Traffic fatalities within the City of Chicago that are included in Vision Zero Chicago (VZC) statistics. Vision Zero is Chicago’s commitment to eliminating fatalities and serious injuries from traffic crashes. The VZC Traffic Fatality List is compiled by the Chicago Department of Transportation (CDOT) after monthly reviews of fatal traffic crash information provided by Chicago Police Department’s Major Accident Investigation Unit (MAIU). CDOT uses a standardized process – sometimes differing from other sources and everyday use of the term -- to determine whether a death is a “traffic fatality.” Therefore, the traffic fatalities included in this list may differ from the fatal crashes reported in the full Traffic Crashes dataset (https://data.cityofchicago.org/d/85ca-t3if). Official traffic crash data are published by the Illinois Department of Transportation (IDOT) on an annual basis. This VZC Traffic Fatality List is updated monthly. Once IDOT publishes its crash data for a year, this dataset is edited to reflect IDOT’s findings. VZC Traffic Fatalities can be linked with other traffic crash datasets using the “Person_ID” field. State of Illinois considers a “traffic fatality” as any death caused by a traffic crash involving a motor vehicle, within 30 days of the crash. Fatalities that meet this definition are included in this VZC Traffic Fatality List unless excluded by any criteria below. There may be records in this dataset that do not appear as fatalities in the other datasets. The following criteria exclude a death from being considered a "traffic fatality," and are derived from Federal and State reporting standards. The Medical Examiner determined that the primary cause of the fatality was not the traffic crash, including: a. The fatality was reported as a suicide based on a police investigation. b. The fatality was reported as a homicide in which the "party at fault" intentionally inflicted serious bodily harm that caused the victim's death. c. The fatality was caused directly and exclusively by a medical condition or the fatality was not attributable to road user movement on a public roadway. (Note: If a person driving suffers a medical emergency and consequently hits and kills another road user, the other road user is included, although the driver suffering a medical emergency is excluded.) The crash did not occur within a trafficway. The crash involved a train or other such mode of transport within the rail dedicated right-of-way. The fatality was on a roadway not under Chicago Police Department jurisdiction, including: a. The fatality was occurred on an expressway. The City of Chicago does not have oversight on the expressway system. However, a fatality on expressway ramps occurring within the City jurisdiction will be counted in VZC Traffic Fatality List. b. The fatality occurred outside City limits. Crashes on streets along the City boundary may be assigned to another jurisdiction after the investigation if it is determined that the crash started or substantially occurred on the side of the street that is outside the City limits. Jurisdiction of streets along the City boundary are split between City and neighboring jurisdictions along the street centerline. The fatality is not a person (e.g., an animal). Change 12/7/2023: We have removed the RD_NO (Chicago Police Department report number) for privacy reasons.

Analysis of ‘Traffic Crashes - Vision Zero Chicago Traffic Fatalities’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/8394b076-2e6a-4686-a123-13dcfef7b0af on 12 February 2022.

--- Dataset description provided by original source is as follows ---

Traffic fatalities within the City of Chicago that are included in Vision Zero Chicago (VZC) statistics. Vision Zero is Chicago’s commitment to eliminating fatalities and serious injuries from traffic crashes. The VZC Traffic Fatality List is compiled by the City’s multi-departmental Fatal Crash Response Coordination Committee (FCRCC) that reviews fatal traffic crashes provided by Chicago Police Department’s Major Accident Investigation Unit (MAIU).

This committee uses a standardized process – sometimes differing from other sources and everyday use of the term -- to determine whether a death is a “traffic fatality” for VZC purposes. Therefore, the traffic fatalities included in this list may differ from the fatal crashes reported in the full Traffic Crashes dataset (https://data.cityofchicago.org/d/85ca-t3if).

Official traffic crash data are published by the Illinois Department of Transportation (IDOT) on a yearly basis. The traffic fatality list determined on an ongoing basis through the year may differ from IDOT’s official crash data for Chicago as IDOT may define the cause and location differently from the FCRCC. Once IDOT publishes its data for a year, crashes in this dataset for that year are edited to match IDOT’s determinations, unless the FCRCC disagrees with the IDOT determination – which happens only rarely and usually due to an interpretation of one of the criteria below.

VZC Traffic Fatalities can be linked with other traffic crash datasets using the “RD_NO” or “Person_ID” fields.

The FCRCC defines a “traffic fatality” for the purpose of VZC statistics as "any death caused by a traffic crash, within 30 days of the crash” and “involves a motor vehicle.” Fatalities that meet the VZC definition of a traffic fatality are included in this dataset unless excluded by the criteria below. There may be records in this dataset that do not appear as fatalities in the other datasets.

