Influences of Mixed Traffic Flow and Time Pressure on Mistake-Prone Driving Behaviors among Bus Drivers

Bus safety is a matter of great importance in many developing countries, with driving behaviors among bus drivers identified as a primary factor contributing to accidents. This concern is particularly amplified in mixed traffic flow (MTF) environments with time pressure (TP). However, there is a lack of sufficient research exploring the relationships among these factors. This study consists of two papers that aim to investigate the impact of MTF environments with TP on the driving behaviors of bus drivers. While the first paper focuses on violated driving behaviors, this particular paper delves into mistake-prone driving behaviors (MDB). To collect data on MDB, as well as perceptions of MTF and TP, a questionnaire survey was implemented among bus drivers. Factor analyses were employed to create new measurements for validating MDB in MTF environments. The study utilized partial correlation and linear regression analyses with the Bayesian Model Averaging (BMA) method to explore the relationships between MDB and MTF/TP. The results revealed a modified scale for MDB. Two MTF factors and two TP factors were found to be significantly associated with MDB. A high presence of motorcycles and dangerous interactions among vehicles were not found to be associated with MDB among bus drivers. However, bus drivers who perceived motorcyclists as aggressive, considered road users’ traffic habits as unsafe, and perceived bus routes’ punctuality and organization as very strict were more likely to exhibit MDB. Moreover, the results from the three MDB predictive models demonstrated a positive impact of bus route organization on MDB among bus drivers. The study also examined various relationships between the socio-demographic characteristics of bus drivers and MDB. These findings are of practical significance in developing interventions aimed at reducing MDB among bus drivers operating in MTF environments with TP.

Potential Application of iRap for Road Safety Assessment under Mixed Traffic Condition Case Study: Le Van Viet Street in Ho Chi Minh City

Road transport safety policies have emphasized road infrastructure safety design and engineering as a core function.However,in developing countries like Vietnam,this approach has been slower to adopt,resulting in substandard roads.In-depth studies of accident locations indicate that road environment factors contribute significantly to road accidents in Vietnam and road design features are associated with specific accident types and hazards.Proactive and reactive approaches,such as road safety audit,inspection,assessment,and treatment of hazardous locations,are necessary to ensure that the road and its environment are safe.This paper provides an overview of road safety in Vietnam in general,and Ho Chi Minh in particular,including its factors and characteristics,as well as road infrastructure safety improvements.The iRap tool for road safety inspection and assessment is highlighted as a potential method for systematically analyzing road infrastructure deficiencies and providing targeted countermeasures to improve road safety under mixed traffic conditions.

Interaction-Aware Cut-In Trajectory Prediction and Risk Assessment in Mixed Traffic

Accurately predicting the trajectories of surrounding vehicles and assessing the collision risks are essential to avoid side and rear-end collisions caused by cut-in.To improve the safety of autonomous vehicles in the mixed traffic,this study proposes a cut-in prediction and risk assessment method with considering the interactions of multiple traffic participants.The integration of the support vector machine and Gaussian mixture model(SVM-GMM)is developed to simultaneously predict cut-in behavior and trajectory.The dimension of the input features is reduced through Chebyshev fitting to improve the training efficiency as well as the online inference performance.Based on the predicted trajectory of the cut-in vehicle and the responsive actions of the autonomous vehicles,two risk measurements are introduced to formulate the comprehensive interaction risk through the combination of Sigmoid function and Softmax function.Finally,the comparative analysis is performed to validate the proposed method using the naturalistic driving data.The results show that the proposed method can predict the trajectory with higher precision and effectively evaluate the risk level of a cut-in maneuver compared to the methods without considering interaction.

