive statistical analysis and parametric test using Independent T sample test. The PHF is calculated based on Fixed Hourly Interval and Moving Hourly Interval and their inverse. The results of the study show the value of PHF in the road network system in urban areas for variations function and type of road that is in the range of 0.79 to 0.98 with an average of 0.91. Other findings show that the inverse method of Moving Hourly Interval can be used as an approach to obtain the PHF value under conditions of resource constraints

The Optimal Size of a Heterogeneous Air Taxi Fleet in Advanced Air Mobility: A Traffic Demand and Flight Scheduling Approach

Introducing Advanced Air Mobility (AAM) as a novel transportation mode poses unique challenges due to limited practical and empirical data. One of these challenges involves accurately estimating future passenger demand and the required number of air taxis, given uncertainties in modal shift dynamics, induced traffic patterns, and long-term price elasticity. In our study, we use mobility data obtained from a Dresden traffic survey and modal shift rates to estimate the demand for AAM air taxi operations for this regional use case. We organize these operations into an air taxi rotation schedule using a Mixed Integer Linear Programming (MILP) optimization model and set a tolerance for slight deviations from the requested arrival times for higher productivity. The resulting schedule aids in determining the AAM fleet size while accounting for flight performance, energy consumption, and battery charging requirements tailored to three distinct types of air taxi fleets. According to our case study, the methodology produces feasible and high-quality air taxi flight rotations within an efficient computational time of 1.5 h. The approach provides extensive insights into air taxi utilization, charging durations at various locations, and assists in fleet planning that adapts to varying, potentially uncertain, traffic demands. Our findings reveal an average productivity of 12 trips per day per air taxi, covering distances from 13 to 99 km. These outcomes contribute to a sustainable, business-focused implementation of AAM while highlighting the interaction between operational parameters and overall system performance and contributing to vertiport capacity considerations.

Framework for assessing bridges construction impact on work zone traffic using BrIM

This research presents a framework for visualizing bridge construction impact on work zone traffic using Bridge Information Modelling (BrIM) and Google Maps API. The framework consists of four modules. The first module contains the construction data of the bridge by reporting the construction's daily progress. The second module is designated to model traffic data of the work zone using Google Maps API, traffic Survey counting, and Google Earth Images. The third module performs a traffic simulation for the work zone, and calculating the user cost of different stages. The fourth module visualizes the bridge's construction using Bridge Information Modelling (BrIM) and virtual reality in the Twinmotion engine to demonstrate the construction stages and the corresponding traffic states. An actual case study of El-Nahas Bridge in Cairo city-Egypt is presented to demonstrate the main features of the developed framework and its practical aspects. The case study results reveal that the impact of the construction stages varies on work zone traffic throughout the project period. The impact greatly influences the traffic status at the beginning of the project associated with high user costs. Then, the impact declines in later stages depending on the type of construction activities in each stage.

Multi-Vehicle Tracking and Counting Framework in Average Daily Traffic Survey Using RT-DETR and ByteTrack

Multi-Vehicle Tracking and Counting Framework in Average Daily Traffic Survey Using RT-DETR and ByteTrack

ANALISA PENYEBAB KEMACETAN TERHADAP ARUS LALU LINTAS JALAN LINTAS SUMATERA PANGKALAN BALAI

This study focuses on survey studies on the analysis of the causes of congestion on the km15-km18 road sections. To find out the analysis of the causes of congestion, road capacity, vehicle volume, level of service, determine resolution of problems, and analyze average daily traffic by conducting field surveys for seven days. This research was conducted in 1 research segment, namely: on the Sumatran crossroads at Pangkalan Balai Km15-km18 "Analysis Of The Causes Of Congestion On Traffic Flow Of The Sumatra Traffic Road Pangkalan Balai". The purpose of this research is to determine the effect of narrowing on traffic performance on the Sumatra Highway Km 15 – Km 18. The research implementation method used is by means of an Average Daily Traffic (LHR) survey, namely collecting data directly at the research location. Based on the results of the analysis, it was found that the side barriers included high, the volume of vehicles with inadequate road capacity.

Analysis of APILL Interchange Capacity, Effective Approach Width, and Saturation Current Determination Using PKJI 2023.