The following criteria exclude a death from being considered a "traffic fatality" for VZC purposes:

1. The Medical Examiner determined that the primary cause of the fatality was not the traffic crash, including:

a. The fatality was reported as a suicide based on a police investigation.

b. The fatality was reported as a homicide in which the "party at fault" intentionally inflicted serious bodily harm that caused the victim's death.

c. The fatality was caused directly and exclusively by a medical condition or where the fatality was not attributable to road user movement on a public roadway. (Note: If a person driving suffers a medical emergency and consequently hit and kills another road user, the other road user is included although the driver suffering a medical emergency is excluded.)

1. The crash did not occur within the public right-of-way.

2. The crash involved a train or such mode of transport within their dedicated right-of-way.

3. The fatality was on a roadway not under Chicago Police Department jurisdiction, including:

a. The fatality was occurred on an expressway. The City of Chicago does not have oversight on the expressway system. However, a fatality on expressway ramps occurring within the City jurisdiction will be counted in Vision Zero Chicago Traffic Fatalities.

b. The fatality occurred outside City limits. Crashes on streets along the City boundary may be assigned to another jurisdiction after the investigation if it is determined that the crash started or substantially occurred on the side of the street that is outside the City limits. Jurisdiction of streets along the City boundary are split between City and neighboring jurisdictions along the street center line.

1. The fatality is not for a person (e.g., an animal).

--- Original source retains full ownership of the source dataset ---

Objectives: With regard to the pediatric population involved in vehicle side impact collisions, epidemiologic data can be used to identify specific injury-producing conditions and offer possible safety technology effectiveness through population-based estimates. The objective of the current study was to perform a field data analysis to investigate injury patterns and sources of injury to 4- to 10-year-olds in side and oblique impacts to determine the potential effect of updated side impact regulations and airbag safety countermeasures. Methods: The NASS-CDS, years 1991 to 2014, was analyzed in the current study. The Abbreviated Injury Scale (AIS) 2005–Update 2008 was used to determine specific injuries and injury severities. Injury distributions were examined by body region as specified in the AIS dictionary and the Maximum AIS (MAIS). Children ages 4 to 10 were examined in this study. All occupant seating locations were investigated. Seating positions were designated by row and as either near side, middle, or far side. Side impacts with a principal direction of force (PDOF) between 2:00 and 4:00 as well as between 8:00 and 10:00 were included. Restraint use was documented only as restrained or unrestrained and not whether the restraint was being used properly. Injury distribution by MAIS, body region, and source of injury were documented. Analysis regarding occupant injury severity, body region injured, and injury source was performed by vehicle model year to determine the effect of updated side impact testing regulation and safety countermeasures. Because the aim of the study was to identify the most common injury patterns and sources, only unweighted data were analyzed. Results: Main results obtained from the current study with respect to 4- to 10-year-old child occupants in side impact were that a decrease was observed in frequency of MAIS 1–3 injuries; injuries to the head, face, and extremities; as well as injuries caused by child occupant interaction with the vehicle interior and seatback support structures in 1998 model year passenger cars and newer. Conclusions: Results from this study could be useful in design advances of pediatric anthropomorphic test devices, child restraints, as well as vehicles and their safety countermeasure systems.

Objective: Recent changes in FMVSS have led to the utilization of side air curtains to provide occupant retention during rollover events. However, the safety advantage provided by the air curtains relies on the vehicle system’s ability to detect the rollover event and deploy the curtains. The purpose of this study is to identify crash and vehicle characteristics in motor vehicle rollovers that influence side air curtain deployment and occupant outcomes. The current study aims to improve the understanding of rollover events and inspire more robust air curtain deployment strategies. Methods: Study data were extracted from rollover cases documented in the NASS-CDS data set from 2011 to 2015. Vehicle model years of 2011 or later with side air curtains installed were examined. The presence of a rollover sensor in each vehicle was determined from vehicle content data available on the Insurance Institute for Highway Safety’s crash rating website. The resulting data set contained 14,003 weighted cases of rollover accidents in which the side air curtain did not deploy (40 raw count) and 23,178 cases of deployment (80 raw count). Results: Several crash event and vehicle characteristics were similar for the nondeployed and deployed groups, including number of quarter turns, primary location of damage, initiating event for the rollover, and vehicle model year. However, the nondeployed group included significantly more passenger vehicle body types (vs. SUV or truck) and had a significantly lower rate of rollover sensor presence. Presence of a rollover sensor increased the odds air curtain deployment by a factor of 36.5 (95% confidence interval [CI], 5.06–265). Cases in which both side air curtains deployed resulted in a higher frequency of injured occupants (Maximum Abbreviated Injury Scale [MAIS] ≥ 3). However, rollover events resulting in these injuries were also associated with higher rates of impact with another object or vehicle and damage to the roof of the vehicle, suggesting a higher energy event. Conclusions: Nondeployment of the side curtain airbags in rollovers occurred more frequently in vehicles without dedicated rollover sensors, which were most frequently passenger vehicles.

