Car Drivers Research Articles

Improving attitudes towards vulnerable road users

Some car drivers pass vulnerable road users (VRUs) at too high a speed and leave too little gap. Research suggests that out-group bias and a lack of empathy may relate to these dangerous incidents. To address this problem, four road safety videos were created with the aim of increasing car drivers’ empathy toward Vulnerable Road Users (VRUs). Each video focused on the back-story of a VRU (two horse riders and two cyclists), with a predominantly persuasive approach to inducing empathy and reducing out-group bias. The effectiveness of the videos on car drivers’ immediate implicit and explicit attitudes, and on their future intended behaviour around these VRUs, was assessed by comparing intervention participants’ responses with those of control participants, both before and after the intervention. Explicit attitudes towards horse riders improved following the intervention for drivers who saw the horse rider videos compared to a control group. The horse rider videos did not however improve explicit attitudes toward cyclists. Similarly, those participants who saw the cyclist videos showed improved attitudes towards cyclists but not horse riders. An Implicit Attitude Test (IAT) found no implicit biases for or against horse riders or cyclists, either before or after the intervention. Intended future passing behaviour was affected by the intervention however, with car drivers reporting greater intended passing distances and lower passing speeds compared to the control group. The results suggest that safety campaigns that adopt this approach can change attitudes and intended behaviours towards VRUs.

What is the market potential for on-demand services as a train station access mode?

On-demand mobility services (FLEX) are often proposed as a solution for the first/last mile problem. We study the potential of using FLEX to improve train station access by means of a three-step sequential stated preference survey. We compare FLEX with the bicycle, car and public transport for accessing two alternative train stations. We estimate a joint access mode and train station choice model. Estimating a latent class choice model with different nesting structures, we uncover four distinct segments in the population. Two segments (∼50%) with a lower Willingness-to-Pay seem to be more likely to take-up FLEX. Ex-urban car drivers seem to be the most likely segment to adopt FLEX, showing great, since members of this segment are currently frequent users of the private car. Our case study also shows that while FLEX competes primarily with public transport when accessing local stations, it competes primarily with car for reaching distant stations.

Finding alternatives for the traditional diesel-powered company car: A conjoint analysis approach

Although the use of company cars is associated with more congestion, pollution and accidents compared to privately owned cars, the Belgian fiscal system provides exceptionally high incentives to company cars. As a result, the proportion of company cars is higher in Belgium than in any other OECD country. With a corporate mobility budget, more sustainable options are being offered as an alternative to large diesel-powered company cars, but little is known about how company car drivers value these alternatives. In this article, we explore how car-dependent employees make their choices in the company mobility system and aim to find options that enable more sustainable commuting. A choice-based conjoint analysis carried out among 422 car dependent company car drivers was used to measure their preference for alternative car-based solutions. The results indicate an overall preference for hybrid cars, but a shift toward fully electric vehicles is necessary to have a significant impact on climate change. Our results suggest that respondents with a higher environmental concern are more eager to make the transition toward smaller and fully electric vehicles, which is in line with previous studies. The study revealed that there is currently no alternative that is both more sustainable and more preferred by the sample, which again stresses the need for more drastic government intervention.

How Do Vehicles Make Decisions during Implementation Period of Discretionary Lane Change? A Data-Driven Research

To investigate and compare the lane changing behavior of passenger cars and heavy vehicles during the implementation period (defined as the interval from the start time to the end time of a lane change maneuver), this study applies the gradient boosting decision tree (GBDT) method to model the lane changing behavior of heavy vehicles and passenger cars, respectively. Results show that the lane change models vary with the vehicle types and lane change directions. Different factors are considered by the drivers of passenger cars and heavy vehicles when implementing lane changes to different directions. Partial dependence plots of GBDT models reveal that the influence of independent variables on lane changing behavior is nonlinear and complicated, which means that the same variable leads to various effects on the lane change decision across different vehicle types and lane change directions. In contrast with other state-of-the-art methods, the proposed method can obtain more accurate results. The findings indicate that it is necessary to build specific lane change models based on vehicle types and lane change directions for microscopic traffic simulators and autonomous vehicles.

