High Traffic Flow Research Articles

Advancements in autonomous detection of high noise emitters in road traffic

Noise pollution is an increasing problem in densely populated areas with high traffic flow. The NEMO project (Noise and Emissions Monitoring https://nemo-cities.eu/) is funded by the EU to develop a system that is capable of detecting high emitters in terms of noise and air pollutants to prosecute vehicle owners. To this end, a fully autonomous noise measurement system was developed and tested on several test locations, both unsupervised and supervised. This paper describes the advancements in autonomous measuring of traffic noise and specifically addresses the problem of reliable noise source detection in dense traffic streams. While the correct localization of the source is of great importance, it is not yet enough to measure the correct sound pressure level. We therefore propose a method to estimate the influence of nearby noise sources, i.e. closely driving additional vehicles, that disturb the sound signal of the vehicle of interest and correct for it. This algorithm has been applied on several test locations. Using these insights, we will discuss the benefits and possibility of the integration of such a system in the near future.

Dynamic emission characteristics and control strategies of air pollutants from motor vehicles in downtown Beijing, China

This study combined the real-time monitoring and investigation of traffic flows to comprehensively analyze the road traffic flow and vehicle structure in downtown Beijing. A dynamic emission inventory of motor vehicle air pollutants in downtown Beijing in 2021 was established, and the impact of these emissions on air quality was simulated and quantified, and different emission reduction control scenarios were proposed to evaluate their environmental improvement effects and explore measures to mitigate the impact of pollution emissions. The results show that the high traffic flow and the structure of the motor vehicle emissions in downtown Beijing are the main causes of severe motor vehicle pollution. Monitoring data shows that traffic flow in central Beijing is dominated by small passenger vehicles, while the vehicle mix is better than in other regions, with 72.0% of vehicles meeting "National V" or higher emission standards. However, to achieve higher air quality goals, further reducing vehicle emissions is necessary. Based on dynamic traffic flow, the average daily emissions of nitrogen oxides (NOX), particulate matters(PM2.5) and volatile organic compounds(VOC) from motor vehicles in central Beijing are 17.7 tons, 0.6 tons and 14.0 tons, respectively, accounting for 23.0% of the city's average daily motor vehicle emissions. If a zero-emission zone for motor vehicles were implemented in central Beijing, the annual average emission level of pollutants will be reduced by 10.4% to 21.0%. The designation of ultra-low emission zones for motor vehicles could be effective in improving the air quality in the center of Beijing.

Digital twins and 3D information modeling in a smart city for traffic controlling: A review

The idea of a smart city has evolved in recent years from limiting the city’s physical growth to a comprehensive idea that includes physical, social, information, and knowledge infrastructure. As of right now, many studies indicate the potential advantages of smart cities in the fields of education, transportation, and entertainment to achieve more sustainability, efficiency, optimization, collaboration, and creativity. So, it is necessary to survey some technical knowledge and technology to establish the smart city and digitize its services. Traffic and transportation management, together with other subsystems, is one of the key components of creating a smart city. We specify this research by exploring digital twin (DT) technologies and 3D model information in the context of traffic management as well as the need to acquire them in the modern world. Despite the abundance of research in this field, the majority of them concentrate on the technical aspects of its design in diverse sectors. More details are required on the application of DTs in the creation of intelligent transportation systems. Results from the literature indicate that implementing the Internet of Things (IoT) to the scope of traffic addresses the traffic management issues in densely populated cities and somewhat affects the air pollution reduction caused by transportation systems. Leading countries are moving towards integrated systems and platforms using Building Information Modelling (BIM), IoT, and Spatial Data Infrastructure (SDI) to make cities smarter. There has been limited research on the application of digital twin technology in traffic control. One reason for this could be the complexity of the traffic system, which involves multiple variables and interactions between different components. Developing an accurate digital twin model for traffic control would require a significant amount of data collection and analysis, as well as advanced modeling techniques to account for the dynamic nature of traffic flow. We explore the requirements for the implementation of the digital twin in the traffic control industry and a proper architecture based on 6 main layers is investigated for the deployment of this system. In addition, an emphasis on the particular function of DT in simulating high traffic flow, keeping track of accidents, and choosing the optimal path for vehicles has been reviewed. Furthermore, incorporating user-generated content and volunteered geographic information (VGI), considering the idea of the human as a sensor, together with IoT can be a future direction to provide a more accurate and up-to-date representation of the physical environment, especially for traffic control, according to the literature review. The results show there are some limitations in digital twins for traffic control. The current digital twins are only a 3D representation of the real world. The difficulty of synchronizing real and virtual world information is another challenge. Eventually, in order to employ this technology as effectively as feasible in urban management, the researchers must address these drawbacks.