Analysis of ‘Road traffic accidents ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/d22714da-94a1-4380-96f9-404128a2cbd3 on 15 January 2022.

--- Dataset description provided by original source is as follows ---

Data on traffic accidents in Schleswig-Holstein

# Description of the fields

— ‘ID’ — Current number of the accident (one record per accident) — ‘ULAND’ — Land, here only ‘01’ = Schleswig-Holstein — 'UREGBEZ' — always’ 0’ — ‘UKREIS’ — Kreis — ‘UGEMEINDE’ — Municipality — ‘UJAHR’ — year of accident — ‘UMONAT’ — month of accident — ‘USTUNDE’ — hour of accident — ‘UWOCHENTAG’ — Day of the week: 1 = Sunday, 2 = Monday, 3 = diestag,... 6 = Saturday — ‘UKATEGORY’ — category of accident (classification criterion is the most serious accident sequence): 1 = fatal accident, 2 = accident with serious injuries, 3 = accident with minor injuries — ‘UART’ — type of accident: 1 = collision with starting/continuing/dormant vehicle, 2 = collision with preceding/waiting vehicle, 3 = collision with vehicle running side in the same direction, 4 = oncoming vehicle collision, 5 = collision with turning/cross vehicle, 6 = collision between vehicle and pedestrian, 7 = impact on road barrier, 8 = agreement between ground and right, 9 = agreement from other ground to ground 0, — ‘UTYP1’ — accident type: 1 = driving accident, 2 = turning accident, 3 = turning/cross accident, 4 = accident exceeding, 5 = accident caused by dormant traffic, 6 = longitudinal accident, 7 = other accident — ‘ULICHTVERH’ — Luminous conditions: 0 = daylight, 1 = insulation, 2 = darkness — ‘Istrad’ — accident with wheel: 1 if the accident involved at least one bicycle — ‘actual cars’ — Car accident: 1 if the accident involved at least one passenger car — ‘IstFuss’ — accident involving pedestrians: 1 if the accident involved at least one pedestrian — ‘IstKrad’ — accident by motorcycle: 1 if the accident involved at least one motorcycle, such as Mofa, motorcycle/scooter — ‘IstGkfz’ — accident involving a goods vehicle: 1 if the accident involved at least one lorry with a standard bodywork and a total weight exceeding 3,5 tonnes, a truck with a tank or special body, a tractor unit or other tractor — ‘IstOther’ — Accident with others: 1 if the accident involved at least one means of transport not mentioned above (e.g. bus or train) — ‘USTRZUSTAND’ — Road condition: 0 = dry, 1 = wet/wet/plugged, 2 = winter smooth — ‘LINREFX’ — The geo-coordinates of the place of accident on the road section (UTM coordinate of the ETRS89 reference system, zone 32N) — 'LINREFY’ — ‘XGCSWGS84 '— The geo-coordinates of the place of accident on the road section (geographical coordinates in decimal degrees of the WGS84 reference system) — 'YGCSWGS84’

# Source of data

This is an extract from the accident data for Germany https://unfallatlas.statistikportal.de/_opendata2021.html

Filtered to those entries for which ‘ULAND = 01’. In the geocoordinates, comma was replaced by a decimal point.

Further explanations on traffic accident data can be found on the page of the Accident Atlas of the Statistical Offices of the Federal Government and the Länder.

--- Original source retains full ownership of the source dataset ---

Vehicle Crash Test Barrier Market Outlook

The global market size of the Vehicle Crash Test Barrier Market is poised for significant growth, with estimates predicting it will rise from USD 1.2 billion in 2023 to USD 2.3 billion by 2032, reflecting a compound annual growth rate (CAGR) of 7.9%. This robust growth is primarily driven by the increasing emphasis on vehicle safety, stringent regulatory standards, and the rising number of vehicular accidents worldwide.