Research Regarding Different Types of Headlights on Selected Passenger Vehicles when Using Sensor-Related Equipment.

Statistical surveys show that the majority of traffic accidents occur due to low visibility, highlighting the need to delve into innovative car lighting technologies. A car driver must not only be able to see but also to be seen. The issue of headlight illumination is vital, especially during the dark hours of the night. Therefore, the focus of this article is determining the range of visibility of dipped (low-beam) headlights under specific experimental conditions. We also designed a methodical guideline aimed at identifying the distance at which dipped headlights illuminate the road while a vehicle is in motion. Research conducted on various classes of road confirmed that the Hyundai i40 is best used on higher-class roads, while the Dacia Sandero is better used on lower-class roads due to the shape and spreading out of its light cone. Furthermore, the pros and cons of the distribution of light cones on several classes of road are presented. Sensor-related equipment was also used to investigate light beam afterglow. In particular, an LX-1108 light meter was applied to determine the obstacle illumination intensity, the properties of which enable recording of low lighting values, and a DJI Mavic AIR 2 unmanned aerial vehicle (UAV; drone) was utilized to record the data related to the location of the examined vehicle, as well as light afterglow at night; relevant data evaluation was carried out using Inkscape software.

Insights into peer-to-peer carsharing: Modelling and scenario analysis via a Bass diffusion agent-based model

Our paper aims at estimating the uptake of peer-to-peer carsharing (P2PCS) in less-densely populated areas and how it could be influenced by innovation, social interaction and transport policies. We specified a Bass Diffusion agent-based model including two modules representing the supply and demand of P2PCS. Both modules are parametrized with data derived from a discrete choice survey of potential users (N = 449) representative of the population living in Friuli-Venezia Giulia, an Italian region bordering with Austria and Slovenia. We specified the rental rate as a dynamic variable that varies according to the excess of demand or supply. Innovation and imitation effects change the status of car owners and car drivers into potential P2PCS users. According to our simulations the P2PCS market would reach a steady state at a rental rate of 6.1 €/h with 7% of car owners and car renters engaging in the system. We also found that if the preferences for the servitization paradigm were more diffused, P2PCS would be used by 11% of the population at a rental rate of 5.5 €/h, and that adopting a package of highly effective policies supporting both the demand and the supply would increase the market share up to 42%.

How to Cross the Chasm for the Electric Vehicle World’s Laggards—A Case Study in Kuwait

Ever since the discovery of oil in 1938, the State of Kuwait has increasingly sought out international brands in the car market due to the high purchasing power of Kuwaiti nationals. However, the makers of electric vehicles (EVs) have not been able to penetrate this market, with the exception of innovators and early adopters. The phenomenon in disruptive innovation theory—called “Crossing the Chasm”—regarding a mass market appeal has not yet occurred in Kuwait. Through deep interviews with 12 Kuwaiti owners of EVs and automotive dealers who sold either EVs or Hybrid Electric Vehicles (HEVs), 10 key reasons for this phenomenon have been previously revealed, which were used to develop an extensive questionnaire. A total of 472 car drivers aged from 18 to 30, identified as the “early majority”, completed the questionnaire to achieve the objective of identifying the factors required to create a mass market for EVs in Kuwait. The results demonstrated that potential customers highly preferred three different types of attributes of EVs: environmental, financial, and technological. There were significant differences in the identified attributes preferred by Kuwaiti individuals for EVs in terms of the number of cars owned and the sector of employment. Moreover, the results of our study indicate that potential customers are very willing to buy EVs in the future, considering both their financial and infrastructure attributes. There were further significant differences in the identified necessary conditions to buy EVs in terms of educational level and monthly income. This study discusses a variety of valuable promotional tactics, which may be implemented in conjunction with public incentives and policy changes in the State of Kuwait. This information is considered useful for marketers and designers who wish to tap into this lucrative market, which is significantly different from that in the global North.

