Increasing Vehicle Speed Research Articles

Efficient Nonlinear Model Predictive Path Tracking Control for Autonomous Vehicle: Investigating the Effects of Vehicle Dynamics Stiffness

Motion control is one of the three core modules of autonomous driving, and nonlinear model predictive control (NMPC) has recently attracted widespread attention in the field of motion control. Vehicle dynamics equations, as a widely used model, have a significant impact on the solution efficiency of NMPC due to their stiffness. This paper first theoretically analyzes the limitations on the discretized time step caused by the stiffness of the vehicle dynamics model equations when using existing common numerical methods to solve NMPC, thereby revealing the reasons for the low computational efficiency of NMPC. Then, an A-stable controller based on the finite element orthogonal collocation method is proposed, which greatly expands the stable domain range of the numerical solution process of NMPC, thus achieving the purpose of relaxing the discretized time step restrictions and improving the real-time performance of NMPC. Finally, through CarSim 8.0/Simulink 2021a co-simulation, it is verified that the vehicle dynamics model equations are with great stiffness when the vehicle speed is low, and the proposed controller can enhance the real-time performance of NMPC. As the vehicle speed increases, the stiffness of the vehicle dynamics model equation decreases. In addition to the superior capability in addressing the integration stability issues arising from the stiffness nature of the vehicle dynamics equations, the proposed NMPC controller also demonstrates higher accuracy across a broad range of vehicle speeds.

Dynamic Response Analysis of Asphalt Pavement under Pavement-Unevenness Excitation

This paper investigates and analyzes the dynamic response of asphalt pavement under pavement-unevenness excitation based on an orthogonal vector function system and efficient DVP (dual variable and position) method. Firstly, starting from the pavement unevenness of the vehicle excitation source, the pavement-unevenness excitation is established by using the filtered white-noise method, and the random load of the vehicle model is obtained by simulation. Then, based on the basic governing equation of the road-surface problem under the random load, the analytical solution of the road-surface mechanical response is obtained by using the orthogonal vector function system and DVP method. The effects of pavement-unevenness grade, vehicle speed, vehicle load, interlayer contact condition, and transverse isotropy on the mechanical response of the road surface are analyzed via the analytical results. The results show that DVP can effectively solve the dynamic response of pavements under the excitation of pavement unevenness; in addition, it can also be applied to certain situations, such as transverse isotropy of materials and interface conditions. The results show that the pavement unevenness does not affect the average stress and strain of each layer but has a significant effect on the peak value and dispersion degree. An increase in vehicle speed causes a peak in strain and a larger coefficient of variation. Poor bonding between interfaces can lead to increased stress and strain at the bottom of the surface layer.

Correlation between Muscular Activity and Vehicle Motion during Double Lane Change Driving.

The aim of this study was to compare the correlation between electromyography (EMG) activity and vehicle motion during double lane change driving. This study measured five vehicle motions: the steering wheel angle, steering wheel torque, lateral acceleration, roll angle, and yaw velocity. The EMG activity for 19 muscles and vehicle motions was applied for envelope detection. There was a significantly high positive correlation between muscles (mean correlation coefficient) for sternocleidomastoid (0.62) and biceps brachii (0.71) and vehicle motions for steering wheel angle, steering wheel torque, lateral acceleration, and yaw velocity, but a negative correlation between the muscles for middle deltoid (-0.75) and triceps brachii long head (-0.78) and these vehicle motions. The ANOVA test was used to analyze statistically significant differences in the main and interaction effects of muscle and vehicle speed. The mean absolute correlation coefficient exhibited an increasing trend with the increasing vehicle speed for the muscles (increasing rate%): upper trapezius (30.5%), pectoralis major sternal (38.7%), serratus anterior (13.3%), and biceps brachii (11.0%). The mean absolute correlation coefficient showed a decreasing trend with increasing vehicle speed for the masseter (-9.6%), sternocleidomastoid (-12.9%), middle deltoid (-5.5%), posterior deltoid (-20.0%), pectoralis major clavicular (-13.4%), and triceps brachii long head (-6.3%). The sternocleidomastoid muscle may decrease with increasing vehicle speed as the neck rotation decreases. As shoulder stabilizers, the upper trapezius, pectoralis major sternal, and serratus anterior muscles are considered to play a primary role in maintaining body balance. This study suggests that the primary muscles reflecting vehicle motions include the sternocleidomastoid, deltoid, upper trapezius, pectoralis major sternal, serratus anterior, biceps, and triceps muscles under real driving conditions.