Traffic flow impacts on the environment along urban streets under mixed traffic conditions in Al-Najaf city

With the increase in population and urban mobilization worldwide, the rapid urbanization of Najaf has led to a massive increase in road traffic. Automobile traffic is now regarded as one of the most significant sources of air pollution in Iraq, with a considerable impact on air quality. This study conducted measurements in a selected urban-road network in Al-Najaf city in Iraq that witnessed a high traffic flow index to measure vehicle emissions and study the correlation between the traffic flow and emissions in this network during peak hours. Priority parameters were measured such as: “Carbon dioxide,” “Carbon monoxide,” “Nitrogen dioxide,” “Nitrogen monoxide,” “Sulfur dioxide,” and other parameters also monitored, including temperature, the direction of the wind, the velocity of wind, and the traffic parameters. It shows that the high heterogeneous traffic flow increases pollutants produced by vehicles. At the same time, it decreases substantially with the decrease in flow and speed. The highest level of Carbon dioxide was: 486ppm, 466ppm, and 447 ppm at peak hours when high traffic density. Also, the highest concentration of Co was 8.22, 4.52, and 3.98 ppm in all locations indexed in the moderate zone, No2 and SoD exceeding EPA levels marking the index in the (very unhealthy) zone. The correlation analysis showed a good and very good linear regression model between CO, CO2, and volume with average vehicle speed. According to these results, the pollution in Najaf due to transportation is significant, with potentially serious health repercussions.

Vehicles lateral acceleration and speed profiles investigation at the entry area of interchange ramps as a criterion of geometric road design

The subject of road safety is the main subject of many research programs regarding the road network infrastructure. In the present study, lateral acceleration is recorded through modern instruments, depending on passing speed for each participant driver, for four (4) interchanges and six (6) horizontal curves in total. Essentially, this study emphasizes on how the geometric roads design affects driving behavior. The main purpose is to determine the effect of on-ramp applied speed and curve geometry on lateral acceleration and to create a clear speed profile of drivers during their passage from an interchange ramp. The data collection took place in morning weekend hours, in order to avoid high traffic flows and record the vehicles motions in free flow conditions. As a result, the analysis can examine the main human factors, which affect the driving behavior, too. The selected interchange ramps are mainly trumpets, but also clover and diamond sections and the under-investigation curve radii varies between 28 and 175 meters.For each curve, the presented figures correlate the speed within the curve and the lateral acceleration, while comparisons are made between the lateral acceleration recorded in this research and the literature and guidelines limits. Additionally, V85, V50 and V15 are calculated from the total measurements, taking also into account the data from three additional horizontal curves of Schistos-Skaramagas interchange investigated one year earlier. Therefore, aggregate speed profiles are created and presented.In conclusion, the results show that an increase in the speed leads to an increase in the lateral acceleration as well. Also the limit values of lateral acceleration received by drivers into smaller-radii curves, significantly exceed the maximum driver comfort limit and the maximum driver safety limit, as well as the provided -by design guidelines- values, in contrast to larger-radii curves. Regarding the speed within the curve in respect to the horizontal radius, it was found that as the radius of the curve increases the applied speed also increases. However, this increase is more abrupt for the smaller radius curves compared to the larger ones. Moreover, de Jong's models include higher values than the measurements made in the present study and much more than those presented by Jafarov's and Zaluga's model (2020), especially in cases of large horizontal radii.

АЛГОРИТМ ОРГАНИЗАЦИИ ПЕРЕВОЗОК НА ОСНОВЕ КРИТИЧЕСКОГО ЭЛЕМЕНТА МАТРИЦЫ КОРРЕСПОНДЕНЦИЙ

The passenger urban transport system based on unmanned automatic transport of small capacity, which is closed, i. e. functioning independently - without human participation, is considered. Data collection, analysis and organization of transportation in such system are carried out using information technologies and intelligent algorithms. The correspondence matrix serves as an information basis for drafting a transportation plan. An algorithm for drawing up a transportation plan based on the correspondence matrix is proposed, in which the critical element correlates with the condition of sufficient accumulation of requests for transportation. In addition, the algorithm provides the possibility of in-passing transportation of passengers. It is demonstrated that the proposed algorithm makes it possible to achieve a level of comfort comparable to the comfort of a taxi ride, but at the same time, the economic effect of transportation is higher than that of a taxi, due to a larger number of passengers traveling together. The considered model is aimed at increasing the mobility and flexibility of passenger transportation in conditions of high traffic flows and is distinguished by economic and environmental benefits, since the method of passenger transportation by unmanned vehicles provides high carrying capacity of urban transport systems with a high level of passenger comfort on the route.

