Speeding Research Articles

An Investigation of Double Collisions of Pickup Trucks with Multiple Fatalities in Narathiwat Province, Thailand, October 2023

On 11 Oct 2023, a pickup truck crashed into a roadside tree in Narathiwat Province, southern Thailand after overtaking another vehicle. We conducted a descriptive study by reviewing medical records and interviewing rescuers, officers, survivors, and witnesses. We surveyed the collision site, reviewed video records, and used Haddon’s matrix to assist with the analysis. A pickup truck carrying 11 passengers (including the driver) overtook another pickup truck on a stretch of road. The driver of the first pickup truck lost control due to tire deflation and crashed into a tree resulting in eight deaths (72.7%) and three hospitalizations (27.3%). All deaths were caused by severe head injuries. Multiple factors during pre-crash (vehicle unfamiliarity leading to improper passing sight distance and speeding), the crash (overloaded truck and a roadside tree), and post-crash such as poor communication, contributed to the severity of this event. The driver of the truck had no driving license and was unfamiliar with the vehicle. Six passengers were sitting in the truck’s cab and three were in the cargo bed. Pre-crash and crash speeds were determined to be 80 and 100 kilometers per hour, respectively. The passing sight distance was grossly insufficient. Poor communication in the rescue process and the crowd of people at the scene resulted in improper emergency management. Strengthening law enforcement, increasing the number of speed limit signs, felling roadside trees, and practicing mass casualty incidents should be implemented.

Perbandingan Penegakan Aturan Lalu Lintas Antara Penerapan Tilang Manual Dan Electronic Traffic Law Enforcement (ETLE) Di Kota Padang

Enforcement of traffic rules is regulated in Law Number 22 of 2009 concerning Road Traffic and Transportation and Government Regulation No. 80 of 2012 concerning Procedures for Inspecting Motorized Vehicles on the Road and Enforcement of Traffic and Road Transportation Violations. The development of an electronic-based law enforcement system gave birth to Electronic Traffic Law Enforcement as an innovation to overcome obstacles in the application of manual fines. However, in its application, ETLE was also not free from various problems, so the urgency was born to conduct research to find out and compare the procedures for applying manual and ETLE tickets and how to apply future tickets in Indonesia, especially in the city of Padang as a research location. This study uses empirical juridical methods, the data used is primary data from interviews with Padang Police TMC operators and secondary data is in the form of document studies. The result of the research is that manual poles are directly imposed on violators by officers. Meanwhile, ETLE is a modern ticket system used by the police to monitor and prosecute traffic violations electronically with camera and sensor technology to identify vehicles that violate traffic rules, such as violating a red light or crossing the speed limit. Obstacles that occur in manual ticketing are low legal awareness from both law enforcers and the public. The obstacles that occur in ETLE are the limitations of static and mobile camera devices so that the application is not comprehensive. The application of fines in the future will still use a combination of manual and electronic ticketing due to the low level of public legal awareness and the uneven distribution of electronic ticketing devices in the city of Padang.

Decision support for traffic safety: case of rear-end collision modelling

ABSTRACT This paper presents the decision problem of selecting a collision-warning activation algorithm for Rear-End Collision Alert Signal (RECAS) systems installed in motorcycles and other powered two-wheelers. Using Agent-Based Modelling, Discrete Event Simulation and System Dynamics, we have developed a hybrid simulation model of three scenarios of rear-end collisions to measure the performance of several algorithms found in the literature. The best-performing algorithm, by Hirst & Graham, has reduced the probability of collisions on average by 31.21% in comparison with the baseline scenario of using a standard brake light. Using this algorithm also resulted in up to 11.20% reduction in the estimated severity of injuries when a rear-end collision was not averted. As the Hirst & Graham algorithm was the most effective in all the tested emergency braking scenarios and across all the tested speed limits, we recommend this algorithm to be used in RECAS systems in powered two-wheelers.