The growth factors for this market are multifaceted. Firstly, the rising consumer awareness regarding vehicle safety has significantly boosted the demand for rigorous crash testing. Consumers are increasingly prioritizing safety ratings when purchasing vehicles, which compels manufacturers to invest heavily in advanced crash testing technologies. Furthermore, governmental regulations and safety standards are becoming more stringent globally, necessitating comprehensive vehicle testing to ensure compliance. This regulatory pressure is a significant driver for the market.

Another significant growth factor is the ongoing advancements in automotive technology. The rise of electric and autonomous vehicles requires new and more sophisticated crash testing methodologies. These advancements are not only pushing the boundaries of current testing protocols but also necessitating the development of new types of test barriers that can accurately simulate real-world crash scenarios. Additionally, the increasing complexity of modern vehicles, with advanced materials and construction techniques, requires more diversified testing approaches.

Moreover, the increasing number of road accidents globally has put a spotlight on the need for improved vehicle safety. According to the World Health Organization, approximately 1.35 million people die each year as a result of road traffic crashes. This alarming statistic has prompted regulatory bodies and vehicle manufacturers to invest more in crash testing to enhance vehicle safety features. The development of new crash test barriers that can better simulate a variety of collision scenarios is crucial for this purpose.

Geographically, North America and Europe have traditionally been at the forefront of vehicle safety standards, driven by stringent regulations and a high level of consumer awareness. However, emerging markets in Asia Pacific and Latin America are rapidly catching up due to increasing vehicle sales and the adoption of international safety standards. Asia Pacific, in particular, is expected to witness substantial growth, driven by countries like China and India, where vehicular growth is at an all-time high.

In the context of enhancing vehicle safety, the role of Road Crash Attenuator Sales has become increasingly significant. These devices are designed to absorb the impact energy during a collision, thereby reducing the severity of crashes. The growing emphasis on road safety and the implementation of advanced safety measures have led to a surge in the demand for crash attenuators. These systems are particularly crucial in high-risk areas such as highways and urban intersections, where the likelihood of accidents is higher. As governments and regulatory bodies worldwide strive to improve road safety standards, the market for road crash attenuators is expected to witness substantial growth. Manufacturers are focusing on developing innovative solutions that not only enhance safety but also offer cost-effectiveness and ease of installation.

Type Analysis

The Vehicle Crash Test Barrier Market can be segmented by type into rigid barriers, semi-rigid barriers, and flexible barriers. Rigid barriers are typically used in frontal crash tests. These barriers are designed to simulate a solid object, such as a wall or another vehicle, and are crucial for determining the impact resistance of a vehicleÂ’s structure. The demand for rigid barriers is driven by stringent regulatory requirements and the need for precise testing methodologies that can accurately replicate real-world crash scenarios.

Semi-rigid barriers, on the other hand, offer a combination of flexibility and rigidity. They are used in crash tests to simulate impacts with objects such as guardrails or median barriers. These barriers are essential for evaluating the performance of vehicles in off-center impacts and sideswipe collisions. The increasing focus on enhancing side-impact protection in vehicles has significantly boosted the demand for

Objective: The odds of death for a seriously injured crash victim are drastically reduced if he or she received care at a trauma center. Advanced automated crash notification (AACN) algorithms are postcrash safety systems that use data measured by the vehicles during the crash to predict the likelihood of occupants being seriously injured. The accuracy of these models are crucial to the success of an AACN. The objective of this study was to compare the predictive performance of competing injury risk models and algorithms: logistic regression, random forest, AdaBoost, naïve Bayes, support vector machine, and classification k-nearest neighbors.Methods: This study compared machine learning algorithms to the widely adopted logistic regression modeling approach. Machine learning algorithms have not been commonly studied in the motor vehicle injury literature. Machine learning algorithms may have higher predictive power than logistic regression, despite the drawback of lacking the ability to perform statistical inference. To evaluate the performance of these algorithms, data on 16,398 vehicles involved in non-rollover collisions were extracted from the NASS-CDS. Vehicles with any occupants having an Injury Severity Score (ISS) of 15 or greater were defined as those requiring victims to be treated at a trauma center. The performance of each model was evaluated using cross-validation. Cross-validation assesses how a model will perform in the future given new data not used for model training. The crash ΔV (change in velocity during the crash), damage side (struck side of the vehicle), seat belt use, vehicle body type, number of events, occupant age, and occupant sex were used as predictors in each model.Results and Conclusions: Logistic regression slightly outperformed the machine learning algorithms based on sensitivity and specificity of the models. Previous studies on AACN risk curves used the same data to train and test the power of the models and as a result had higher sensitivity compared to the cross-validated results from this study. Future studies should account for future data; for example, by using cross-validation or risk presenting optimistic predictions of field performance. Past algorithms have been criticized for relying on age and sex, being difficult to measure by vehicle sensors, and inaccuracies in classifying damage side. The models with accurate damage side and including age/sex did outperform models with less accurate damage side and without age/sex, but the differences were small, suggesting that the success of AACN is not reliant on these predictors.