Design Factors and Criteria for Building a Non-Level Pedestrian Crossing at an Urban Campus

Bandung Islamic University (UNISBA) is in a densely populated urban area of Bandung. UNISBA lecture and administrative buildings are scattered in several locations. In architecture typo-morphology terms, a campus building with this environmental setting is often referred to as an urban campus. The high traffic flow on these roads, together with the intense conflict between road crossers, often results in congestion due to vehicle deceleration needed to allow pedestrian crossing. To facilitate the need for the movement for the users of the UNISBA campus buildings and minimize conflicts with road users, infrastructure that connects the UNISBA campus buildings is needed to facilitate pedestrian crossing. The pedestrian crossing could be in the form of a level crossing in the same elevation as the road or a non-level crossing situated above or under the road. The type of pedestrian crossing studied in this paper is a non-level pedestrian crossing in the form of a pedestrian bridge. In designing the infrastructure for non-level crossings, it is necessary to pay attention to the movement patterns that occur and the factors that influence willingness to use. This study aims to determine the movement pattern of UNISBA campus facility users consisting of students, lecturers, educational staff, and visitors by using quantitative origin-destination spatial analysis. Descriptive exploratory factor analysis was also used to determine the preferences of the users of the UNISBA campus buildings to use non-level crossings. The results of this analysis will be the basis for designing non-level accessibility between UNISBA campus buildings.
 Keywords: pedestrian crossing, pedestrian bridge, urban campus, urban design, urban mobiity

Pre-trip reservation enabled route guidance and signal control cooperative method for improving network throughput

With the ever-increasing traffic demand, efficient urban traffic operation is facing more and more pressure and challenges. Route guidance and signal control are effective methods to enhance the existing urban traffic capacity and realize the sustainable development of traffic systems. In this paper, a collaborative optimization method of route guidance and intersection signal controlling is proposed under the background of a pre-trip reservation. Vehicles were divided into reserved and non-reserved vehicles, which corresponds to pre-trip reservation and non-reserved travel, respectively. Firstly, route guidance models considering both road network efficiency and vehicle travel time are proposed for different types of vehicles. Then, based on the impact of different travel modes on traffic flow distribution, a collaborative optimization for route guidance and intersection signal control was realized through the proposed dynamic signal optimization method. The experimental results showed that road network capacity was improved by 16% under the condition of high traffic flow by using the proposed optimization method. The proposed method can also alleviate the congestion of some sections without causing the transfer of congestion. The effectiveness of the proposed method was verified by simulation experiments, which can provide a theoretical reference for traffic control and management in the context of pre-trip reservation.

Advantage Actor-Critic for Autonomous Intersection Management

With increasing urban population, there are more and more vehicles, causing traffic congestion. In order to solve this problem, the development of an efficient and fair intersection management system is an important issue. With the development of intelligent transportation systems, the computing efficiency of vehicles and vehicle-to-vehicle communications are becoming more advanced, which can be used to good advantage in developing smarter systems. As such, Autonomous Intersection Management (AIM) proposals have been widely discussed. This research proposes an intersection management system based on Advantage Actor-Critic (A2C) which is a type of reinforcement learning. This method can lead to a fair and efficient intersection resource allocation strategy being learned. In our proposed approach, we design a reward function and then use this reward function to encourage a fair allocation of intersection resources. The proposed approach uses a brake-safe control to ensure that autonomous moving vehicles travel safely. An experiment is performed using the SUMO simulator to simulate traffic at an isolated intersection, and the experimental performance is compared with Fast First Service (FFS) and GAMEOPT in terms of throughput, fairness, and maximum waiting time. The proposed approach increases fairness by 20% to 40%, and the maximum waiting time is reduced by 20% to 36% in high traffic flow. The inflow rates are increased, average waiting time is reduced, and throughput is increased.