A SURVEY OF VERTEBRATES’ ROADKILL WITHIN A 10 KM RADIUS FROM THE CENTRE OF KUALA PILAH TOWN, NEGERI SEMBILAN

Assessing animal roadkill provides valuable insights into the diversity and abundance of different species within a particular area. This study has the potential to uncover factors influencing the occurrence of animal roadkill. However, there is a scarcity of studies focusing on animal roadkill in small, secluded areas such as the Kuala Pilah district, Negeri Sembilan. Thus, this study evaluates the composition and distribution of vertebrate roadkill within a 10 km radius from the centre of Kuala Pilah Town, with a focus on temporal (time of discovery), spatial (types of roads and types of surrounding areas), and environmental factors (the presence of streetlights). The road segments located within a 10 km radius from Kuala Pilah Town have been examined in ten weeks and the found carcasses were identified by their taxonomic groups and photographed. Further, their discovery location has been observed and marked with coordinates. A chi square test was then performed to evaluate the occurrence of animal roadkill with all recorded data. This study revealed 48 animal carcasses, with a taxonomic composition of 27.08% birds (13 individuals), 50% mammals (24 individuals), 18.75% reptiles (9 individuals), and 4.17% amphibians (2 individuals). The roadkill patterns showed that squirrels and cats as the most prevalent species found, with higher carcass rates found in plantation/forest areas and on state roads. Roadkill occurrences increased between 7 a.m. and 1 p.m., while streetlights had no noticeable impact on the numbers. Overall, mammals turned out to be the most frequent vertebrate class involved in roadkill with time being the only significant factor influencing the numbers. With a better understanding of the factors influencing vertebrate roadkill, mitigation strategies such as fencing, roadside vegetation clearance, and vehicle speed restrictions might be devised to minimize the adverse impacts of road infrastructure on local animal populations.

Effects of passing rates on driving behaviour in variable speed limit-controlled highways: Evidence of external pressure from a driving simulator study

Variable message signs on motorways can show dynamically changing speed limits for traffic safety or efficiency reasons. While the effects of variable speed limits have been studied in the literature, the effect of (drivers in) vehicles operating under different speed limit information − caused by transitioning from one speed limit to another − has received relatively little attention. During such a transition, drivers can either be overtaken by vehicles operating under a higher speed limit, or conversely, drivers overtake slower vehicles operating under a lower speed limit. In both scenarios, opposite forms of external pressure are expected to be exerted by the surrounding traffic. Sixty-seven participants performed three randomised drives (201 drives in total), each reflecting one of three different passing rates scenarios, i.e., the number of vehicles overtaking the driver, or vice versa, caused by a speed limit change. Passing rates varied from as low as 90 veh/h to as high as 360 veh/h. Increasing passing rates act as a proxy for increasing levels of external pressure applied to drivers. Statistical analyses are conducted using a Linear Mixed Model (LMM) and a Generalised Estimating Equations (GEE) approach, accounting for correlation caused by the panel nature of the data. The LMM indicates that the driving behaviour indicators are indeed affected under different passing rates and that these differences are statistically significant. Results indicate that drivers in higher passing rate scenario(s) tend to accelerate and drive faster compared to the low(er) passing rate scenario(s). Further, the GEE model for speed selection indicates that drivers from different age groups and gender select different speeds in response to the impact of external pressure caused by surrounding traffic. Similarly, the GEE model for speed variation within a driver suggests differential speed variations of age groups and gender under different passing rates. Overall, this study finds pronounced effects directly related to the imposed external pressure via the surrounding traffic, where high passing rates lead to significant speed variations that increase the chances of drivers engaging in safety-critical events.

