Road Traffic System Research Articles

IoT based Dynamic Road Traffic Management System

Traffic due to automobiles is a major problem in many urban places in India as well as in other countries. Malfunctioning of the traffic lights and various other dysfunctionalities has led to traffic congestion which hurts the economy, environment, and overall quality of life. Hence it is very important to manage the traffic congestion problem effectively. In this paper, a prototype is proposed for a traffic management system using IR sensors, Arduino, serial to the parallel shift register, and LED displays. The density of the traffic is measured by placing the IR sensors at the 4 lane junction after a certain distance. The data collected from sensors is used to dynamically change the sequence of green lights as well as to dynamically change the green light delays. The proposed road traffic management system is implemented in the proteus software. For high traffic zone, a higher green light delay is given whereas for low density zone, the duration of the green light delay is reduced. The system is also designed in such a way as to give preference to the lanes which have no vehicles/very few vehicles by providing the least green light delays.

Quality of Automatic Traffic Volume Counting by Cameras and Impact on the Qualitative Indicators of Traffic

This paper presents research on the collection, analysis, and evaluation of the fundamental data needed for road traffic systems. The basis for the research, analysis, planning and projections for traffic systems are traffic counts and data collection related to traffic volume and type. The quality and accuracy of this data are very important for traffic planning or optimization. Therefore, the purpose of this research is to apply advanced methods of automatic counting of motorized traffic and to evaluate the impact of this data on the measurement of important traffic indicators. The accuracy of measurements arising from the traditional method of data collection through manual counting will be compared with the most advanced methods of automatic counting through cameras. For this purpose, an analytical algorithm for the recognition and processing of data related to road users as a function of the time of day was applied. The program was written in the programming language Python, and the accuracy of the data and its effect on the results of qualitative traffic indicators were analyzed using the Synchro software model. The developed program is capable of recognizing and classifying different types of vehicles in traffic, such as motorbikes, motorcycles, cars, pick-ups, trucks, vans and buses, as well as counting the traffic volume over time. The results obtained from these two models show the advantages of applying advanced methods of data collection and processing related to dynamic traffic processes, as well as the quality in terms of the impact on the measurement of qualitative traffic indicators. A comparison of the quality of results for the different time intervals and varying levels of visibility in traffic is presented using tables and graphs. At nighttime, when visibility was poor, the discrepancy between the manual and automatic counting methods was around 9.5%. However, when visibility was good, the difference between manual counting and the automated program was 4.87% for the period 19:00–19:15 and 3.64% for the period 05:00–05:15. This discrepancy was especially noticeable when distinguishing between vehicle categories, due to the limitations in the accuracy in recognizing and measuring the dimensions of these vehicles. The difference between the two calculation models has a minor effect on qualitative traffic indicators such as: approach LOS, progression factor, v/s, v/c, clearance time, lane group flow, adj. flow, satd, and flow approach delay.

Piloting a hospital-based road traffic injury surveillance system in Nairobi County, Kenya, 2018–2019

BackgroundKenya's estimated road traffic injury (RTI) death rate is 27.8/100,000 population, which is 1.5 times the global rate. Some RTI data are collected in Kenya; however, a systematic and integrated surveillance system does not exist. Therefore, we adopted and modified the World Health Organization's injury surveillance guidelines to pilot a hospital-based RTI surveillance system in Nairobi County, Kenya. MethodsWe prospectively documented all RTI cases presenting at two public trauma hospitals in Nairobi County from October 2018–April 2019. RTI cases were defined as injuries involving ≥1 moving vehicles on public roads. Demographics, injury circumstances, and outcome information were collected using standardized case report forms. The Kampala Trauma Score (KTS) was used to assess injury severity. RTI cases were characterized with descriptive statistics. ResultsOf the 1,840 RTI cases reported during the seven-month period, 73.2% were male. The median age was 29.8 years (range 1–89 years). Forty percent (n = 740) were taken to the hospital by bystanders. Median time for hospital arrival was 77 min. Pedestrians constituted 54.1% (n = 995) of cases. Of 400 motorcyclists, 48.0% lacked helmets. Similarly, 65.7% of bicyclists (23/35) lacked helmets. Among 386 motor vehicle occupants, 59.6% were not using seat belts (19.9% unknown). Seven percent of cases (n = 129) reported alcohol use (49.0% unknown), and 8.8% (n = 161) reported mobile phone use (59.7% unknown). Eleven percent of cases (n = 199) were severely injured (KTS <11), and 220 died. ConclusionWe demonstrated feasibility of a hospital-based RTI surveillance system in Nairobi County. Integrating information from crash scenes and hospitals can guide prevention.