Track vertical irregularity estimation for railway bridges using a novel and lightweight deep-learning architecture

A comprehensive methodology is presented for the estimation of track vertical irregularities of railway bridges from vehicle responses, based on a novel and lightweight multi-layer-perceptron (MLP) deep learning architecture. Firstly, a vehicle–track–bridge interaction (VTBI) model is established for the generation of the datasets of deep learning networks. Secondly, the lightweight deep learning architecture is meticulously designed to identify the track's vertical irregularities. Then, the effectiveness of the proposed technique is validated through examples of a single-span simple bridge and a three-span bridge. Further, the sensitivity of the present method against various factors is investigated, including different combinations of vehicle responses, measurement noise, vehicle speed and different classes of track irregularity. It is confirmed that the identified track irregularities of the railway bridges, regardless of irregularity class and noise level, are in excellent agreement with the ground-truth ones. The increase in vehicle speed to some extent reduces the estimation accuracy of the irregularity. The proposed method has higher identification accuracy and efficiency for longer irregularity sequences of multi-span railway bridges.

Estimation of soot refractive index from its nanostructural parameters with the dispersion model

Particles derived from combustion processes, mainly composed of soot agglomerates, are acknowledged to be among the main contributors to climate change. Their effects depend mostly on their size, shape, and internal structure. Specifically, the latter has a significant effect on their optical properties, mainly through the refractive index. This index has been widely evaluated, but scarcely correlated with the soot internal characteristics. In this work, relationships between the nanostructural parameters (such as the degree of graphitization, among others) obtained with conventional analytical techniques and the input parameters of the dispersion model (a representation of the electromagnetic radiation through the Lorentz-Drude approach) are proposed with the aim to determine the refractive index. From experiments in a chassis dynamometer, it has been observed that as the vehicle speed increases, the soot samples have, in general, higher degree of graphitization, due to increased combustion temperature. The method proposed allows quantifying how both the real and imaginary parts of the complex refractive index increase as the degree of graphitization increases. Much lower dependence on the average crystal length has been observed. Different combinations of techniques can be used to determine the nanostructural parameters, depending on the analytical technique used. As far as the resulting parameters are reliable, the effect of the technique selected is minor, thus providing flexibility to the application of the method.

Modeling drivers’ dilemma at unsignalized T-intersections under mixed traffic conditions: A case study from India

Objective At unsignalized T-intersections, right turning drivers from major or minor roads have to accept or reject the available gap and cross the intersection. Poor judgment may arise risk of collision with the major road conflicting vehicles. Subject drivers intending to cross the intersection encounter wide range of gaps. Drivers accept large gaps and reject small gaps. However, drivers experience dilemma over a wide range of gaps. This study aims to examine dilemma experienced by the right turning drivers by modeling gap acceptance and rejection decisions for estimating dilemma zone boundaries on major road. Methods Videographic method was considered for collecting traffic movement data at unsignalized T-intersections. Traffic video data was collected at three specific unsignalized T-intersections with varying degree of channelization. After this, accepted and rejected gaps with different traffic characteristics of offending vehicles (subject drivers) and conflicting vehicles such as speed, distance, vehicle type, etc. for right turning movements were extracted from the video data to analyze gap acceptance and rejection decisions of the drivers and estimate dilemma zone boundaries. Results Gap decisions (acceptance or rejection) were modeled using Generalized Linear Model (GLM) as a function of conflicting vehicle type, speed, and distance from the intersection along with degree of channelization for major and minor roads. The results showed that gap rejection probability increased with increment in conflicting vehicle’s speed and decrement in conflicting vehicle’s distance from the intersection. Dilemma zone boundaries were obtained using developed GLM models by estimating the conflicting vehicle distance from the intersection for 90% and 10% gap rejection probabilities. Dilemma zone boundaries were observed to shift farther from the intersection with increase in vehicle speed and vehicle size. The analysis revealed that subject drivers experienced more dilemma while accepting a gap from major road as compared to minor road. Conclusions This study showed that channelization plays a major role in mitigating dilemma of the subject drivers. Overall, the study identified dilemma zone boundaries for unsignalized T-intersections which may assist the right turning subject drivers to cross the intersection safely.