Pedestrian level of service simulating and redesigning sidewalk in crowded urban areas

The design of sidewalks in crowded areas is of great importance in cities. These spaces are sensitive if they happen to be in a central business district (CBD). In this research study, the main objective is to analyse and design the sidewalk adjacent to the bazaar in Semnan, Iran, in a CBD, positioned in a historical location of the city. After surveying number of pedestrian sidewalks during peak hours in the morning and evening, the above-mentioned street was divided into eight parts, and the highest traffic flow was considered as a criterion for the design. Then, based on HCM2016, the density and the level of service (LOS) of each part were obtained. The findings indicated that part 4 had LOS E and density 11 < 11, 52 < 18, part 6 had LOS E and density 11 < 12, 06 < 18 and part 7 with the highest traffic volume of about 2500 people and LOS E was prioritised to increase LOS. The data obtained for each part were studied by PathFinder software and compared with the obtained manual information. Therefore, the road-diet theory was implemented. By increasing the width of the sidewalk by about 3–5 ft/section, there was a resulting improvement in LOS.

An improved risk estimation model of lane change using naturalistic vehicle trajectories

Lane change (LC) behavior has critical effects on traffic flows and safety due to its complex interactions with surrounding vehicles. To ensure safe lane changes and prevent potential crashes, it is important to recognize the potential crash risk of lane change in real time. This study proposes an improved risk estimation (IRE) model to evaluate the potential collision risk of lane change (LCR) vehicle groups. The safety margin is introduced to consider the deceleration capability of vehicles to measure the reaction time of drivers during the LC. Then the IRE model is established, incorporating the collision probability and collision severity measured based on the safety margin. The trajectory data, extracted from the highD dataset, are used and 1536 LC samples are investigated. We compare the LCR under different contextual factors, including vehicle types (cars and trucks), two lane change directions (left and right lane change, LLC and RLC), and traffic flows (low and high traffic). It was found that truck drivers keep higher LCR compared with car drivers due to limited brake capacity, and the left lane change results in higher LCR compared with the right lane change. Additionally, lane change is associated with higher crash risk in high traffic flow, as compared to low traffic flow. The understanding of the crash risk of lane change behavior under different contextual factors, can be useful for real-time crash prediction and devising traffic management strategies.

Identification and treatment of black spots in the road network around Universitas Tadulako

Safety is an essential thing that must be met in the implementation of traffic activities on the highway. Every effort is made to increase traffic safety. The road network around Universitas Tadulako has a high traffic flow so that the number of accidents increases. The accidents are indicated by several black spot locations. This condition requires research that can identify and find the proper black spot treatment. Therefore, the objectives of this research are to identify and discover the proper black spot treatment on the road network around campus. The method used in this research is an interview of road network users around the campus (students, community members, and the authorities) and inspections of locations that can become black spots. Three hundred forty-six respondents were collected and analyzed. The results show that the location of the black spot around the Universitas Tadulako is in front of the gate of the Universitas Tadulako lecturer housing. The proposed treatments at the black spot location are controlling street vendors’ spots, optimizing traffic lights, setting U-turns, cutting several trees, and repairing road pavements.

A stochastic model for stop-and-go phenomenon in traffic oscillation: On the prospective of macro and micro traffic flow

To investigate the stop-and-go phenomenon triggered by car-following, a hybrid model of micro and macro is proposed. Firstly, with the stochastic nature of driving behavior, a Brownian noise is added into the velocity difference to give a modification to the car-following model. Then, to combine the macroscopic traffic flow characteristics, the traffic stream model is introduced, and the two models are fused in the context of high traffic flow. Next, the theoretical validity of the fusion model is verified by the existence and uniqueness of the solution. The coefficients of the hybrid model are extracted as the stop coefficient and go coefficient which reflect the micro driving behavior. The Maximum Likelihood Estimations of the two coefficients are also given, as well as the boundedness of traffic oscillation in stop-and-go. Finally, numerical simulations show that the model has good fitting and prediction ability for traffic flow in high flow period. Moreover, the greater the stop coefficient, the stronger the traffic flow oscillation intensity, the larger the upper boundedness of the oscillation, the more severe the stop-and-go.