On the scheduling of lifecycle network-level pavement maintenance: modelling and applications

ABSTRACT Pavement maintenance is a prominent issue in road traffic systems and plays a fundamental role in ensuring the safety, mobility and comfort of road networks worldwide. This paper introduces an innovative approach for scheduling network-level pavement maintenance based on mathematical planning, guided by the principle of lifecycle cost analysis (LCCA). The primary objective is to optimise pavement performance while minimising maintenance costs, ultimately achieving cost-effectiveness. In particular, the method aims to solve the ‘2W1H’ problem (i.e. ‘Which’, ‘When’, and ‘How’), which implies identifying the specific road sections, determining an appropriate maintenance timeline, and selecting the most effective maintenance treatment for long-term pavement maintenance planning. The proposed method comprises a bi-level optimisation model. The upper layer is a multi-objective optimisation model which concurrently maximising the lifecycle pavement performance while minimising the lifecycle costs; the lower layer evaluates the impact of pavement maintenance operations on travellers' route choice behaviour by employing the user equilibrium problem to determine the change in user cost attributable to a specific maintenance scheduling scheme. A meta-heuristic algorithm is utilised to solve the model and acquire a Pareto front for multi-objective optimisation. Furthermore, we discuss the practical engineering applications under budgetary constraints and pavement performance requirements, followed by the consideration of parameter uncertainties in pavement performance prediction models. The numerical experiments demonstrate that our approach can deliver pavement maintenance scheduling outcomes across various scales of road networks, and highlight the promising potential of our approach for future pavement management endeavours.

Assessing the design of road traffic death information systems in Iran: A participatory systems approach

AimTo describe and analyze the information architecture and information pathways of the road traffic death recording, registration and reporting system in Guilan Province, northernIran. MethodsWe used Business Process Mapping, a qualitative approach. This participatory and iterative approach consists of a document review, key informant interviews, development of a process map and a participatory workshop with key stakeholders to illuminate and validate the findings. We classified the tasks performed in the system into three phases: (1) Identification and recording; (2) Notification and registration, and (3) Production of statistics. ResultsWe identified 13 stakeholders, with operating and influencing roles in the process of identification, registration and production of statistics about road traffic deaths in Guilan province. The three main sources of road traffic death statistics are the Ministry of Health and Medical Education, the National Organization for Civil Registration and the Forensic Medicine Organization. Our results reveal a highly fragmented system with minimal cross-sectoral data exchange. Each stakeholder operates in a silo resulting in delays and redundancies in the operating system. In the absence of an effective communication among stakeholders, the information exchange was dependent on the family of the deceased. These fragmented information silos alter the compilation of cause of death statistics and result in under-reporting and discrepancies in road traffic deaths figures. ConclusionsDesigning a comprehensive road traffic information system that provides accurate and timely information requires an understanding of the information flow and the entangled web of different stakeholders operating in the system. Participatory systems approaches such as process mapping can assist in capturing the complexity of the system and the integration process by facilitating stakeholders’ engagement and ownership in improving the design of the system.

Research on Traffic sign recognition based on CNN Deep Learning Network

With the continuous development of social economy, the road traffic system as one of the basis of national economy is also increasingly developed, which is followed by the traffic safety problems are increasingly prominent. Among them, driving violations such as not obeying traffic signs are the main cause of traffic accidents. In this research, Traffic Sign Recognition (TSR) has become a hot research topic. The research status and application field of traffic sign detection and recognition technology are introduced and analyzed in detail, and the improvement of traffic sign database is introduced. After that, the application of CNN in image processing and traffic sign recognition is introduced, and the existing problems in traffic sign recognition are analyzed. The CNN deep learning network used in this paper can conduct training while identifying targets, effectively improve the recognition accuracy of traffic signs under complex natural conditions and reduce the time consumption.