Analysis of structural dynamic response of vertical sound barriers under natural wind and vehicle induced pulsating wind effects

Abstract Aiming at the influence of natural wind and vehicle-induced pulsating wind on vertical sound barriers, a finite element plug-in panel sound barrier is established based on the finite element method for dynamic response analysis. This paper establishes a sound barrier finite element analysis model based on finite element analysis software. It takes the 8-span vertical sound barrier as the basic working condition to analyze the dynamic response analysis of the sound barrier structure under the action of natural wind of different grades, i.e., the influence of pressure and displacement; the dynamic response of the sound barrier structure with a natural wind speed of 7 grades or more. In addition, it analyzes the dynamic properties of the sound barrier structure caused by train-induced pulsating wind pressure at speeds of more than 200 km/h, i.e., the influence of pressure and displacement, and investigates the dynamic characteristics of different vehicles with different wind speeds, pressure, and displacement. Furthermore, the response of the vertical sound barrier at different vehicle speeds is also explored, and the results are compared to examine its dynamic response. The research findings show that the sound barrier structure does not resonate during the self-resonance analysis, but the vibration of adjacent sound barrier panels affects each other. As natural wind speeds increase, the displacement of the steel column endpoints of the vertical sound barrier gradually increases; along the length of the sound barrier, the change of the peak pressure at the top of the steel columns and the top of the unit plate shows a symmetrical trend, and the displacements of the steel columns and the top of the unit plate show a trend of gradual increase in the travelling direction, and they both increase at the end of the column. The displacement of the top of the steel column and the top of the unit plate both show a trend of gradual increase along the direction of the vehicle, and both reach the maximum value at the end of the steel column and the unit plate. With the increase in vehicle speed, the overall peak displacement value also increases synchronously.

Analysis of wheel-rail contact under oil lubrication conditions

Abstract This investigation centers on the characteristics of the contact between the wheel and rail when lubricated with oil, with a consideration of the impact of surface roughness. Confronting significant challenges related to low adhesion, a thorough examination is undertaken to analyze the changes in film thickness under oil lubrication, investigating trends at varying vehicle speeds and axle loads. Employing detailed modeling based on micro-elastohydrodynamic theory, the distribution of oil film thickness under diverse operational conditions is determined. The findings indicate that, under oil lubrication, a film thickness in the range of several tens of micrometers is established, effectively insulating the surfaces of the wheel and rail, thereby reducing adhesion. With increasing vehicle speed, the thickness of the oil film also rises, whereas an elevation in axle load results in a marginal decrease in film thickness. This research contributes to a comprehensive comprehension of the wheel-rail contact mechanism in oil lubrication scenarios, providing theoretical backing to address concerns related to low adhesion. The implications are substantial for improving the safety and economic efficiency of efficient railway transportation.

Stability prediction method of time-varying real-time hybrid testing system on vehicle-bridge coupled system

In recent years, real-time hybrid testing (RTHT) has been applied for the dynamic testing of high-speed trains running on bridges. A guarantee of stability for the RTHT system is essential to achieve a safe and reliable result. However, the inherent time-varying characteristics of the vehicle-bridge coupled system pose challenges to RTHT stability prediction. This study aims to develop a stability prediction method specifically tailored for time-varying RTHT system. Firstly, the vehicle-bridge coupled RTHT was modelled using a discrete state–space representation with a comprehensive consideration of the time-varying vehicle-bridge interaction and the dynamics of the shaking table. Subsequently, a time-varying stability criterion was derived from the periodic time-varying state matrix, forming the basis for a relative stability prediction method. The validity of the proposed method was confirmed through simulations and experiments employing a single-axle interaction within the vehicle-bridge coupled RTHT system. The coupled system consisted of a quarter-car model and simply supported beams were used as an example to evaluate the stability and accuracy of the time-varying RTHT. The results showed that the stability increased with increasing vehicle speed. Reducing the pure time delay of the shaking table improved both stability and accuracy. Increasing the effective frequency of the shaking table improved the accuracy but may reduce the stability of the RTHT.

Study of Two-Fluid Effects in Weakly Ionized Plasma Under Electromagnetic Fields

The multifluid effects caused by the relative motion and interaction between plasma components have a significant effect on electromagnetohydrodynamic wave propagation and the related mass and energy transport of flows. In this work, the charged particle (ion and electron)–neutral two-fluid model is analyzed and employed to study the two-fluid effects (e.g., velocity drift and thermodynamic nonequilibrium between plasma components) of the weakly ionized plasma flows under the electromagnetic fields. In a hypersonic E×B crossed-field configuration acceleration problem, the increased electromagnetic field strength significantly enhances the two-fluid effects. When the load factor equals 3, which measures the strength of the electrode voltage and induced electromotive force, the relative velocity difference between the charged particles and neutrals can reach 28%. The influences of two-fluid effects appreciably increase with the Mach number and Knudsen number but decrease with the degree of ionization. This suggests that, as the vehicle speed and altitude increase, the two-fluid effects become more significant.