The influence of helmets on sound localisation in motorcyclists

Motorcyclists are among the most vulnerable road users globally, they enjoy less protection than car drivers and experience higher speed collisions than cyclists, with less mobility and spatial awareness to avoid crashes. Sound localisation (SL) while wearing military and ski helmets has been a significant area of research to improve spatial awareness, but no research has been completed thus far on the impact of motorcycle helmets on SL. This project aims to examine experimentally the impact of a motorcycle helmet on the Head Related Impulse Response (HRIR), and therefore determine the extent of the impact on SL ability of a user. A database of HRIRs as a function of position in the horizontal place was established with and without a motorcycle helmet. The variation in the signals was evaluated, and it was found that the helmet results in significant loss of higher frequencies, important for resolving front-back confusions. It is also demonstrated that the overall sound attenuation would result in reduced SL ability of the rider. A novel system to compensate for the changes in the HRIR was developed and experimentally tested to mitigate the impact on SL ability for the wearer.

Aplikasi Simulasi Berkendara dengan Metode Fuzzy Logic Menggunakan Phonegap

Android-Based Car Driving Simulation Application is an application used to obtain information about driving and caring for a car using smartphone support media. This is based on the increase in car accidents from year to year. The lack of information and the lack of knowledge of car drivers about driving information has made the author make a Car Driving Simulation application for the needs of visitors in using and accessing this application. Remembering technology is like a gadget that is no longer difficult to obtain, in fact it is possible for all people to have it. The application is designed with a smartphone that uses the Android operating system. Applications are made based on information needs for motorists. This application has gone through the stages of testing on four Android smartphone devices. This application is made using Phonegap with HTML and CSS programming languages and runs on the Kitkat version of the Android operating system as a minimum requirement.

Correlated random parameters model with heterogeneity in means for analysis of factors affecting the perceived value of road accidents and travel time

Road safety funding and management have become important issues in improving the quality of life of road users and there is evidence of a difference in driving behavior and the factor of road use between urban and rural areas, which is, in turn, reflected in different road safety evaluations. The purpose of this study is to assess the financial losses caused by road accidents on Thailand’s highways and the related factors empirically, deploying the willingness-to-pay (WTP) approach. Data were obtained from 640 urban and 960 rural car drivers using a stated choice questionnaire and face-to-face interviews. This study used Correlated Random Parameters Binary Logit with Heterogeneity in Means (CRPBLHM) approach to analyze factors affecting WTP. According to the results, the value of a statistical life and injury for urban drivers was 1.63 times higher than that for rural drivers, and the value of travel time reduction per hour for urban drivers is ∼1.14 times higher than that found for rural drivers. Furthermore, the results of the CRPBLHM model reported that there are significant differences between urban and rural drivers’ safety intentions and WTP. In the urban model, it was found that driving behavior (ticket, seatbelts, and speed) and weekday trips significantly increase the WTP, whereas household size and gender are unobserved characteristics among drivers. The rural model revealed that a driver’s education (bachelor’s and master’s degrees held), and a necessary trip were significantly associated with drivers’ valuation of safety; moreover, it was found that household size, sole earner status, own accident, in possession of a doctoral degree, and being young were significant in acting as unobserved characteristics. The results demonstrated differences in the value of road safety and unobserved heterogeneity among drivers, which influence risk perception and valuation with reference to the area context. Relevant agencies can use the results as a guideline for budget allocation and practical policy-related road safety management.