Real-Time Event-Driven Road Traffic Monitoring System Using CCTV Video Analytics

Real-Time Event-Driven Road Traffic Monitoring System Using CCTV Video Analytics

Оптимізація управлінських підходів для впровадження та ефективності системи менеджменту безпеки дорожнього руху

The issues of optimizing management approaches for effective implementation of road traffic safety management systems in enterprises are considered. The authors examine internal and external factors affecting road safety and explore methods to enhance management approaches to ensure a high level of safety. Special attention is paid to process and risk-oriented approaches, as well as the importance of interaction with stakeholders. It is noted that a successful safety management strategy involves integrating safety into all areas of enterprise activities and continuously monitoring the system. Research confirms that adopting such a risk-oriented approach significantly enhances the effectiveness of road safety management systems. Reduction of risks and improvement of safety are the outcomes of implementing this strategy, enabling enterprises to more efficiently control and manage potential road hazards. Future research plans include focusing on developing new methods to assess the effectiveness of safety management systems, aimed at further improving the functionality and reliability of such systems. Additionally, there are plans to conduct a detailed study on the impact of innovative technologies on the functioning of road safety systems, to implement the most effective technical solutions. There are also plans to expand the application of safety management systems across various types of enterprises to ensure an optimal level of safety for a wide spectrum of road users. This may include not only transportation companies but also construction, logistics, and other industries involved in the transportation of goods and services. Taking into account the prospects of further research, it is expected that they will contribute to further improving road safety and ensuring stability for all road users, which is a crucial step in providing safety and comfort on highways.

The interaction between a driver and intelligent transport systems

A road traffic system is a complex system which includes four main parts – human, vehicle, road, and the natural environment. Road safety in Slovakia is based on the strategy of the government, as well as on European policies. It is important to implement complex strategic measures in the fields of traffic accidents, emergency services, and definitions of classifying injuries and deaths to decrease the number of injuries. The National plan’s measures must be included in strategic documents, which discuss road safety. It is necessary to combine several strategic goals in the transport process, to provide transport services according to users’ needs. The increase in the safety on the roads is a process that tries to mitigate negative impacts of traffic accidents. In recent years, Intelligent Transport Systems (ITS) have reduced several road traffic fatalities, particularly amongst passenger deaths. Various types of intelligent transport systems (ITS) are currently implemented in passenger cars and provide a higher level of road safety. However, there is a need to assess the effects of these systems on traffic safety. Drivers must perceive technologies as useful, effective, easy to use, affordable, and socially acceptable. There is also a need for drivers’ willingness to use ITS. This paper discusses the benefits of using intelligent transport systems (ITS) in urban conditions. They can enable the safety of road traffic. We verified it with a questionnaire. We have gathered 519 answers. The results were processed and evaluated in this article.

Smart Traffic Scheduling for Crowded Cities Road Networks

With the fast-expanding number of vehicles in smart cities, the management of road intersections and traffic congestion has grown to be major problems. Drivers often express their opinion that putting traffic lights on while taking traffic flows into account will have a significant impact on how traffic moves. This paper presents a smart Road traffic Control management system termed Urban Traffic Control (UTC) keeping real-time dynamic traffic flow in mind which helps in upgrading the level of road traffic network management. To provide an organized traffic arrangement, UTC presents methodologies such as vehicle counting, controlling process, and evaluation of lanes keeping status in mind, this whole procedure is implemented by taking the complete traffic network into an account instead of just considering intersections. The primary goal of our system is to lessen traffic jams by cutting down on the trip and waiting times vehicles spend at crossings and intersections. We need to assign a plan for traffic flow that has the least amount of traffic congestion and vehicle waiting time, for this purpose some indicators and models are introduced in this study. Lane weight, traffic jam indicator, and vehicle priority are among these models. As this work is an improvement on the current Road Network without much changing, we integrate our system on normal traffic lights which allow each lane a chance to move and we also considered the no-interference lane movement. To simulate our idea, we introduced a smart road traffic control system consisting of multi-agents, by using a NetLogo stimulator. To compare the fixed cycle traffic light, several vehicles (150 in total) with random behaviour were generated and scattered over 25 different intersections for the time duration of 9 h. This setting was used to test our smart traffic control solution on both lane flow and no interference movement flow. According to the obtained results, there was a 25.98% reduction in total average waiting time over simulation period for all vehicles and a reduction of 34.16% for no interference movement flow. These observations clearly state that suggested method is better suited for today's complex traffic conditions where change in infrastructure is minimal.