Two minus one road equals improved quality of life

BackgroundSundbyberg municipality (part of greater Stockholm) has reconstructed a traditional two-lane road, with an allowed speed limit of 30 km/h, into a road with one car lane and two bicycle lanes, one on either side of the car lane (a “two minus one road”). The aim was to increase traffic safety and accessibility, especially for bicyclists and pedestrians MethodThe design used was a before- an after-study including both subjective and objective measures. To collect subjective data a survey measuring quality of life was used by asking residents and travellers how they experienced the road and their neighbourhood. The collection of objective data was done with the help of video cameras recording traffic conflicts, vehicle speed and position on the road ResultsThe reconstruction of the road had positive effects on quality of life in general, specifically safety, security, and accessibility for bicyclists and pedestrians. Something which was achieved without reducing car drivers’ experience of accessibility. Subsequent analyses were conducted to increase the understanding of different ‘sub-groups’. Specifically, analyses assessed: if responses could be linked to modal choice; whether the reconstruction of the road resulted in a modal shift; and whether it was any differences between respondents who had or had not a child attending any of the local schools. Overall, the responses from the ‘sub-groups’ were not significantly different from each other (except for respondents with children). The video analyses on traffic safety showed no differences in conflicts before and after the reconstruction. The only negative result was that car drivers’ speed increased by 3 km/h ConclusionThe reconstruction of roads with a traffic intensity, equivalent to the selected road is suitable for a two minus one road. Traffic safety, security, and accessibility will increase, but not at the expense of car drivers’ accessibility.

Sensorless Control of Surface-Mount Permanent-Magnet Synchronous Motors Based on an Adaptive Super-Twisting Sliding Mode Observer

The Sliding Mode Observer (SMO) is widely used for the sensorless control of Permanent-Magnet Synchronous Motors (PMSMs) due to its simple structure and strong parameter robustness. However, traditional SMOs have a limited speed range and suffer from chattering issues, which affect the accuracy of rotor position estimation. To address these problems, this paper proposes an Adaptive Super-Twisting SMO (AST-SMO) method. First, a fast super-twisting function is designed to resolve the step problem that occurs at the zero-crossing of the traditional sign function. Next, an adaptive-tracking high-order Sliding Mode Observer is constructed to extend the speed range of the SMO. The stability of the system is proven using the Lyapunov theorem. Finally, a sensorless control system for PMSMs is implemented and validated in MATLAB/SIMULINK. The results indicate that, compared to the traditional SMO, the AST-SMO reduces the back EMF THD from 20.03% to 14.2%. Additionally, the rotor estimation error across all speed ranges is less than 0.01. Therefore, AST-SMO offers a higher tracking accuracy, a wider speed range, and effectively suppresses sliding mode chattering and harmonic interference.

Identifying the vehicle accident models based on driving behavior factors using structural equation modeling

The increase in population is accompanied by an increase in the number of vehicles. It is inevitable that the number of vehicle accidents will also increase, which can be caused by various factors. Driver factors reviewed in this study include socioeconomic characteristics, movement characteristics, accident characteristics, and driver behavior characteristics. the purpose of this study is to study the vehicle accident model using interviews and Driving Behavior questionnaires with a total of 307 motorist respondents who have experienced accidents. Driver factors reviewed in this study include socioeconomic characteristics, movement characteristics, accident characteristics, and driver behavior characteristics using interviews and Driving Behavior questionnaires with a total of 307 motorist respondents who have experienced accidents. This investigate used SEM (Structural Equation Modeling) with SmartPLS computer software. Two-wheeled vehicle accident modeling results Y=–0.234 X1+0.153 X3+ei2; R2=0.102. The greatest influence occurs in the characteristics of driver behavior (X3), namely Ordinary Violation, and for four-wheeled vehicle accident modeling results, Y=–0.343 X1+0.284 X3+ei2; R2=0.217. The greatest influence occurs in driver behavior characteristics (X3), namely Ordinary Violation. Ordinary Violation is defined as a deliberate deviation from the rule of law. Thus, from the research results, the most influential variable was the behavior of drivers who committed ordinary violations such as ignoring speed limits, breaking through intersections, and driving under the influence of alcohol. So, there needs to be collaboration between the police and related parties in tackling accidents and reducing the risk of traffic accidents, such as long as socialization or information through newspapers or electronic media to the public in Jayapura City regarding the importance of collective awareness of driving safety