Corresponding data set for Tran-SET Project No. 17ITSTSA01. Abstract of the final report is stated below for reference:

"The Transportation and Capital Improvement of the City of San Antonio, Texas Department of Transportation (TxDOT) and other related agencies often make several efforts based on traffic data to improve safety at intersections, but the number of intersection crashes is still on the high side. There is no one size fits all solution for intersections and the City is often usually confronted with doing best value option analysis on different solutions to choose the least expensive yet more advancements. The goal of this project was to obtain the relationship between road network characteristics and public safety with a focus on intersections; perform a thorough analysis of critical intersections with high crash incidents and crash rates within the city of San Antonio, Texas, and analyze key factors that lead to crashes and recommend effective safety countermeasures. Researchers conducted the following tasks: literature review, crash data analysis, factors affecting crashes at intersections, and the development of possible solutions to some of the identified challenges. Several variables and factors were analyzed, including driver characteristics, like age and gender, road-related factors and environmental factors such as weather conditions and time of day ArcGIS was used to analyze crash frequency at different intersections, and hotspot analysis was carried out to identify high-risk intersections. The crash rates were also calculated for some intersections. The research outcome shows that there are more male drivers than female drivers involved in crashes, even though we have more licensed female drivers than male drivers. The highest number of crashes involved drivers within the age range of 15 – 34 years; this is an indication that intersection crash is one of the top threats to the young generation. The study also shows that the most common crash type is the angle crash which represents over 23% of the intersection crashes. Driver’s inattention ranked first among all the contributing factors recorded. The highrisk intersections based on crash frequency and crash rate show that the intersection along the Bandera Road and Loop 1604 is the worst in the city, with 399 crashes and 8.5 crashes per million entering vehicles. The research concluded with some suggested countermeasures, which include public enlightenment and road safety audit as a proactive means of identifying high-risk intersections."

The folder 'experiment' contains the raw, simulated, and fitted images as well as the extracted differential cross sections and polarisation moments. The folder 'calculations' contains the calculated differential cross sections (isotropic, x-axis and z-axis orientation) and the polarisation moments at the experimental field and at infinite field. Also included are the maximized differential cross sections calculated at infinite electric field. All files are provided as .dat files.

The objectives of this study are to: (1) evaluate the fatality risk of powered two-wheeler (PTW) riders in collisions with various types of opponent vehicles; (2) estimate the likelihood of different impact orientations between PTWs and other vehicles involved, and (3) develop an initial crash-based speed–fatality prediction model specific to the United States that controls for vehicle orientation. Data was extracted from the National Highway Traffic Safety Administration’s Crash Reporting Sampling System and the Fatality Analysis Reporting System covering 2017–2021. This data was used to estimate the fatality risks associated with various types of opponent vehicles involved in PTW crashes. The vehicles involved in each crash were coupled based on the vehicles’ impact locations, and the effects of different vehicle orientations on fatality were estimated using odds ratio analysis. Multivariate logistic regressions were used to model the relationship between impact speed and fatality risk for front-end collisions involving PTWs. Crashes involving buses and heavy trucks posed a significantly higher risk to PTW riders, with the fatality risk being four times greater compared to collisions with passenger vehicles. This risk varied based on impact orientation; frontal collisions with the front or sides of the opposing vehicle were the most dangerous, with fatality odds approximately four times higher than rear-end impacts. The speed-fatality prediction model showed the fatality risk increased with higher PTW travel speed while accounting for the expected higher fatality risk in crashes involving older riders, heavy vehicles, or un-helmeted riders. The significant influence of opponent vehicle type on fatality risk in crashes involving PTWs highlights the need for further investigation into vehicle-specific crash prevention and mitigation strategies, especially for light and heavy trucks. Similarly, the high variability in fatality odds across different crash configurations underscores the importance of integrating impact orientation surrogate variables into injury prediction models. The speed–fatality prediction model developed in this study provides a foundational framework for evaluating the effectiveness of advanced rider assistance systems and other safety interventions that reduce crash speed. Future research should explore the benefits of such measures through simulation and real-world testing.

Automotive Crash Test Facility Market Outlook

In 2023, the global market size for automotive crash test facilities was valued at approximately $2.8 billion and is projected to reach around $4.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 5.2%. This market growth is driven by escalating demand for vehicle safety improvements and stringent government regulations mandating crash tests for new vehicles.