Influence of dedicated lanes for connected and automated vehicles on highway traffic flow

AbstractThe introduction of Connected and automated vehicles (CAVs) promises various social and economic benefits, but safety issues are encountered when CAVs are mixed with human‐driven vehicles (HDVs). This study presents three scenarios as lane operation alternatives for situations in which CAVs and HDVs are mixed. The proposed lane operation scenarios for CAVs are the operation of dedicated lanes (DLs) for CAVs, operation of a DL for CAVs and buses, and the operation of DLs for buses. For each scenario, the effects of the market penetration rate (MPR) on traffic efficiency and safety were evaluated. The following findings were obtained from the results: CAVs had a potential effect on each lane according to the lane operation scenario; traffic efficiency and safety improved in a traffic flow situation where CAVs and HDVs were mixed; traffic efficiency and safety were higher when operating DLs for CAVs than when operating a mixed traffic flow; and efficiency and safety were optimal when operating Scenario 2 (DL for CAVs and Buses) in the early stages of introducing CAV (MPR 10–30%) and operating Scenario 1 (DL for CAVs) in the mid‐ to long‐term stages (MPR 40–80%). These findings provide a basis for preparing new policy alternatives to the current policy of adopting DLs for buses. Furthermore, the evaluation of the effects of each DL operation in the transition period where CAVs and HDVs are mixed will contribute to the operation of an efficient and safe CAV‐based road traffic system.

A Straightforward Framework for Road Network Screening to Lombardy Region (Italy)

It is not possible to deal with sustainable mobility without considering road safety as a key element: Target 3.6 of the Sustainable Development Goals aims at halving the number of road deaths by 2030. To do so, further effort and effective tools are required for road authorities, to implement improvement measures and enhance road safety for all. Road network screening (RNS) is the first step of the whole Road Infrastructure Safety Management (RISM) System process. It is applied to a wide scale to assess the safety performance of the whole road network and identify the worst performing roads (or sites). The literature is quite rich with RNS models and methods, which have greatly improved, recently. Moreover, although many national frameworks on road safety have been issued over time, some barriers remain, specifically related to data quality, such as accurate crash location, which is mainly used to integrate crash data with other databases. In addition, most of these frameworks adopted partial indexes to identify black spots and presented results using fixed maps for visualization. This paper fills these gaps by the proposal of a straightforward operational framework to perform RNS, based on a simple and flexible rationale to integrate raw crash, traffic, and road data. Specifically, the framework: (i) manages crash location data, without relying on plane or geographical coordinates, which are missing or inaccurate and still are a crucial issue in many European countries such as Italy; (ii) adopts an adjusted accident cost rate index that integrates frequency and severity of crashes as well as a measurement of exposure; (iii) introduces variable maps that show the results at different jurisdiction levels. A relevant case study demonstrates the usefulness of this framework using 30,000+ crash data of the whole non-urban road network of the Lombardy Region (Northern Italy). Road authorities could adopt this framework to perform an accurate safety screening on the overall regional road network. Moreover, this framework could be implemented in a road traffic safety managerial system to better prioritise safety interventions within a tight budget and help achieve sustainable development targets.

Expressway Information Collection Processing and Control Technology Based on RFID Internet of Things

In order to solve the problems of highway traffic congestion and frequent traffic accidents, a technology method for highway information collection, processing, and control based on RFID Internet of Things is proposed. The highway information collection and processing control technology designed in this paper is based on radio frequency identification technology to realize the collection of highway vehicle information, analyze, and process the collected information, and finally get the road condition information. Through the extraction and analysis of the traffic flow information in the video surveillance, the background difference method is used to extract the relevant vehicle factors in the video, including the extraction of traffic flow information, vehicle model extraction, and vehicle speed extraction. Traffic detection provides convenience. The experimental data shows that from Monday to Friday on weekdays, the road congestion rates are 2.72%, 1.94%, 2.77%, 2.27%, and 3.47% respectively; the average vehicle speed on weekdays is 89.96 km/h, and the test results are fast and accurate. The proposed method integrates road information collection and road information service, realizes traffic detection when there are vehicles, and realizes detection and perception of large-scale road traffic systems. Travelers provide real-time traffic information and navigation services.