Mathematical Modeling,Field Calibration and Numerical Simulation of Low-Speed Mixed Traffic Flow in Cities

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Characteristics of synchronized traffic in mixed traffic flow

In this paper, the characteristics of synchronized traffic in mixed traffic flow are investigated based on the braking light model. By introducing the energy dissipation and the distribution of slowdown vehicles, the effects of the maximum velocity, the mixing ratio, and the length of vehicles on the synchronized flow are discussed. It is found that the maximum velocity plays a great role in the synchronized flow in mixed traffic. The energy dissipation and the distribution of slowdown vehicles in the synchronized flow region are greatly different from those in free flow and a traffic jamming region. When all of vehicles have the same maximum velocity with Vmax 〉 15, the mixed traffic significantly displays synchronized flow, which has been demonstrated by the relation between flow rate and occupancy and estimation of the cross-correlation function. Moreover, the energy dissipation in the synchronized flow region does not increase with occupancy. The distribution of slowdown vehicles shows a changeless platform in the synchronized flow region. This is an interesting phenomenon. It helps to deeply understand the synchronized flow and greatly reduce the energy dissipation of traffic flow.

Analysis of occupation time of vehicles at urban unsignalized intersections in non-lane-based mixed traffic conditions

In India, traffic flow on roads is highly mixed in nature with wide variations in the static and dynamic characteristics of vehicles. At unsignalized intersections, vehicles generally do not follow lane discipline and ignore the rules of priority. Drivers generally become more aggressive and tend to cross the uncontrolled intersections without considering the conflicting traffic. All these conditions cause a very complex traffic situation at unsignal- ized intersections which have a great impact on the capacity and performance of traffic intersections. A new method called additive conflict flow （ACF） method is suitable to determine the capacity of unsignalized inter- sections in non-lane-based mixed traffic conditions as prevailing in India. Occupation time is the key parameter for ACF method, which is defined as the time spent by a vehicle in the conflict area at the intersection. Data for this study were collected at two three-legged unsignalized intersections （one is uncontrolled and other one is semi- controlled） in Mangalore city, India using video-graphic technique during peak periods on three consecutive week days. The occupation time of vehicles at these intersections were studied and compared. The data on conflicting traffic volume and occupation time by each subject vehicle at the conflict area were extracted from the videos using image processing software. The subject vehicles were divided into three categories： two wheelers,cars, and auto-rickshaws. Mathematical relationships were developed to relate the occupation time of different cate- gories of vehicles with the conflicting flow of vehicles for various movements at both the intersections. It was found that occupation time increases with the increasing con- flicting traffic and observed to be higher at the uncontrolled intersection compared to the semicontrolled intersec- tion. The segregated turning movements and the presence of mini roundabout at the semicontrolled intersection reduces the conflicts of vehicular movements, which ulti- mately reduces the occupation time. The proposed methodology will be useful to determine the occupation time for various movements at unsignalized intersections. The models developed in the study can be used by practitioners and traffic engineers to estimate the capacity of unsignalized intersections in non-lane-based discipline and mixed traffic conditions.

Simulation of High-Level Way Toll System under the Condition of Mixed Traffic Flow

Parking-toll on main-line is one of toll models on high-level ways in our country at present. This paper analyzes the flow's distributing function, queuing model, and vehicle passing time. Through computer simulation, the negative index relationships between carrying capacity and serving time, and the index relationships between the queuing delay and flow are gained under the condition of different serving time and different vehicle type composition. When the flow density is low, the vehicle type composing has less influence on system serving level. Contrarily, also. Disposing toll station by roadway where flow density is high, we can save transection areas of toll station, reduce system queuing delay time, and enhance carrying capacity of toll station.

Gap acceptance behavior of drivers at uncontrolled T-intersections under mixed traffic conditions

Explicit traffic control measures are absent in uncontrolled intersections which make them susceptible to frequent conflicts and resulting collisions between vehicles. In developing countries like India, drivers at such intersections do not yield to higher priority movements which cause more crashes between vehicles. The objective of this study is to analyze and model the gap acceptance behavior of minor street drivers at uncontrolled T-intersections considering their aggressive nature. Three intersections in the northeast region of India have been selected as the case study area. Preliminary analysis of the data revealed that drivers behave aggressively, not because they have to wait for a long time at the stop line, but because of their lack of respect for traffic rules. Binary logit models are developed for minor road right turning vehicles which show that gap acceptance behavior is influenced by gap duration, clearing time and aggressive nature of drivers. The equations obtained were used to estimate the critical gaps for aggressive and non-aggressive drivers. Critical gaps are also calculated using an existing method called clearing behavior approach. It is also shown that the estimation of critical gap is more realistic if clearing time and aggressive behavior of drivers are considered.