Robust Preview Control for Half‐Vehicle Active Suspension System of Hub‐Driven Electric Vehicles with Coupling Effects

The mechanical‐electrical‐magnetic coupling effects caused by the air gap deformation in in‐wheel motors exacerbate motor magnetic force oscillation, deteriorating the in‐wheel motor operation and ride comfort. In order to enhance vehicle performances, it is imperative to mitigate these coupling effects during the design of hub‐driven electric vehicle suspensions. In this paper, the analytical investigation is conducted on the coupling effects between electromagnetic excitation and transient dynamics in EVs based on the half‐vehicle model. The dynamic responses of hub‐driven EVs considering coupling effects are explored under both open‐loop and closed‐loop systems at various speeds and road conditions. Numerical simulations demonstrate that the closed‐loop system with wheelbase preview robust control exhibits superior comprehensive performance in suppressing coupling effects of the rear wheel hub motor and enhancing ride comfort compared to the system without preview control. Furthermore, as vehicle speed increases, robust preview control effectively reduces fluctuations in pitch angle acceleration, pitch angle, and rear wheel rotor eccentricity. In addition, robust preview control yields better performance in reducing vehicle body centroid acceleration and rear wheel rotor eccentricity and enhancing motor and vehicle performance with increasing road roughness. This work provides a practical vibration model and control reference for studying the dynamic characteristics of hub‐driven EVs.

An experimental methodology to support development of yaw damper prototypes based on a hardware-in-the-loop test bench

Research and development of innovative suspension components for rail vehicles have involved huge investments in recent years. Research efforts have focussed on designing and optimising suspension systems to deal with the new challenges introduced in railway dynamics by the continuous increase in vehicle speed. In particular, yaw dampers have been a relevant research topic due to their influence on vehicle stability. In this context, this paper aims to propose a Hardware-In-the-Loop (HIL) methodology for testing yaw dampers under experimental conditions close to real operating scenarios, comparing the influence of different prototypes on the stability of high-speed rail vehicles. A reduced vehicle model is proposed for real-time integration in HIL tests. This model provides a reference stroke to be imposed on the prototype tested, considering the actual damping force provided by the device being analysed. Two yaw damper prototypes are introduced to validate the proposed methodology by means of comparative analysis at different vehicle speeds. The experimental results provided by the HIL test bench are then compared with corresponding analysis done using Multi-Body (MB) simulations. The proposed HIL methodology has proved to be able to test physical prototypes and define guidelines to assist damper manufacturers developing and optimising yaw damper components.

Social and economic prerequisites and trends in the development of transport innovations

In the context of innovative development of modern economy, innovative ideas in the field of transport, which are indicators of trends in the development of transport systems, are considered. The attention is focused on the current trends of individualisation of vehicles, greening of transport and increasing traffic speeds. The aim of the study is to analyse specific examples of the implementation of these trends. The scientific novelty of the author’s approach refers to the identification of “weak signals” in the analysis of transport innovations, indicating the emergence and development of promising trends.The authors used actual materials devoted to transport innovations, Internet information sources, and scientific literature. Foresight methodology was applied.Examples of innovative developments within the framework of the trends under consideration have been analysed. It is revealed that these trends are often combined with each other within the framework of specific transport vehicles and technologies, which generates synergistic effects important for the transport industry and the economy as a whole.The analysis of transport innovations has shown that individualisation, greening and increasing vehicle speeds have become important conditions for the effective functioning and development of the transport industry. These trends exist both in isolation and in combination with each other. The combination of different trends in one vehicle or technology allows not only to bring the transport industry to a qualitatively higher level, to create new transport systems and products with the necessary consumer characteristics, but also to increase the economic efficiency of transport-related industries and the economy as a whole.