METHOD FOR CREATING SVM CLASSIFIER FOR DATA ANALYSIS ON FPGA

The paper explores the use of SVM classifier method for data analysis on FPGA, which, despite its effectiveness, may face challenges related to limited resources and data processing speed. In this context, there is a need to develop new methods for integrating SVM classifiers with high-performance computing hardware. The increasing demand for speed and energy efficiency requires new approaches to implementing machine learning methods. One of the key tools for data classification and analysis is the Support Vector Machine (SVM), widely used in business, science, medicine, and many other fields. Developing an efficient and optimized method for creating SVM classifiers for FPGA requires further research and development, as existing methods may be suboptimal in terms of speed and FPGA resource utilization. The article provides an overview of known hardware solutions to this problem, proposed in the current scientific literature. Additionally, the effectiveness of combining hardware and software components to achieve significant acceleration of the data analysis process is discussed. The article emphasizes the need for further research and improvement to fully realize the transformative potential of machine learning classification methods.

Vehicle Classification and Counting for Traffic Analysis based on Single-stage YOLOv8 Model

Intelligent traffic systems are emerging and becoming part of smart city infrastructure that requires computer vision applications to provide traffic information like vehicle classification and counting in real-time. Vehicle counting helps detect heavy traffic on roads, and vehicle classification helps enforce further processes like speed estimation to enforce speed limit laws based on the vehicle class. Deep learning computer vision-based systems provide automatic feature extractions that are robust to changes in lighting, shadows, and occlusions. This paper proposes a software solution for a real-time traffic monitoring system based on a cutting-edge single-stage deep learning model through the state-of-the-art YOLOv8 algorithm. YOLOv8 is the most recent model of the YOLO family, which provides object detection and classification through its CNN architecture. The proposed work detects vehicles and counts them based on their class. The four common vehicle classes are sedan cars, buses, trucks, and motorcycles, and a counter for each class is displayed on the system’s output screen in real-time and recorded in a log file. The results of the proposed system running on the Nvidia GTX 1070 GPU show an average accuracy of 96.58% with an average error of 3.42% for vehicle detection and an average accuracy of 97.54% with a 2.46% average error for vehicle counting. For vehicle classification, the results for the four vehicle classes (car, bus, truck, and motorcycle) show an accuracy of (94.7%, 94.7%, 96.2%, 99.7%), precision (95%, 100%, 81.4%, 100%), recall (97.9%, 36.3%, 100%, 66.6%), and the f1-score (96.3%, 53.2%, 89.7%, 79.9%), respectively. Index Terms— Computer Vision, Deep Learning, Vehicle Detection, Traffic Analysis, YOLO.

Analysis of the Relationship between Speed Consistency and Traffic Accident Probability (on the Mojokerto-Surabaya Toll Road)

Vehicle speed consistency plays a crucial role in maintaining traffic safety, with speed limits set to reduce accident fatalities. While the direct impact of speed limits on vehicle speed is minimal, their implementation significantly influences driver behavior, with about 85% of drivers complying with speed limits. However, variables such as traffic volume, weather conditions, and travel urgency often cause drivers to be inconsistent in adhering to these limits, increasing accident risk. On the Mojokerto-Surabaya toll road, data from IRSMS Korlantas Polri and Jasa Marga recorded 193 accidents with 101 fatalities from 2018 to August 2023, mostly caused by driver behavior such as excessive speed. This study analyzes the relationship between speed consistency and accident probability on this road, highlighting accident issues due to speed violations and inconsistency at ramp off/on locations. Results show the importance of toll road infrastructure considering vehicle volume, identifying accident blackspots, and implementing urgent speed management as key factors in improving safety on the Surabaya-Mojokerto toll road. The findings emphasize the need for better traffic management and speed regulation to reduce fatal accident risks.