Effects of Driver Response Time Under Take‑Over Control Based on CAR‑ToC Model in Human–Machine Mixed Traffic Flow

The take-over control(ToC)of human–machine interaction is a hotspot.From automatic driving to manual driving,some factors affecting driver response time have not been considered in existing models,and little attention has been paid to its effects on mixed traffic flow.This study establishes a ToC model of response based on adaptive control of thought-rational cognitive architecture(CAR-ToC)to investigate the effects of driver response time on traffic flow.A quantification method of driver’s situation cognition uncertainty is also proposed.This method can directly describe the cognitive effect of drivers with different cognitive characteristics on vehicle cluster situations.The results show that when driver response time in ToC is 4.2 s,the traffic state is the best.The greater the response time is,the more obvious the stop-and-go waves exhibit.Besides,crashes happen when manual vehicles hit other types of vehicles in ToC.Effects of driver response time on traffic are illustrated and verified from various aspects.Experiments are designed to verify that road efficiency and safety are increased by using a dynamic take-over strategy.Further,internal causes of effects are revealed and suggestions are discussed for the safety and efficiency of autonomous vehicles.

Overtaking behaviour of vehicles on undivided roads in non-lane based mixed traffic conditions

Traffic on Indian roads is highly mixed in nature with wide variations in the static and dynamic characteristics of vehicles. These vehicles do not follow strict lane discipline and occupy any available lateral position on the road space. Overtaking is one of the most complex and important manoeuvre on undivided roads where the vehicles use the opposing lane to overtake the slower vehicles with the presence of oncoming vehicles from opposite direction. They are unavoidable especially in the case of mixed traffic conditions where there is always a speed difference between the fast and slow moving vehicles. Overtaking process involves lane-changing manoeuvres, acceleration and deceleration actions and estimation of relative speed of overtaking and overtaken vehicles, and also, estimation of speed and distance of the oncoming vehicle. The main objective of the present study is to study the overtaking characteristics of vehicles on undivided roads under mixed traffic conditions. For this purpose, details of overtaking data were collected on a two-lane two-way undivided road using moving car observer method and registration plate method. The overtaking characteristics of all types of vehicles under mixed traffic conditions were observed and mathematically modelled. The data extracted and analysed were the acceleration characteristics, speeds of the overtaking vehicles, overtaking time, overtaking distances, safe opposing gap required for overtaking, flow rates, overtaking frequencies, types of overtaking strategy, and types of overtaking and overtaken vehicles. Two types of overtaking strategies were observed in the field such as flying overtaking and accelerative overtaking. Graphs were plotted between the relative speed of the overtaking and overtaken vehicles against the overtaking time and negative correlation was found between the speed differential and total overtaking time for all categories of vehicles. It was observed that the number of overtaking increases with increase in the flow rate in the on-going direction and decreases with increase in flow in the opposite direction, The results obtained from this study will be useful to understand the overtaking behaviour of vehicles in mixed and non-lane discipline traffic conditions. These parameters will be useful in the development of traffic simulations models for undivided roads and thereby for estimation of capacity. The findings from the study can also be used to estimate potential collision times which will be helpful to improve the road safety.