Analysis of Charging Infrastructure for Private, Battery Electric Passenger Cars: Optimizing Spatial Distribution Using a Genetic Algorithm

To enable the deployment of battery electric vehicles (BEVs) as passenger cars in the private transport sector, suitable charging infrastructure is crucial. In this paper, a methodology for the efficient spatial distribution of charging infrastructure is evaluated by investigating a scenario with a 100% market penetration of BEVs of (around 1.3 million vehicles) in Berlin, Germany. The goal of the evaluated methodology is the development of various charging infrastructure scenarios—including public and private charging—which are suitable to cover the entire charging demand. Therefore, these scenarios are investigated in detail with a focus on the number of public charging points, their spatial distributions, the available charging power, and the necessary capital costs. For the creation of these charging infrastructure scenarios, a placement model is developed. As input, it uses the data of a multi-agent transport simulation (MATSim) scenario of the metropolitan area of Berlin to evaluate and optimize different distributions of charging infrastructure. The model uses a genetic algorithm and the principle of multi-objective optimization. The capital costs of the charging points and the mean detour car drivers must undertake are used as the optimization criteria. Using these criteria, we expect to generate cost-efficient infrastructure solutions that provide high usability at the same time. The main advantage of the method selected is that multiple optimal solutions with different characteristics can be found, and suitable solutions can be selected by subsequently using other criteria. Besides the generated charging scenarios for Berlin, the main goal of this paper is to provide a valid methodology, which is able to use the output data of an agent-based, microscopic transport simulation of an arbitrary city or area (or even real driving data) and calculate different suitable charging infrastructure scenarios regarding the different optimization criteria. This paper shows a possible application of this method and provides suggestions to improve the significance of the results in future works. The optimized charging infrastructure solutions for the Berlin scenario show capital costs of between EUR 624 and 2950 million. Users must cover an additional mean detour of 254 m to 590 m per charging process to reach an available charging point. According to the results, a suitable ratio between the charging points and vehicles is between 11:1 and 5:1. A share of fast charging infrastructure (>50 kW) of less than ten percent seems to be sufficient if it is situated at the main traffic routes and highly frequented places.

Detection of object throwing behavior in surveillance videos

Anomalous behavior detection is a challenging research area within computer vision. One such behavior is throwing action in traffic flow, which is one of the unique requirements of our Smart City project to enhance public safety. This paper proposes a solution for throwing action detection in surveillance videos using deep learning. At present, datasets for throwing actions are not publicly available. To address the use-case of our Smart City project, we first generate the novel public 'Throwing Action' dataset, consisting of 271 videos of throwing actions performed by traffic participants, such as pedestrians, bicyclists, and car drivers, and 130 normal videos without throwing actions. Second, we compare the performance of different feature extractors for our anomaly detection method on the UCF-Crime and Throwing-Action datasets. Finally, we improve the performance of the anomaly detection algorithm by applying the Adam optimizer instead of Adadelta, and we propose a mean normal loss function that yields better anomaly detection performance. The experimental results reach an area under the ROC curve of 86.10 for the Throwing-Action dataset, and 80.13 on the combined UCF-Crime+Throwing dataset, respectively.

PERUBAHAN PENDAPATAN MASYARAKAT DESA JIKO INDUK KECAMATAN MOTONGKAD, BOLAANG MONGONDOW TIMUR PADA MASA PANDEMI COVID 19 (Changes In Income of The Jiko Induk Village Communities Motongkad District, Bolaang Mongondow East during The Pandemic Covid 19)

East Bolaang Mongondow is one of the areas that has begun to develop the tourism sector apart from agriculture, animal husbandry, services, mining and others. The tourism sector which was developed about three years ago before the outbreak of Covid 19, especially in Jiko Induk Village was the Abadi Beach, Tanjung Silar Beach and Cimoki Beach tourism. This has had the impact of decreasing tourist visits to Jiko Induk Village, which has resulted in decreased income for the people of Jiko Induk Village who work in the tourism sector. aims to describe changes in the condition of people's income in Jiko Induk Village both for people who work as farmers and fishermen as well as service sellers at tourist destinations Cimoki Beach, Abadi Beach and Tanjung Silar, namely by category before becoming a tourist destination, when it became a tourist destination and during the Covid 19 Pandemic.
 The research result showed that the category of changes in livelihood during the Covid 19 Pandemic illustrates that 13 respondents who have the profession of part-time workers, namely as fishermen and sellers of boat motorcycle taxi services, with a percentage of 43.33%, and people who have jobs as car driver renters, builders, yellow rice sellers and BRI Link Agents each had 1 respondent with a percentage of 3.33%. Thus the category of changes in the livelihoods of the Jiko Induk Village community experienced a significant change in livelihood when it became a tourist destination by opening new jobs for the Jiko Induk Village community.