PERFORMANCE OF THE THREE-ARMED UNSIGNALIZED INTERCHANGE ON JALAN TIPAR CAKUNG, EAST JAKARTA

The growth of the population density greatly affects the level of transportation needs in the city of Jakarta. The increase in the number of vehicles that are lack of balanced with the development of infrastructure It will cause conflicts on the road, especially intersections. Therefore, it is necessary to conduct research on interchange to know the problems that occur. This research was conducted at the Tipar Cakung – Agung Sedayu interchange in East Jakarta with an observation time of 3 days. The method that used in this study is a field survey method, namely by collecting data on traffic. It carried out by recording the number of vehicles that pass through the intersection every 15 minutes. Then from the results of the survey and calculation with the analysis guided by Indonesian Road Capacity Manual (MKJI, 1997). Based on the results of research for interchange performance in existing conditions, the highest traffic flow was obtained at 2831.7 pcu / hour, Degree of Saturation (DS) 1.05, delay on intersection (D) of 22.058 seconds/pcu and queue odds (QP%) in the range of values 44.93%-90.27%.

A New Perspective on Traffic Flow Prediction: A Graph Spatial-Temporal Network with Complex Network Information

Traffic flow prediction provides support for travel management, vehicle scheduling, and intelligent transportation system construction. In this work, a graph space–time network (GSTNCNI), incorporating complex network feature information, is proposed to predict future highway traffic flow time series. Firstly, a traffic complex network model using traffic big data is established, the topological features of traffic road networks are then analyzed using complex network theory, and finally, the topological features are combined with graph neural networks to explore the roles played by the topological features of 97 traffic network nodes. Consequently, six complex network properties are discussed, namely, degree centrality, clustering coefficient, closeness centrality, betweenness centrality, point intensity, and shortest average path length. This study improves the graph convolutional neural network based on the above six complex network properties and proposes a graph spatial–temporal network consisting of a combination of several complex network properties. By comparison with existing baselines containing graph convolutional neural networks, it is verified that GSTNCNI possesses high traffic flow prediction accuracy and robustness. In addition, ablation experiments are conducted for six different complex network features to verify the effect of different complex network features on the model’s prediction accuracy. Experimental analysis indicates that the model with combined multiple complex network features has a higher prediction accuracy, and its performance is improved by 31.46% on average, compared with the model containing only one complex network feature.

Spatial distribution of health-risky road traffic noise pollution in Dessie City, North East Ethiopia.

Dessie is the trade center for northeast Ethiopia. High traffic flow plus overacting of promotion made the city noisy. There is a shortage of relevant evidence that enforces policy makers to design intervention plans. Therefore, this study aimed to explore the health-risky road traffic noise pollution in Dessie City, Ethiopia. The study was conducted by purposive selection of the study area and sampling sites of the city from May 31, 2021 -June 6, 2021. Noise level recordings were taken by a digital Sound Meter and location data was collected by Global Positioning System. Residential, health facility, commercial, and mixed sites were identified by field observation. A total of 20 noise sampling points were included. The sampling points were selected by considering World Health Organization guideline. The measurements were taken twice a day at peak hours, between 8:00-11:00am and 4:00-7:00pm on all days of the week. The sound level meter was placed at a height of 1.5m and 2m from the curb. A total of 280 sound level records were conducted over one week. Among twenty noise recording sites, more than 50% of them registered as excessive noisy sites for all types of site categories (health facility, residential, commercial, and mixed areas). For the seven days, average noise recordings were in the range of 66-72 dB at 83% of mixed areas; 33% of health facilities; 25% of residential areas, and 86% of commercial areas. The highest levels of noise pollution were seen at the Bus-station, Buanbuawuha Square, Tekuam, Arada, Ethio General Hospital, Ersha-seble, and Menafesha areas. This study shows that the average noise level measurement within a week exceeded the permissible limits set by Ethiopia and the World Health Organization. It helps for policy development and timely actions against noise pollution and as baseline information for further investigation.

Visual Accessibility and Inclusive Wayfinding Design in Hospital Environment in Nigeria