The rising focus on vehicle safety is a significant growth factor for the automotive crash test facility market. With increasing awareness among consumers about the importance of vehicle safety features, auto manufacturers are compelled to invest heavily in crash testing to ensure their vehicles meet safety standards. This trend is further amplified by the introduction of advanced driver-assistance systems (ADAS) and autonomous driving technologies, which necessitate rigorous testing protocols to guarantee their effectiveness in real-world scenarios. As a result, the demand for state-of-the-art crash test facilities is on the rise, propelling market growth.

Technological advancements in crash testing methodologies and equipment are also contributing to the market expansion. The development of sophisticated crash test dummies, high-speed cameras, and data acquisition systems has enhanced the accuracy and reliability of crash test results. Additionally, innovations in virtual crash testing using computer simulations have revolutionized the industry by providing cost-effective and efficient alternatives to physical crash tests. These advancements enable manufacturers to conduct comprehensive safety evaluations, thus fueling the demand for both physical and virtual crash test facilities.

Government regulations and standards play a pivotal role in driving the market for automotive crash test facilities. Regulatory bodies across the globe, including the National Highway Traffic Safety Administration (NHTSA) in the United States and the European New Car Assessment Programme (Euro NCAP), have established stringent safety requirements that vehicles must meet before they can be sold. These regulations necessitate extensive crash testing, compelling automakers to invest in advanced testing facilities. Moreover, the growing emphasis on pedestrian safety and the introduction of new safety standards for electric vehicles are expected to further boost the demand for crash test facilities.

Crash Test Dummies are integral to the process of evaluating vehicle safety during crash tests. These anthropomorphic test devices are meticulously designed to mimic the size, weight, and articulation of the human body, allowing for accurate simulation of human responses in crash scenarios. Equipped with numerous sensors, crash test dummies provide critical data on the forces exerted on the body during a collision, helping engineers assess the potential for injury. The evolution of crash test dummies has been marked by advancements in technology, enabling more precise measurements and a better understanding of crash dynamics. As vehicle designs become more complex with the integration of new technologies, the role of crash test dummies becomes even more crucial in ensuring that safety standards are met and exceeded.

Regionally, North America and Europe are anticipated to dominate the automotive crash test facility market, owing to the presence of leading automobile manufacturers and stringent safety regulations. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period. The rapid expansion of the automotive industry in countries like China and India, coupled with increasing investments in vehicle safety, is driving the demand for crash test facilities in this region. Moreover, government initiatives to enhance road safety and the rising adoption of electric vehicles are likely to contribute to the market growth in the Asia Pacific region.

Type Analysis

The automotive crash test facility market is segmented by type into frontal crash test facilities, side impact crash test facilities, rear impact crash test facilities, rollover crash test facilities, and others. Frontal crash test facilities represent a significant segment due to the high frequency of head-on collisions and the severe impact they can have on vehicle occupants. These facilities are designed to replicate frontal crashes and assess the effectiveness of safety mechanisms such as airbags and crumple zones. The continuous advancements in frontal crash

Snapshot img

Automotive Crash Test Dummies Market Size 2025-2029

The automotive crash test dummies market size is forecast to increase by USD 17.2 million at a CAGR of 2.9% between 2024 and 2029.

The market is experiencing significant growth due to the increasing emphasis on vehicle safety and stringent regulatory requirements. The market is driven by the rising demand for advanced crash test dummies that accurately simulate human responses during accidents. One of the key trends influencing market growth is the increasing use of moving dummies for pedestrian protection systems. These dummies help simulate the impact on pedestrians during collisions, enabling manufacturers to design vehicles that minimize harm to both occupants and pedestrians. Another trend shaping the market is the increasing popularity of crash test simulators. These simulators allow manufacturers to conduct numerous tests in a controlled environment, reducing the need for physical testing and saving time and resources.
However, the market also faces challenges such as the high cost of developing advanced crash test dummies and the need for continuous research and development to keep up with evolving safety standards. Companies seeking to capitalize on market opportunities and navigate challenges effectively should focus on collaborating with regulatory bodies and investing in research and development to create innovative and cost-effective solutions.

What will be the Size of the Automotive Crash Test Dummies Market during the forecast period?