SMALL ROAD MONITORING SYSTEM FOR FOUR WHEEL VEHICLES

The application of the vehicle regulation system at intersections in rural areas does not yet have a good regulatory system compared to the vehicle control system in urban areas. The lack of equitable distribution of road widening in rural areas makes people often have problems accessing roads when using four-wheeled vehicles. People often experience problems when accessing small roads, especially when more than one vehicle passes at the same time. This problem was also experienced in DesaTanjung Sari, Kecamatan Cijeruk, Kabupaten Bogor. This study aims to design and build a small road monitoring system so that car drivers get a warning if there are four-wheeled vehicles that have passed the small road. The object recognition method used in the small road monitoring system for four-wheeled vehicles is the HC-SR04 ultrasonic sensor which is placed on the left, right, and top sides. Arduino Uno R3 microcontroller will be used as the main system device. The communication between points used is LoRa Ra-02 as the sender and receiver. The results of this study show the results of the system prototype running well in accordance with the planned functions.

Thermal comfort analysis of auto-racing suits using a dynamic thermal manikin

Motorsports athletes compete at high speeds for, on average, three to four hours in a cockpit that can reach temperatures of 50°C. While engineers have worked to create a faster car and safer conditions, the comfort of the driver is often sacrificed. Motorsports governing bodies require that a driver’s racing suit meet at least one of several certification levels for thermal protection. While much research and testing go into certification, there continues to be a lack of information in the body of research regarding the impact of the racing suit on thermal comfort and heat stress. Therefore, the purpose of this research was to determine the impact of auto-racing personal protective clothing on the thermal comfort of race car drivers by utilizing a thermal manikin to observe the thermal insulation, evaporative resistance, and total heat loss (THL) of standard racing suits. Racing suit systems of varying SFI Foundation, Inc. (SFI) certification levels were purchased and analyzed using an ANDI sweating thermal manikin in an environmental chamber. Results from this research demonstrate that the average predicted THL for an SFI compliant racing ensemble is 172 W/m2. Findings indicate it is more beneficial for thermal comfort to wear a lower rated suit with base layers as opposed to a higher rated suit without undergarments. More research must be done to better understand how the predicted THL for racing ensembles effects the human body when performing under race day conditions, and to determine a minimum THL benchmark for racing ensembles.

Impact Attenuator Design for Improvement of Racing Car Drivers’ Safety

An essential element for driver safety is represented by the Impact Attenuator (especially for race cars). The effect of the Impact Attenuator can be seen in the behavior of a dummy, tied with a seat belt, in a frontal collision with a rigid wall. The loads that act on the dummy are determined and checked to see if they fall within the values recommended by existing standards. The car is considered a structure with a dummy fixed with a seat belt and equipped with an Impact Attenuator. Two types of Impact Attenuator having constructive similarity and symmetries are studied, made up of three different materials and different thicknesses of material. The behavior of the dummy was studied, considering a frontal collision of the car–dummy assembly, in accordance with existing standards. Using simulation software, the accelerations were determined at various points on the mannequin’s body and the force appearing on the seat belts was determined. The Gibbs–Appell equations are the method used to determine the dynamic response in this problem involving shocks.

Detecting Driver Sleepiness using Convolutional Neural Networks

The development in computer vision has aided drivers in the form of automatic self-driving cars etc. The accidents are caused by driver's exhaustion and drowsiness about 20%. Its carriages a dangerous issue for which numerous methods were proposed. However, they are not appropriate for real-time implementation. The major encounters confronted by these approaches are forcefulness to handle dissimilarity in human face and lightning conditions. Our intention is to implement a smart operating system that can lower the rate of road accidents considerably. This method enables us to find driver's face features like eye closure percentage, eye-mouth aspect ratios, blink rate, yawning, head movement, etc. In this classification, the driver is uninterruptedly observed by using a webcam. The car driver’s facial features along with the eye movements are observed using a cascade classifier. Eye images are pull out and fed to Custom designed Convolutional Neural Network for categorizing whether both left and right eye are closed. Based on the sorting, the eye closure score is considered. Upon finding that the driver is being detected drowsy that a high alarm will be raised.