The impact of vehicle parameters on road PM10 vehicle resuspended emissions: A case in South African low-income settlement

About 70% of the roads in low-income settlements are unpaved and close (≤15m) to residents, thus a major source of ambientand indoor PM10 concentrations. International studies have suggested that decreasing vehicle speed and managing vehicle type onpaved or unpaved roads can reduce vehicle dust emissions. These mitigation strategies should be examined before being adoptedand gazetted into South African air quality management plans. This study aimed to characterise roads and traffic, emphasisingdetermining the impact of vehicle type on PM10 emissions. GIS was used to determine the proportion of paved and unpaved roads. Atraffic counter was used to monitor vehicles and to determine traffic composition, diurnal cycles, and average speed per road type.Field campaigns (summer; 6 days; 15 hrs per day) were carried out in Bokamoso to monitor PM10 concentration usinga TSI DustTrak DRX® real-time optical aerosol counter. The Box Model method quantifies vehicle PM10 emission factors for heavy-duty, medium-duty, and motor vehicles. About 0.88 km of road within Bokamoso is paved with a daily traffic volume of >2000, and 3.6 km is unpaved with >250 daily traffic volume. Paved road heavy-duty vehicle non-exhaust PM10 emissions reported a positive medium to strong coefficient of determination to vehicle speed increase with a coefficient of determination of 0.59. Even though there is a positive coefficient of determination between heavy-duty vehicle non-exhaust PM10 emission factors and speed on unpaved roads, it is weak (0.2) due to low and less variable vehicle speed. Motor vehicle paved and unpaved road non-exhaust emission factors showed no significant coefficient of determination with increased vehicle speed. Paved road non-exhaust emission factors were not significantly variable with vehicle type. They ranged between an average of 0.15-0.18 g/km/h, with motor vehicles reporting an average of 0.18 g/km/h while heavy-duty vehicles reported an average of 0.15 g/km/h. On the contrary, unpaved road non-exhaust traffic PM10 emissions ranged between 0.16-0.3 g/km/h. The emission factors presented may be used to model vehicle traffic emissions, improve on-road vehicle dust emissions impact assessment and as a guide when deciding on local applicable road dust mitigation strategies

Insight into jet-regeneration composite cooling technology employed in scramjet: Significance of relative positions of two jet holes

Due to the further increase in hypersonic vehicle speed, the scramjet faces supersonic combustion and aerodynamic heating, and the conventional single cooling method like regenerative cooling has been unable to meet the heat dissipation requirements of scramjet. The composite cooling system has become the hotspot of recent research. Jet cooling has a good cooling effect at high heat flux, so the jet-regeneration composite cooling method is innovatively proposed in this study. Compared with other composite cooling systems, the jet impingement can effectively weaken thermal boundary layer thickness. Initially, the total performance of the jet-regeneration composite cooling was experimentally verified via subcritical air. Furthermore, the numerical simulation of the jet-regeneration composite cooling was also carried out after the validation of turbulence models and mesh independence. Further examples, such as the jet impingement under the effect of the initial mainstream (so-called jet-mainstream) and regenerative cooling (so-called mainstream-only), are used to illustrate the advantages of this composite cooling (so-called jet-only). The heat transfer coefficient of jet-only is 2.6 times larger than that in the case of jet-mainstream. Compared with traditional regenerative cooling, even under the influence of the mainstream, the boundary layer thickness at the stagnation point of the jet impingement can be reduced by 40 times. This work is beneficial to the design of the jet-regeneration composite cooling system.

Knock probability determination employing convolutional neural network and IGTD algorithm

This study presents a novel method based on the convolutional neural network to evaluate knock probability. In this way, lots of data sets are extracted from the real driving conditions of a turbocharged gasoline vehicle. The trained network shows 92 % accuracy in knock detection and 87 % accuracy in normal combustion recognition. This trained network is then used to forecast the knocking probability of the vehicle in different operating conditions. The results revealed that the exhaust gas temperature sensor considerably affects the knock recognition precision by 3 %. Most of the network errors in knock probability determination would be associated with the full load-high speed region and the network errors in normal combustion detection would be related to the low-end torque zone. It is also found that the knock probability decreases with the vehicle's speed increase and its probability at the constant vehicle speed would be higher at low engine rotational speed. This new approach can predict engine knock zones for different vehicle parameters and can be implemented by the engine control unit to suppress knock before happening in an active manner rather than the current passive method.

Effect of polygonal wheel on the vehicle-track dynamic interaction in turnout and its transmission to the trailer bogie wheels

The dynamic interaction between the vehicle and track is strongly influenced by out-of-round wheels and turnout rail profile geometries, which result in high-magnitude contact forces and abnormal vibrations. This study presents the dynamic response of the tram-turnout interaction due to polygonal wheel wear and analyses its transmission between the wheelsets. A three-dimensional coupled tram-turnout dynamic model was formulated, taking into account the polygonal wear on the front bogie wheelsets. Through numerical simulations, the dynamic characteristics of a tram passing through the turnout switch and crossing panels under the influence of polygonal wear were simulated. Furthermore, the impact of polygonal wear amplitudes and tram speeds on the transmission of dynamic impact forces and vibrations from the front bogie wheelset to the trailer bogie wheels are described. According to the numerical findings, when the flexible wheelset experiences polygonal wear, it can lead to substantial impact forces and vibrations as the tram moves through the turnout switch and crossing zones. Moreover, the transmission of dynamic impact forces and vibrations from the front bogie wheelset to the trailer wheels increases as the wheel wear amplitude and the vehicle speed increase.