Guest Editorial Introduction to the Special Issue on Data Science for Intelligent Transportation Systems

Intelligent transportation system (ITS) is a key enabler for future road traffic management systems. The core components of ITS include vehicles, roadside units, and traffic command centers. They generate a large amount of data flow that is made up of both mobility and service-related data. Therefore, some data science methods to handle the transportation data are very necessary for ITS. Although some attempts have been done to explore data science methods for ITS, there exist various scientific and engineering challenges including software and hardware development, computational complexity, data multi-source heterogeneity, and privacy protection. Consequently, to fully explore the benefits of ITS applications like connected and autonomous vehicles, traffic control and prediction, road safety, and accident prediction, advanced data science methodologies and applications are in great need.

Assessing the management of road traffic infrastructure in form of BOT in Tien Giang province from the perspective of traffic safety and investment efficiency

Road traffic infrastructure management and exploitation is a material production industry with both service and technical attributes, directly related to human life, means of transport and other assets. Traffic safety criteria are expressed through the ability to smooth traffic and the safety when traveling. To meet the above requirements, the road traffic infrastructure system must ensure quality in all aspects such as: design - construction - operation management. The Trung Luong - My Thuan expressway through Tien Giang province, invested in BOT form, phase 1, does not meet traffic safety criteria. The route does not have an emergency stop lane for rescue activities in the event of an accident. This is due to the issues in investment project planning, surveying and designing. For that reason, the article evaluates the management and operation of roads invested in the form of public-private partnership (BOT) in Tien Giang province from the perspective of traffic safety and investment efficiency. The, the article points out the gaps of state management in the field of road exploitation, as a basis for proposing solutions to improve the efficiency of BOT road traffic operation in Tien Giang province, Vietnam.

Fusion of engineering insights and emerging trends: Intelligent urban traffic management system

Traffic congestion is a great concern, especially in urban areas where the vehicles’ number on roads continues to intensify significantly against the slow development of road infrastructure. To resolve this intractable problem, researchers proposed various Traffic Management Systems that rely on the fusion of traffic data sources and emerging technologies to maximize the traffic flow, and thus fluidify the intersections since they are the origin of traffic congestions, and also reroute the vehicles to avoid traffic congestions areas, and thus reduce fuel consumption and air pollution. Although there are many studies on traffic management, there is still a lack of research covering the entire urban road traffic management system. Therefore, this study intends to fill the gap, generating new insight into the state of research related to the entire Traffic Management System. The principal aim of this survey is to provide a complete view of current approaches proposed in the literature to handle the traffic congestion problem. We first supply a review of the body of knowledge in recent years of Traffic Management Systems. Second, we summarize the benefits and drawbacks of the recent literature. Third, we analyze and discuss the three main subsystems of a Traffic Management System and then classify the various contributions according to the subsystem to which they belong. Finally, we present and discuss future research orientations and open issues that need further investigation for a realistic and efficient Traffic Management System.

Long-Term COVID-19 Restrictions in Italy to Assess the Role of Seasonal Meteorological Conditions and Pollutant Emissions on Urban Air Quality

A year-round air quality analysis was addressed over four Italian cities (Milan, Turin, Bologna, and Florence) following the outbreak of the Coronavirus 2019 (COVID-19) pandemic. NO2, O3, PM2.5, and PM10 daily observations were compared with estimations of meteorological variables and observations of anthropogenic emission drivers as road traffic and heating systems. Three periods in 2020 were analysed: (i) the first (winter/spring) lockdown, (ii) the (spring/summer) partial relaxation period, and (iii) the second (autumn/winter) lockdown. During the first lockdown, only NO2 concentrations decreased systematically (and significantly, between −41.9 and −53.9%), mainly due to the drastic traffic reduction (−70 to −74%); PM2.5 varied between −21 and +18%, PM10 varied between −23 and +9%, and O3 increased (up to +17%). During the partly relaxation period, no air quality issues were observed. The second lockdown was particularly critical as, although road traffic significantly reduced (−30 to −44%), PM2.5 and PM10 concentrations dramatically increased (up to +87 and +123%, respectively), mostly due to remarkably unfavourable weather conditions. The latter was confirmed as the main driver of PM’s most critical concentrations, while strong limitations to anthropogenic activity—including traffic bans—have little effect when taken alone, even when applied for more than two months and involving a whole country.