Prevalence of Neck Pain in Car and Motorcycle Drivers: A Comprehensive Review of Primary, Secondary, and Tertiary Care

Car and motorcycle drivers frequently experience neck pain, which may have an impact on their quality of life and productivity at work. Understanding the prevalence of neck pain in this population and identifying effective interventions was essential for developing targeted healthcare strategies. The purpose of this review was to determine the prevalence of neck pain among car and motorcycle drivers and assess the effectiveness of primary, secondary, and tertiary care interventions in managing and preventing this health issue. A comprehensive literature search was conducted to gather relevant studies on neck pain prevalence and interventions among drivers. The collected data was analysed and synthesised to provide an in-depth understanding of the issue. The result of this review reveals a significant prevalence of neck pain among car and motorcycle drivers, highlighting the need for targeted interventions. Primary, secondary, and tertiary care strategies are essential in addressing neck pain in this population. Primary care interventions focus on preventing the onset of neck pain, while secondary care aims to manage existing symptoms and prevent their worsening. Tertiary care interventions involve rehabilitation and long-term management of chronic neck pain. The present review concluded that a multi-faceted approach, encompassing primary, secondary, and tertiary care interventions, is necessary to prevent and manage neck pain in drivers. However, the current evidence base has limitations, and further research is required to enhance our understanding of effective interventions for this population.

Effectiveness of real-time and post-trip interventions from the H2020 i-DREAMS naturalistic driving project: A Sneak Preview

This paper addresses the effectiveness of real-time and post-trip interventions from the H2020 i-DREAMS naturalistic driving project. The project aims to setup a framework for the definition, development and validation of a context-aware ‘safety tolerance zone (STZ)’ for driving. A range of sensors are used to collect a large variety of data, which enables assessment of the STZ, and help designing interventions. Effectiveness evaluation is based on the outcome and process evaluation using the COM-B and RE-AIM frameworks, respectively. Preliminary results for a sample of 27 car drivers from Belgium and 26 car drivers from UK are presented. Overall, the interventions were found effective in improving driving behaviour. UK drivers have performed significantly better, while Belgian car drivers showed mixed results, mainly due to the changing mobility patterns during COVID19 pandemic.

Quantitative indicators of street lighting with mood, fatigue, mental workload and sleepiness in car drivers: Using generalized structural equation modeling

Inadequate lighting will be associated with some degree of perceptual error such as sleepiness. The main purpose of this study was to investigate the interactions between mood, fatigue, mental workload, and sleepiness and their relationship with quantitative indicators of street lighting in passenger car drivers. The present study was a cross-sectional study that was performed on 270 drivers of passenger cars. The quantitative indices of lighting studied were illuminance, luminance, uniformity, and disability glare which were calculated using the Hagner device (EC1-L) and according to EN 13201 standard. Alertness and mood indices, fatigue scale (SAMN-PERELLI), mental workload (NASA-TLX), positive and negative affect schedule (PANAS) were used. Generalized structural equation modeling (GSEM) was used to investigate the relationship between mood, fatigue, mental workload, and drivers' sleepiness. Data analysis was performed in version 26 of SPSS software and version 14 of Stata software There is a significant relationship between illuminance and mood (P < 0.001). There is a significant relationship between the degree of disability glare on the streets and the mood (P = 0.006). There is a significant relationship between fatigue score and mood (P < 0.001) so that with increasing one unit in fatigue scale, mood score decreases by 0.669 units (P < 0.001). Finally, it can be assured that lighting interventions can be done as an effective way to increase alertness and reduce fatigue and the mental workload of drivers with the aim of reducing night traffic accidents.