Sustainable Traffic Regulation System in Protected Areas: Pilot Technology Testing in National Park in the Czech Republic

In the context of nature protection, there is an effort to regulate individual car traffic in protected areas. In the framework of the research, a pilot testing of a vehicle detection and identification system in the Krkonoše National Park was carried out using two selected technologies (license plate recognition and Bluetooth token detection). The research was carried out under conditions of poorer availability of mobile signal for transmission of measured data, lack of electrical power supply, and in challenging climatic conditions in the mountains. The main objective was to verify the applicability and limits of the mentioned technologies under these difficult conditions. For this purpose, two test sites were built: a fixed and a mobile point. Testing at both points was carried out using two basic methods, namely online through continuous data collection from the detectors and on-site through a local survey during the summer of 2022. The parameters evaluated were the reliability of the vehicle identification itself and the reliability of the operation of the individual detection subsystems and the tested system as a whole. The results show that the license plate recognition system using two cameras for the checkpoint shows a high recognition reliability, but it is reduced for some types of vehicles (especially motorcycles and four-wheelers). At the same time, this technology is demanding on energy resources. Detection using a Bluetooth scanner has proven to be highly reliable up to 50 km/h. A reliable power supply is necessary to achieve high reliability, which was a problem at the mobile point. Evaluation of images from cameras with motion detection showed the limits of this technology, which increased with increasing vehicle speed. The system can be used to detect traffic in protected areas, taking into account the limits specified in this article.

Stochastic analysis and dynamic reliability of the heavy-haul train–bridge system based on direct probability integral method

In this paper, a heavy-haul ballasted track–bridge interaction model is established by the finite element method in matrix representations, and their interaction to the train is achieved by the wheel–rail contact. A new direct probability integral method (DPIM) is introduced to achieve the stochastic analysis and reliability assessment of the train-ballasted track–bridge interaction (TTBI) system. Besides, the accuracy of the train-ballasted track–bridge model is validated by the field measurement. The probability characteristics of the dynamic behavior of the system are compared between DPIM and sophisticated PDEM, to show the accuracy and efficiency of the stochastic analysis method. The results demonstrated that the efficiency is improved by 1–2 orders of magnitude in terms of stochastic post-processing. Furthermore, the influences of random factors, e.g., track irregularity, axle loads and bridge parameters, etc., on the dynamic behavior of system are investigated by the proposed method, and the time-dependent reliability is presented with the aid of the extreme distribution events. The results indicate that the train axle load, running speed and variability of parameters have remarkable effects on dynamic performance. Besides, the failure probability of the bridge is very small attribution to the higher allowable threshold (e.g., mid-span displacement), but the safety of train operation decreases with the increase of vehicle speed especially under the critical speed of resonance.

Exploring the Influence of Signal Countdown Timers on Driver Behavior: An Analysis of Pedestrian–Vehicle Conflicts at Signalized Intersections

Although signal countdown timers (SCTs) are likely to enhance efficiency at signalized intersections, there is little research on how they affect road users’ behavior. The present study explores factors associated with driver behavior through two approaches to examine how SCTs influence drivers’ actions toward pedestrians violating red lights. In the first approach, through an on-road questionnaire survey, the self-reported behavior of 369 drivers when crossing an intersection enabled with SCTs was analyzed. In the second approach, the drivers’ behavior was studied through naturalistic driving studies at two signalized intersections equipped with SCTs in Babol, Iran. Analyzing vehicle–pedestrian conflicts indicated that the presence of SCTs had a significant influence on driving behavior. Also, the ending seconds of green lights, as critical times of the SCTs, led to changes in driving behavior. Increasing the vehicle speed, changing lanes, and concurrent increases of speed and changing lanes were the common driver actions affected by critical times of the SCTs. Finally, the effect of critical times on drivers’ actions during conflicts was modeled by using the binary and multinomial logistic methods. The results show that SCTs are an external factor that can lead to risky driver behavior, such as errors and violations that might increase the potential for pedestrian accidents.