In this research, data analysis uses the 2023 Indonesian Road Capacity Guidelines (PKJI) method to produce signalized intersection performance data including capacity, level and level of congestion, delays, impact of vehicle emissions as well as queue capacity and service level at the intersection. intersection. The results of this research can be used to re-plan routes so that route segment performance can operate optimally. This research requires primary and secondary data. Primary data was collected by conducting direct field surveys, while secondary data was obtained from relevant government agencies. Primary Data Collection is data obtained from the results of field surveys. The data includes: a. Environmental and geometric conditions at each intersection b. Vehicle volume is calculated using CCTV at each intersection. c. Calculating Determination of Effective Approach Width. d. Calculating Determination of saturation current. 3.2 Secondary Data Collection This secondary data is data obtained from related agencies, in the form of population data and traffic data on Jl.KH. Wahid Hasyim and Jl. Sewer Inspection Mataram, Dabag, Condongcatur, Sleman, DIY. Based on the results of research conducted at the empang intersection, Jl. KH. Wahid Hasyim and Jl. Mataram Sewer Inspection, Dabag, Condongcatur, Sleman, DIY. On Sunday 01/10/2023, Monday 02/10/2023, Tuesday 03/10/2023, Wednesday 04/10/2023, Thursday 05/10/2023, Friday 06/10/2023 and Saturday 07/10/2023 . It can be concluded that the busiest traffic activity occurred on Monday, 02/10/2023. With a total of 2539 vehicles or 1106.2 SMP/Hour. High traffic volume is a problem that must be addressed. Based on the analysis carried out at the intersection, the following conclusions can be drawn: 1. Vehicle volume based on the results of a 7 day traffic survey at the intersection of four KH roads. Wahid Hasyim and the Mataram Sewer Inspection Road obtained results of a heavy number of vehicles on Monday 02/10/2023 for the time period 06.00 – 07.00 and 16.30 – 17.30. namely 2539 Kend/Hour. 2. KH four-way intersection capacity. Wahid Hasyim and the Mataram Sewer Inspection road for the period Monday 02/10/2023 in the north direction 1315.811775 SMP/hour, south 1307.86199 SMP/hour, east 2325.226635 SMP/hour, west 2190.930622 SMP/hour. 3. Effective Approach Width on KH road. Wahid Hasyim and the Mataram Sewer Inspection road in the north direction 16.5m, south 13.3m, east 12m, west 10.5m. 4. Basic saturated current on KH road. Wahid Hasyim and the Mataram sewer inspection road in the north direction 9900 SMP/hour, south 7980 SMP/hour, east 7200 SMP/hour, west 6300 SMP/hour. 5. Adjusted saturation current J on road KH. Wahid Hasyim and the Mataram Sewer Inspection road in the north direction 9556.948685 SMP/hour, south 7847.171942 SMP/hour, east 6827.261184 SMP/hour, west 6170.376038 SMP/hour.