Challenges and Opportunities for Future BEVs Adoption in Croatia

Electric vehicles (EVs) represent a revolution and the beginning of a new era in the development of the automotive industry. This study investigates the advantages and disadvantages of battery electric vehicles (BEVs) and the possibilities of their better future adoption in the Republic of Croatia. Based on an in-depth analysis of the current status of BEVs in Croatia, the study shows that the number of passenger BEVs and charging stations are constantly increasing. However, despite the many advantages of BEVs, such as a reduction in urban air pollution, reduction in greenhouse gas emissions, noise-free, less dependence on oil as a fuel, etc., there also are certain disadvantages, such as a limited range of vehicles, the correlation with an insufficient number of charging stations on the transport network as a whole, storage of lithium-ion batteries, maintenance of electric vehicles, high prices, and the safety of BEVs in the road traffic system. The practical implications of BEVs’ positive and negative effects and challenges for increasing their implementation in Croatia are discussed. The results and findings from this research could present a base for policymakers and decisionmakers to formulate policies and strategies to improve the opportunities for the adoption of BEVs in Croatia.

Road Intersection Coordination Scheme for Mixed Traffic (Human-Driven and Driverless Vehicles): A Systematic Review

Autonomous vehicles (AVs) are emerging with enormous potentials to solve many challenging road traffic problems. The AV emergence leads to a paradigm shift in the road traffic system, making the penetration of autonomous vehicles fast and its coexistence with human-driven cars inevitable. The migration from the traditional driving to the intelligent driving system with AV’s gradual deployment needs supporting technology to address mixed traffic systems problems, mixed driving behaviour in a car-following model, variation in-vehicle type control means, the impact of a proportion of AV in traffic mixed traffic, and many more. The migration to fully AV will solve many traffic problems: desire to reclaim travel and commuting time, driving comfort, and accident reduction. Motivated by the above facts, this paper presents an extensive review of road intersection mixed traffic management techniques with a classification matrix of different traffic management strategies and technologies that could effectively describe a mix of human and autonomous vehicles. It explores the existing traffic control strategies and analyses their compatibility in a mixed traffic environment. Then review their drawback and build on it for the proposed robust mix of traffic management schemes. Though many traffic control strategies have been in existence, the analysis presented in this paper gives new insights to the readers on the applications of the cell reservation strategy in a mixed traffic environment. Though many traffic control strategies have been in existence, the Gipp’s car-following model has shown to be very effective for optimal traffic flow performance.

Road traffic crashes and emergency response optimization: a geo-spatial analysis using closest facility and location-allocation methods

Increased occurrence of road traffic crashes in Kano metropolis has resulted in a steady loss of lives, injuries, and increased people's risk exposure. This study looked into the emergency response to road traffic crashes in Kano, with a view to improving efficiency by developing linkages and synergy between Emergency Healthcare Facilities (EHCF), ambulances, and crash hotspots. The geographical location and attributes of the major EHCF, crash hotspots along highway intersections, and the two existent ambulances at the Kano State Fire Service (KSFS) and Federal Road Safety Corp head offices (FRSC) were obtained using GPS surveying. Road traffic network data (vector format) was digitized from satellite image, from which two major road classes (highways and minor roads) were identified, as well as their respective speed limits. The length and speed constraints were used to calculate time distances. Nearest Neighbor and Network (closest facility, shortest route, and location-allocation) analyses were carried out. Location-allocation analysis was to determine based on defined criteria the best locations to allocate EHCF or ambulance for optimum coverage. The results demonstrated that EHCF, ambulances, and crash places have different distribution patterns with almost no linkages. Closest ambulance facility analysis revealed the FRSC ambulance takes 9.41 minutes to arrive to crash spot 18 (Maiduguri Road, following NNPC) and 7.52 minutes to arrive at AKTH, the nearest EHCF. Comparatively, getting to Court road incident scene (spot 16) and IRPH as the closest EHCF takes about 3 times the time it takes to get to spot 18 and 4 times the time it takes to get to AKTH. This means that practically almost all victims in the city suffocate before reaching to the hospital. This signifies that, in cases of demand for CPR at the incident scene, there are higher likelihood of dying as it is expected to be provided within the first four minutes after the crash. Based on a maximum of 4 minutes impedance cutoff from all directions towards the occurrences areas, location-allocation analysis found eight new locations to maximize coverage and improve efficiency. It is concluded that current road traffic crash emergency response system has been determined to be ineffective. As a result, more ambulances should be strategically placed to improve emergency response times.