Visual accessibility refers to the legibility and intelligibility of space cues that most contribute to the searching and use of information from the environment for wayfinding in hospitals. Because of building complexity and expansions over time, there is a lack of visual clarity to navigate and access the most desired destinations in the hospital. However, the inaccessibility of space by many unfamiliar users of any age, gender, or disability resulted in disorientation, uncertainty, stress, frustration, getting lost, and missed medical appointments. The purpose of this study is to investigate the impact and barriers of visual accessibility on wayfinding in hospital buildings. Mixed-method approach combined quantitative and qualitative measures for the study area with focus on General Outpatients Departments (GOPD). A simple random sampling technique was used to select 98 participants. 24 respondents were selected for interview, while GOPD hospital buildings were observed for data elicitation. The main findings show that some of the circulation spaces were crowded with patients, and that most destinations within the GOPD were not visible from the main entrance. In addition, indistinctive nodes act as barriers, rendering some buildings inaccessible during navigation. It also revealed that signage, unit building entrances, and lighting were legible and properly positioned, enhancing space accessibility during wayfinding. The main limitations of this study are the absence of physically challenged people and the elderly in the research process, as well as cultural and linguistic differences. The implications are that designers should make simplified building layout more legible to the wide group of users such that core sections are visible and interlinked with high traffic flow pathways in the hospital for inclusive wayfinding. This study suggested solutions to the problems of visual accessibility in the hospital could improve all users' inclusive wayfinding, increase satisfaction, confidence, reduce confusion during direction-finding in the hospital.

Coupling Virtual Reality Simulator with Instantaneous Emission Model: A New Method for Estimating Road Traffic Emissions

The article presents a new methodology for traffic emissions modeling by coupled the use of dynamic emissions models with a virtual reality driving simulator. The former allows the drivers’ behavior to be studied through a virtual reality driving test, focusing the attention on how traffic flow conditions combined with road geometrical characteristics influence the driving behavior. The latter is used to model the instantaneous vehicle emissions, starting from the driving data provided by the driving simulator. The article analyzes the relationship among three factors: the driving behavior, the pollutant emissions, and the traffic flow condition. The results highlight the influence of the drivers’ behavior on fuel consumption and emissions factors. Under high traffic flow, despite the reduction of the average vehicle speed, the average emissions level increases due to the increased vehicle accelerations and decelerations, which influence the behavior of the engine and the aftertreatment system. The proposed approach points out the relationship between vehicle emissions and drivers’ behavior. Since the coupling among instantaneous emissions modeling and geometry-functionality conditions of the road reveals important elements that traditional approaches miss, the proposed method provides a new way to increase the efficiency of road design and management, from the environmental point of view.

A Class-based Adaptive QoS Control Scheme Adopting Optimization Technique over WLAN SDN Architecture

Recently, Software-Defined Networking (SDN), a network architecture approach that enables the network to be intelligently and centrally controlled by using software applications, has been introduced. Another important issue in the network management context is Quality of Service (QoS). This work investigates the QoS provisioning of various traffic classes on an SDN-enabled network. We propose and implement the class-based adaptive QoS control scheme on SDN-enabled network for various traffic classes, namely VoIP, Video Streaming and File Transfer. The effectiveness of our proposed scheme is validated by simulation using Mininet and Ryu controller. The procedure to create the simulation platform and all details relevant to all software used are described step-by-step in detail. The main performance evaluation metric is the Maximum Number of Traffic Flows admittable with QoS while Average Throughput, Latency, Jitter, and Packet Loss Rate are maintained at the comparable level of the existing work in the literature called JMABC [11]. Our simulation results are illustrated with 95% confidence interval. According to the simulation results, it is obvious that our proposed class-based adaptive QoS control scheme adopting the optimization technique significantly outperforms the existing similar QoS provision scheme in terms of the maximum number of the high priority traffic flows (VoIP) admittable with QoS while the other evaluation metrics are maintained at the same level.

The Influence of Built Environment Factors on Elderly Pedestrian Road Safety in Cities: The Experience of Madrid.

With the progressive ageing of the population, the study of the relations between road safety and elderly users is becoming increasingly relevant. Although the decline of pedestrian skills in the elderly has been widely studied in the literature, few studies have been devoted to the contributing built environmental factors of the elderly pedestrian collisions, such as the sidewalk density, the presence of traffic lights, or even some indicator related to land use or the socioeconomic features of the urban fabric. This paper contributes to the limited literature on elderly pedestrian safety by applying a negative binomial regression to a set of built environmental variables to study the occurrence of accidents involving elderly and younger (non-elderly) pedestrians in Madrid (Spain) between 2006 and 2018. The model considers a selection of built environmental factors per city district, linked to land use, infrastructure, and socioeconomic indicators. Results have highlighted that the elderly pedestrian collisions could be avoided with the existence of a wider sidewalk in the district and a greater traffic lights density. Unlike younger pedestrian accidents, these accidents are much more favored in ageing districts with higher traffic flows.