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The market encompasses safety research and engineering, focusing on enhancing occupant protection and vehicle safety. Key areas of development include small overlap tests, digital twin technology, and lightweight materials. Passive safety is a primary concern, with advancements in composite materials, hybrid III dummies, and injury severity score analysis. Vehicle dynamics and artificial intelligence are also integral, utilizing sensor technology for predictive modeling and machine learning in virtual testing. Additionally, the market explores advanced materials and future mobility concepts, such as accident reconstruction, full-body dummies, and pedestrian dummies.
The integration of active safety and forensic analysis further strengthens the market's significance in the automotive industry. Data analysis plays a crucial role in understanding the impact velocity and vehicle behavior during crashes, ensuring optimal safety standards.

How is this Automotive Crash Test Dummies Industry segmented?

The automotive crash test dummies industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  Male crash test dummy
  Female crash test dummy
  Child crash test dummy


Application

  Passenger vehicle
  Commercial vehicle


Type

  Frontal Impact Testing
  Side Impact Testing
  Rear Impact Testing
  Pedestrian Impact Testing


End-user Industry

  Automotive Manufacturers
  Government & Regulatory Agencies and Research
  Testing Centers


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    Spain
    UK


  Middle East and Africa

    UAE


  APAC

    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Product Insights

The male crash test dummy segment is estimated to witness significant growth during the forecast period.

In the realm of automotive safety, metal additive manufacturing plays a pivotal role in the production of essential components for crash testing. Crash test dummies, a critical element in assessing vehicle safety, have evolved with the help of this technology. Manufacturers like Humanetics utilize metal additive manufacturing to create various male crash test dummies, catering to different body structures, reflecting the increasing global average male weight. These dummies undergo numerous tests, including frontal impact, side-impact, rear-impact, rollover, and pedestrian impact tests. Each dummy serves multiple purposes, necessitating frequent replacement. Government regulations mandate stringent safety standards, driving the demand for advanced safety features.

Research and development in this area is ongoing, with entities such as testing laboratories and computer-aided engineering firms employing finite element analysis and safety testing to optimize designs. Injury criteria, such as the femur injury criterion and chest injury criterion, are essential benchmarks in evaluating the effectiveness of safety features. Autonomous vehicles and advanced driver-assistance systems are transforming the automotive landscape. Metal additive manufacturing contributes to the production of impact sensors and oth

NASS CDS data on rollover crashes involving vehicles with side air curtains

The global automotive side impact beam market is experiencing robust growth, driven by stringent safety regulations mandating their inclusion in vehicles and a rising consumer preference for enhanced vehicle safety features. The market, segmented by application (passenger cars and commercial vehicles) and type (tubular and cap-shaped), is witnessing a considerable shift towards lighter yet stronger materials to improve fuel efficiency without compromising safety. The increasing adoption of advanced driver-assistance systems (ADAS) and the rising demand for electric vehicles (EVs) further contribute to market expansion. Key players like Kozu Seisakusho, Gestamp Automocion, and Aisin are investing heavily in research and development to introduce innovative beam designs and materials, fostering competition and driving innovation within the sector. The market is geographically diverse, with North America and Europe representing significant revenue contributors. However, the Asia-Pacific region, particularly China and India, is projected to exhibit the highest growth rate due to rapid automotive production and increasing disposable incomes. While material costs and manufacturing complexities pose some challenges, the overall market outlook remains positive, fueled by consistent technological advancements and a global focus on passenger safety. The forecast period (2025-2033) anticipates a sustained growth trajectory for the automotive side impact beam market. This projection is underpinned by continued advancements in lightweighting technologies, the incorporation of more sophisticated designs for improved crash performance, and the growing adoption of active safety features. The expansion into emerging markets will play a crucial role in shaping the market's future, with manufacturers strategically focusing on cost-effective solutions to cater to a broader customer base. Competition amongst established players and the emergence of new entrants will further drive innovation and potentially lead to price adjustments within the market. While regional variations in regulatory landscapes and economic conditions might influence growth rates, the fundamental drivers—safety regulations and consumer demand—are expected to remain robust, resulting in a significant market expansion throughout the forecast period.

The global automobile crash test device market is projected to exhibit a CAGR of XX% during the forecast period (2025-2033), reaching a value of USD XXX million by 2033. The market's expansion is driven by the increasing demand for vehicle safety and the implementation of stringent regulations for vehicle crash testing. Key trends in the market include the adoption of advanced technologies such as high-speed cameras, laser scanners, and data acquisition systems. The market is segmented into passenger cars and commercial vehicles based on application. The passenger car segment is expected to hold a larger market share due to the growing emphasis on passenger safety. In terms of type, the market is divided into frontal crash test devices and side impact test devices. Geographically, the market is segmented into North America, Europe, Asia Pacific, Middle East & Africa, and South America. North America is expected to lead the market due to the presence of major automotive manufacturers and stringent vehicle safety regulations.