Traffic Performance Analysis – Emp And Saturation Degrees Using Pkji 2023

The intersection of KH Wahid Hasyim Road and Inspection Road which is located in the Selokan Mataram, Dabag, Condongcatur, Sleman, DIY area has a high traffic volume because it is a link between residential, educational and economic zones and shopping centers. The problem that often occurs at the intersection of Jalan KH Wahid Hasyim and Jalan Inspection Selokan Mataram, Dabag, Condongcatur, Sleman, DIY is high traffic flow, which often results in traffic jams. The regulation of traffic lights currently in operation cannot overcome the congestion that often occurs, especially during peak hours. The aim of this research is to analyze the performance of signalized intersections using the PKJI 2023 method. To provide appropriate solutions and alternative problem solving at these intersections. Which can improve the performance of the signalized intersection Jl. KH Wahid Hasyim and Jl. Mataram Selokam Inspection. Based on the results of research that has been carried out, it is as follows: a. The traffic flow at the intersection of four is marked KH. Wahid Hasyim and the Mataram Sewer Inspection Road based on the analysis results show that the traffic volume at signalized intersections for 7 days is 16,527 PCU/hour. b. The traffic volume at the intersection with the KH road signal. Wahid Hasyim and the Mataram Sewer Inspection road at peak hours on Monday 02/10/2023, namely 2539 or 1106.2 SMP/Hour. c. Annual average daily traffic at the intersection of four with the KH road signal. Wahid Hasyim and the Mataram Sewer Inspection road for 7 days were taken at peak hours 06.00 – 07.00 and 16.30 – 17.30. get results, namely 45.10 Kend/Hour. d. Calculation of traffic performance and EMP. Which was carried out for 7 days with a K value of 0.08. according to the road width of 6m, you get a result of 3.60 SMP/hour. e. Degree of Saturation at the intersection of four signalized roads KH. Wahid Hasyim in the peak volume period Monday 02/10/2023. Taken at each intersection, North 0.520 SMP/hour, South 0.641 SMP/hour, East 0.162 SMP/hour and West 0.291 SMP/hour. 1. Degree of saturation at the intersection of four KH roads. Wahid Hasyim and the Mataram Sewer Inspection road for the period Monday 10/02/2023 is North 0.520 SMP/Hour, South 0.641 SMP/Hour, East 0.162 SMP/Hour and West 0.291 SMP/Hour. then the service level is D with unstable flow conditions but the speed and movement of vehicles is very low. 2. Vehicle volume based on the results of a 7-day traffic survey shows the number of heavy vehicles on Monday 02/10/2023 for the time period 06.00 – 07.00 and 16.30 – 17.30. namely 2539 Kend/Hour. 3. The capacity value (C) obtained is 2688 SMP/Hour. 4. The value of traffic flow and EMP passing through the four signalized intersections on Jl. KH. Wahid Hasyim and Jl. Sewer Inspection with a K value of 0.08 gets a result of 3.60 SMP/Hour.

ANALYSIS OF DENSITY IN SIGNIFICANT junctions (CASE STUDY: junction of JL. MARGOREJO AND JL. FRONTAGE AHMAD YANI

In this modern era, the increase in science and technology has led to an increase in human activities followed by an increase in vehicle capacity and a decrease in pedestrians. So the need for transportation facilities cannot be avoided. In the city of Surabaya, the need for transportation has become a primary need for the urban community and the situation is at the intersection of Jalan Ahmad Yani, Jalan Frontage Ahmad Yani and Jalan Margerejo, City of Surabaya with the 333 intersection type and 3 signal phases, which means that if one arm of the intersection is in phase green, the other three phases are in the red phase. The method used in this research is the 1997 Indonesian Highway Capacity Manual (MKJI 1997). Researchers conducted a traffic survey on the number of vehicles that passed for 3 days, namely Tuesday, Wednesday and Thursday, to calculate the amount of traffic volume, the capacity of the intersection, and the degree of saturation. From the results of the study, the highest traffic volume was found at the intersection of Jalan Ahmad Yani, Jalan Frontage Ahmad Yani and Jalan Margerejo, City of Surabaya, occurring on Wednesdays at 16.00-17.00 WIB. Jalan Ahmad Yani was 4125 pcu/hour, Jalan Ahmad Yani (South) was 710 pcu/hour, Jalan Frontage Ahmad Yani is 2700 pcu/hour, Jalan Margerejo is 1295 pcu/hour. The results of the existing performance at the intersection of Jalan Ahmad Yani, Jalan Frontage Ahmad Yani and Jalan Margerejo, City of Surabaya with the 333 intersection type occurring on Wednesday at 16.00-17.00 WIB, have an average degree of saturation of 0.97.

Urban planning role in environmental development, transportation potentials: Al-Baha region

This paper analyzes the potential for energy generation using the transport system in Al-Baha city by investigating its road hierarchy and evaluate traffic in selected location across the city. Urban systems to manage the transport hierarchy are important, and exploiting them to minimize CO2 emissions rates is critical. The used approach is to investigate the urban planning of Al-Baha city by referring to its approved master plan detailing the road hierarchy, and second, conducting a traffic survey at selected points across the city. The data collection process, involved accessing the master plan for Al-Baha city held by the ministry of the municipality for the Al-Baha region. Additional data related to traffic congestion and demand was gathered physically at chosen sites. The output of the study illustrates the potential for energy generation exploiting traffic mobility at six different sites across Al-Baha city. Furthermore, attractive features that effect the transport system in Al-Baha city were highlighted and the potential for energy saving employing energy generation using the transport system discussed. The research contributes on highlighting the potential for renewable energy, minimizes the need to burn fossil fuels, and can be replicated in other cities characterized by high demand transport systems.