Unpacking the perceived cycling safety of road environment using street view imagery and cycle accident data

Cycling, as a routine mode of travel, offers significant benefits in promoting health, eliminating emissions, and alleviating traffic congestion. Many cities, including London, have introduced various policies and measures to promote ’active travel’ in view of its manifold advantages. Nevertheless, the reality is not as desirable as expected. Existing studies suggest that cyclists’ perceptions of cycling safety significantly hinder the broader adoption of cycling. Our study investigates the perceived cycling safety and unpacks the association between the cycling safety level and the road environment, taking London as a case study. First, we proposed novel cycling safety level indicators that incorporate both collision and injury risks, based on which a tri-tiered cycling safety level prediction spanning the entirety of London’s road network has been generated with good accuracy. Second, we assessed the road environment by harnessing imagery features of street view reflecting the cyclist’s perception of space and combined it with road features of cycle accident sites. Finally, associations between road environment features and cycling safety levels have been explained using SHAP values, leading to tailored policy recommendations. Our research has identified several key factors that contribute to a risky environment for cycling. Among these, the “second road effects,” which refers to roads intersecting with the road where the accident occurred, is the most critical to cycling safety levels. This would also support and further contribute to the literature on road safety. Other results related to road greenery, speed limits, etc, are also discussed in detail. In summary, our study offers insights into urban design and transport planning, emphasising the perceived cycling safety of road environment.

Evaluating the effectiveness of brief anti-speeding messages disseminated within warning notices to driving offenders

Road safety messaging represents a long-standing strategy in efforts to reduce speeding, a behaviour which accounts for an estimated 30 % of all road crashes on Australian roads. This study aimed to further examine the effectiveness of such a strategy via the use of a novel message medium that included anti-speeding messaging disseminated to speeding offenders via warning notices issued by a Start Government Transport agency. Informed by the Step approach to Message Design and Testing (SatMDT), survey content was devised to compare the effectiveness of the messages across various outcome measures including intentions to stay within the posted speed limit. A total of 219 speeding offenders completed the online survey. Overall, the results found some positive responses regarding Intervention condition participants’ responses to the anti-speeding messaging featured within the warning notices. Among some of the key findings were that the Intervention condition participants reported relatively low levels of message rejection. Additionally, females responded more favourably to both messages than males. Collectively, the findings suggest that there is no harm in including such messages within warning notices providing such messages are concept-tested prior to use. Overall, the findings suggest this approach may represent a low-cost option for targeted message delivery.

A portable Eu-MOF-loaded paper-based probe integrated with smartphone for the visual and on-site detection of Cr2O72− in aqueous media

The high toxicity of dichromate anion (Cr2O72−) its accurate necessitates its sensitive and effective detection to safeguard human health. The study introduces a Eu-MOF fluorescent probe, named as Eu-TDCA, synthesized using 2,5-thiophenedicarboxylic acid (H2TDCA) as a bridging ligand for the detection of Cr2O72− in aqueous media. The probe suspension can detect Cr2O72− through fluorescence quenching, and the detection process exhibits a wide linear range (0–85 and 85–230 mg/L), low limit of detection (LOD, 5.1 μg/L) and rapid response speed (2 min). Furthermore, a portable Eu-TDCA-loaded paper-based probe, integrated with a smartphone color recognition app, was developed for the visual, sensitive and quantitative detection of Cr2O72− in real lake and river water samples, achieving satisfactory recoveries of 99.72%–103.75 %. Additionally, an advanced logic gate device was designed to simplify the detection process, providing a new direction for intelligent on-line detection of analytes.