The Frontal Impact and Side Impact Crash Test Barrier market plays a pivotal role in the automotive safety industry, providing essential tools for testing vehicle crashworthiness and ensuring compliance with safety regulations. These crash test barriers simulate real-world collision scenarios, allowing manufacturers

This dataset contains traffic accident records from Addis Ababa City, Ethiopia, spanning the years 2016 to 2022. The dataset includes 13,064 rows and 31 features related to various factors influencing road traffic accident severity. The target variable is categorized into three severity levels: slight, serious, and fatal injuries.The dataset aims to facilitate the analysis and prediction of road traffic accident severity using machine learning algorithms. It was initially collected by the Addis Ababa Police Department and contains a rich set of variables, including weather conditions, collision type, driver demographics, road conditions, and time of accident, among others. This comprehensive dataset serves as a foundation for developing predictive models for accident severity, which can be valuable for urban planning, traffic safety research, and policy development.Key features in the dataset include:Accident Severity (Target Variable): Categorical variable indicating the severity of the accident (slight, serious, fatal).Weather Conditions: Describes the weather at the time of the accident (e.g., clear, rainy, foggy).Collision Type: The type of collision (e.g., rear-end, side-impact).Driver Demographics: Features like driver age, driver sex, and experience that may affect accident outcomes.Location: Various aspects of the accident location, including junction type, road type, and alignment.Temporal Features: Time-related variables such as day of the week, time of day, and seasonal trends.Vehicle Information: Includes vehicle type, vehicle defect, vehicle movement, and the relationship between the vehicle owner and the driver.Casualty Information: Includes age, sex, and fitness of the casualty.

The global crash test sensor market is experiencing robust growth, driven by stringent automotive safety regulations worldwide and the increasing demand for advanced driver-assistance systems (ADAS). The market's expansion is fueled by the integration of sophisticated sensor technologies in vehicles, enabling more accurate and comprehensive crash data acquisition for improved vehicle safety designs. The rising adoption of electric and autonomous vehicles further contributes to market growth, as these vehicles require more extensive and sensitive crash testing to ensure occupant protection. Key players such as FUTEK, Kistler, and Bosch Sensotech are leading the innovation in sensor technology, offering a range of products catering to diverse testing needs, from basic impact detection to complex biomechanical measurements. This technological advancement leads to a shift towards more precise data acquisition, enabling automotive manufacturers to refine vehicle designs and optimize safety features more effectively. However, the high cost associated with advanced crash test sensors and the specialized expertise required for installation and data analysis can present challenges to market expansion. Furthermore, fluctuations in raw material prices and the cyclical nature of the automotive industry can impact market growth. Despite these restraints, the long-term outlook for the crash test sensor market remains positive, driven by consistent technological advancements and the unwavering focus on improving vehicle safety across the globe. The market is segmented by sensor type (accelerometers, load cells, pressure sensors etc.), application (frontal impact, side impact, rollover etc.), and vehicle type (passenger cars, commercial vehicles). Geographic regions such as North America and Europe are expected to maintain significant market share due to robust automotive industries and stringent safety standards. We project continued market expansion in emerging markets like Asia-Pacific as vehicle production increases in these regions.

The global market for automobile crash test female models is experiencing significant growth, driven by increasing awareness of gender-specific safety concerns and stricter regulations mandating the use of anthropomorphic test devices (ATDs) representing a wider demographic. The market, estimated at $150 million in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 8% from 2025 to 2033, reaching approximately $275 million by 2033. This growth is fueled by advancements in ATD technology, allowing for more accurate simulation of female biomechanics in crashes, leading to improved vehicle safety designs tailored to female occupants. Key market drivers include the rising demand for enhanced safety standards, growing female vehicle ownership, and increasing regulatory pressure to incorporate female-specific crash test data. Leading companies like Humanetics, Kistler Group, and Cellbond are driving innovation in this space, investing in R&D to develop more sophisticated and realistic female ATDs. However, the market also faces certain restraints. The high cost of developing and maintaining advanced ATDs can be a barrier to entry for smaller companies. Furthermore, the complexity of accurately modeling female biomechanics necessitates ongoing research and development, which can impact short-term profitability. Despite these challenges, the long-term outlook for the automobile crash test female model market remains positive, as the focus on improving overall vehicle safety and addressing gender-specific safety disparities continues to grow. Market segmentation is likely driven by ATD type (e.g., full-body, upper-body), application (e.g., frontal impact, side impact), and geographic region.