A Study on the Analysis of Road Traffic Survey Data Characteristics and Missing Correction Method

A Study on the Analysis of Road Traffic Survey Data Characteristics and Missing Correction Method

A Case Investigation into Causes of Premature Rutting Failures in Rehabilitated Asphalt Pavements in Tanzania

Abstract Tanzania has faced high incidences of premature rutting failures on their asphalt pavements. Some pavements experienced failures within one to two years after construction/rehabilitation. The objective of this investigation was to identify the factors that contributed to the observed failures on five rehabilitated road sections on a national highway in Tanzania. Pavement temperature data collection, traffic surveys, visual inspection, rut depth measurements, and falling weight deflectometer tests constituted the main activities of the field investigation reported in this paper. The laboratory study included a visual assessment of cores extracted from the studied road sections to determine both physical and engineering properties, including density, stiffness, strength, aggregate shape properties, grading, and physiochemical tests on the recovered binders. The results of the study indicated that the degree and extent of rutting on the investigated road sections was rated as severe., i.e., rutting ranged from 38–138 mm on the five sections when compared to the acceptable threshold value of 15 mm for high volume roads in Tanzania. The elastic deflection results indicated that the underlying layers of the pavement system were generally in a sound condition, which validated the suggestion that the rutting observed was mostly confined to the asphalt concrete layers. Factors such as relatively high axle loads, poor asphalt mixes, and possibly inadequate quality control during construction and rehabilitation were suspected to contribute to the rutting on the sections. Practical measures recommended to the roads agency to avert future occurrences are provided in this paper.

Real-Time Vehicle Identification for Improving the Traffic Management system-A Review

Due to the increasing number of cars on the road and the exponential growth of traffic throughout the globe, regulating traffic has become crucial in the most industrialized countries. The development of technology has led to the current state of traffic management systems that comes with the ability to count, monitor, and predict the speed of vehicles in order to improve the transportation planning. This has also reduced the number of accidents that occur due to worsen traffic conditions. Road traffic surveys have been carried out manually for a long time since automated measures were not often employed due to the difficulty of installation. Machine learning in image processing is widely recognized as a significant approach for real-world applications such as traffic monitoring. The primary benefit of automated vehicle counting is that it allows for the management and evaluation of traffic in the urban transportation system. There are many methods employing distributed acoustic systems on intelligent transportation systems, including YOLO v4 and the Normalized Cross-correlation algorithm, which uses ultrasonic sensors and the algorithms ALPR, YOLO, GDPR, and CNN. The simplest method for identifying a vehicle is to gather information from sensors such as cameras, vibration detectors, ultrasound detectors, or acoustic detectors. These sensors are combined with the proper microcontrollers to determine the amount of traffic using the most recent data and theory. This review article is a quick reference for researchers working on safety-related traffic management systems.

Incorporating Traffic Models into Seismic Damage Analysis of Bridge Road Networks: A Case Study in Central Italy

Transportation networks are one of the most vulnerable civil infrastructures during an earthquake and an estimation of traffic impacts in the post-earthquake scenario is a crucial aspect in the context of risk assessment and evaluation of remedial measures. In this paper, a methodology is presented, combining GIS tools, probabilistic seismic risk analysis and traffic simulation models, which is able to assess the direct and indirect (social) costs: bridge repairs, increase in travel time and a lack of accessibility. Operating issues related to the development and calibration of traffic models applicable to a damaged road network are carefully analysed and reviewed and an innovative approach to evaluate the social cost due to the lack of accessibility is also proposed. The developed modelling framework has been applied on a realistic bridge stock within a road transportation network in central Italy where local land-use data have been collected, extensive traffic surveys have been performed and a traffic model has been calibrated. A probabilistic risk analysis employing a ShakeMap derived from a historical real seismic event has been carried out.