Classification of autonomous vehicle crash severity: Solving the problems of imbalanced datasets and small sample size

Only a few researchers have shown how environmental factors and road features relate to Autonomous Vehicle (AV) crash severity levels, and none have focused on the data limitation problems, such as small sample sizes, imbalanced datasets, and high dimensional features. To address these problems, we analyzed an AV crash dataset (2019 to 2021) from the California Department of Motor Vehicles (CA DMV), which included 266 collision reports (51 of those causing injuries). We included external environmental variables by collecting various points of interest (POIs) and roadway features from Open Street Map (OSM) and Data San Francisco (SF). Random Over-Sampling Examples (ROSE) and the Synthetic Minority Over-Sampling Technique (SMOTE) methods were used to balance the dataset and increase the sample size. These two balancing methods were used to expand the dataset and solve the small sample size problem simultaneously. Mutual information, random forest, and XGboost were utilized to address the high dimensional feature and the selection problem caused by including a variety of types of POIs as predictive variables. Because existing studies do not use consistent procedures, we compared the effectiveness of using the feature-selection preprocessing method as the first process to employing the data-balance technique as the first process.Our results showed that AV crash severity levels are related to vehicle manufacturers, vehicle damage level, collision type, vehicle movement, the parties involved in the crash, speed limit, and some types of POIs (areas near transportation, entertainment venues, public places, schools, and medical facilities). Both resampling methods and three data preprocessing methods improved model performance, and the model that used SMOTE and data-balancing first was the best. The results suggest that over-sampling and the feature selection method can improve model prediction performance and define new factors related to AV crash severity levels.

Competition of decoherence and quantum speed limits for quantum-gate fidelity in the Jaynes-Cummings model

Quantum computers are operated by external driving fields, such as lasers, microwaves, or transmission lines, that execute logical operations on multiqubit registers, leaving the system in a pure state. However, the drive and the logical system might become correlated in such a way that, after tracing out the degrees of freedom of the driving field, the output state will not be pure. Previous works have pointed out that the resulting error scales inversely with the energy of the drive, thus imposing a limit on the energy efficiency of quantum computing. In this study, focusing on the Jaynes-Cummings model, we show how the same scaling can be seen as a consequence of two competing phenomena: the entanglement-induced error, which grows with time, and a minimal time for computation imposed by quantum speed limits. This evidence is made possible by quantifying, at any time, the computation error via the spectral radius associated with the density operator of the logical qubit. Moreover, we also prove that, in order to attain a given target state at a chosen fidelity, it is energetically more efficient to perform a single driven evolution of the logical qubits rather than to split the computation in subroutines, each operated by a dedicated pulse. Published by the American Physical Society 2024

Design and Test of a Crawler-Type On-Film Precision Cotton Seeding Device on DEM-CFD

To solve the limitation of speed in the operation of air-suction cotton precision seeding devices, a new crawler-type precision on-film seeding device was designed using an extended duckbill hole-forming device to produce hole-forming belts and lateral seed collection. Coupling simulation of seeding, and analysis of drag force and movement speed of cotton seeds were conducted on EDEM-CFD. A mechanical model of the operation was established, and the effects of the suction hole diameter, pressure relief block length, and wind pressure on seeding performance were analyzed. Regression models between influencing factors and seeding performance indices were established using response surface methodology. The test data were analyzed using Design Expert 10.0.3. The influence rules for each factor on seeding performance were established. The factors affecting the seeding qualified index exhibited the following order: air pressure > pressure relief block length > suction hole diameter. The optimization goals included defining the maximum value of a qualified single-seed index and the minimum value of the missing index, and the best parameter combination was obtained based on a suction hole diameter of 3.624 mm, pressure relief block length of 63.369 mm, and wind pressure of 3.797 kPa. According to the actual test conditions, the parameters were revised to include a suction hole diameter of 3.6 mm, a relief block length of 63.4 mm, and wind (air) pressure of 3.8 kPa for verification tests. The actual qualified single-seed index is 94.87% ± 0.98 %, the missing index is 1.45% ± 0.32%, and the multiple index is 3.68% ± 0.62%. The difference from the predicted value is within 5%, indicating that this study can provide a reference for the structural design and optimization of crawler-type on-film precision cotton seeding devices.

Speed limits in traffic emission models using multi-objective optimization

AbstractClimate change compels a reduction of greenhouse gas emissions, yet vehicular traffic still contributes significantly to the emission of air pollutants. Hence, in this paper we focus on the optimization of traffic flow while simultaneously minimizing air pollution using speed limits as controllable parameters. We introduce a framework of traffic emission models to simulate the traffic dynamic as well as the production and spread of air pollutants. We formulate a multi-objective optimization problem for the optimization of multiple aspects of vehicular traffic. The results show that multi-objective optimization can be a valuable tool in traffic emission modeling as it allows to find optimal compromises between ecological and economic objectives.

Electric scooter-associated orthopedic injuries cause long absence from work, regret and are emerging as a major cause of hip fractures in young individuals: a comprehensive study from a regional trauma center in a densely populated urban setting

This study aimed to give a full spectrum of orthopedic injuries associated with electric scooter (e-scooter) use and analyze related factors, report on follow-up data from the patient's perspective and make a comparative etiological analysis of young adult hip fractures. A total of 851 consecutive patients were admitted to the Emergency Department following e‑scooter injuries between January 2021 and July 2022, of whom 188 had 214 orthopedic injuries. The demographics, injury, and incident characteristics of these patients were collected. All fractures were classified as per the AO/OTA classification. Two groups were created as operatively or conservatively treated patients and data were comparatively analyzed. Follow-up examination incorporated a survey using binary questions on patients' perspectives. An etiological comparative analysis of hip fractures in young adults admitted to the same center between 2016 and 2022 was conducted. The median patient age was 25. Inexperienced drivers constituted 32% of the injured. The protective gear use rate was at 3%. Higher speed (p = 0.014) and age (p = 0.011) were significantly associated with operative treatment. A total of 39% of the operated patients could not return to preinjury physical function, while 74% regretted using an e‑scooter. The most common etiological factor for traumatic young hip fractures was fall from a height between 2016 and 2020, whereas it became e‑scooter accidents in 2021-2022. The rate of e‑scooter-related operative treatment is high and leaves the patient in regret (84%) and a physically limited condition (39%). A speed limit of ≤ 15 km/h could decrease the rate of operative injuries. The e‑scooter was identified as the top etiological factor in the last 2 years for traumatic young hip fractures. II, Diagnostic cohort study.

Optimal hybrid strategy in adaptive cruise control system for enhanced autonomous vehicle stability and safety

The adaptive cruise control system relies heavily on the vehicle's longitudinal control algorithm. Traditional longitudinal control algorithms typically depend on precise vehicle dynamic modeling or complex controller parameter calibrations. In the research, an optimal hybrid strategy for the control of basic adaptive cruise control system is proposed. The proposed hybrid strategy is the combination of both the Model Predictive Control (MPC) and Coati Optimization Algorithm (COA) and hence it is named as MPCCOA strategy. The fundamental goal of the proposed work is that a vehicle should maintain its current velocity when it approaches another vehicle that is driving at a steady velocity. The inputs for the proposed strategy are vehicle speed and acceleration. The inter-vehicle distance error, velocity error and acceleration are regulated based on the upper and lower limit of acceleration command with the help of proposed strategy. For accomplishing the required steadiness with the limitations in the given input and actual velocity with constant previous vehicle velocity, the proposed controller is utilized. The proposed controller is used to control the traction force of the host vehicle such that the vehicle speed follows the optimal speed trajectory as good as possible while ensuring constraints like distance to a preceding vehicle or speed limits. The performance of the proposed is implemented in the MATLAB platform and compared with existing approaches. The proposed technique demonstrates superior performance metrics, achieving the collision rate, rate of reaching maximum deceleration and ratio of exceeding comfortable deceleration or jerk are 1.27 %, 3.131 % and 9.052 %, respectively.