Operational characteristics of mixed traffic flow under bi-directional environment using cellular automaton

Mixed traffic flow composed of autos and non-autos widely exists in developing countries and areas. To investigate the operational characteristics of the mixed traffic flow consisting of vehicles in different types （large vehicles, cars, and bicycles）, we develop a cellular automaton model to repli- cate the travel behaviors on a bi-directional road segment with respect to the physical and mechanic features of different vehicle types. By implementing the essential parameters calibrated through the field data collection, a numerical study is carried out considering the variation in volume, density, and velocity with different compositions of mixed traffic flows. The primary findings include： the average ve- locity of traffic flow and total volume decrease 60% and 30% after incorporating 10% bicycles, respectively; the phenomenon of double-summit in terms bicycle is beyond 60 % ; the maximal total volume higher than 10 %. of the total volume appears when the proportion of starts to recover when the proportion of bicycle is

Modeling Mixed Traffic Flow at Crosswalks in Micro-Simulations Using Cellular Automata

The cellular automata （CA） micro-simulation model was used to describe the behavior of the mixed traffic flows at crosswalks where the pedestrians compete with the vehicles to cross the roadway. The focus of this paper is the behavior of pedestrians and the influence of pedestrians＇ behavior on the vehicle flow, pedestrian flows, and the vehicle waiting time. The proportion of pedestrians who do not obey traffic laws, the group effect, and expected waiting time of pedestrians, regarded as the most important pedestrian characteristics, are taken into consideration in the analysis. Simulation results show the ability of the microsimulation to capture the most important features of mixed traffic flow.

Analyzing driver's response to yellow indication subjected to dilemma incursion under mixed traffic condition

Under mixed traffic conditions prevailing on Indian roads,drivers show complex response when faced with yellow signal because lane assignment gets dynamic in nature.The present study analyzes the effect of surrounding vehicles on response of the drivers while facing dilemma at intersections.Although dilemma zone definitions hold true in case of homogeneous traffic mix,a statistical analysis is performed to check the consistency across the definitions under mixed traffic condition.Present study shows a significant difference in percentage of red light running in comparison to homogeneous traffic as reported by various studies.For carrying out the research,study locations are chosen in such a way to reflect diversity in road geometry,traffic composition and signal characteristics.The results deduced in this study indicate a strong correlation between the driver's decision making choice and the effect of presence of surrounding vehicle at the onset of yellow signal.The effect of critical time analysis has been found out to be one of the parameters other than critical distance in categorizing driver's aggressiveness while facing the yellow signal.In the process of identifying the statistical significance of dilemma zone definitions,it has been found that under heterogeneous traffic condition,drivers behave differently as compared to homogenous traffic when it comes to dilemma zone.It is observed that the percentage of vehicles crossing the intersection when faced with dilemma by violating the red light is 11.6%according to dilemma zone definition I whereas the definition II has yielded about 10.8%violation covering different vehicle types.The above violation figures derived based on the above definition is somewhat higher as compared to homogeneous traffic condition which is observed to be of the order of 5%-6%.

Capacity Reliability of Signalized Intersections with Mixed Traffic Conditions

The reliability of capacity of signalized intersections in mixed traffic conditions involving vehicles, bicycles, and pedestrians was investigated to complete the conventional, deterministic capacity calculations. Simulations using VISSIM provided estimates of capacity distributions, and demonstrated the effects of the analysis intervals on the distributions. With the random vehicle arrivals taken into account, a capacity reliability assessment method was given as a function. Assessments were also performed regarding the effects of the conflicting pedestrian and bicycle volumes on capacity reliability. The simulation indicates that the pedestrians and bicycles result in greater random fluctuations of exclusive turning lane capacities, but have less effect on the variability of shared lane capacities. Normal distributions can be used to model the capacities for intervals not less than 10 rain. At higher vehicular volumes, the capacity reliability is more sensitive to the mean and standard deviation of the pedestrian and bicycle volumes.

Multi-agent reinforcement learning for cooperative lane changing of connected and autonomous vehicles in mixed traffic

Autonomous driving has attracted significant research interests in the past two decades as it offers many potential benefits,including releasing drivers from exhausting driving and mitigating traffic congestion,among others.Despite promising progress,lane-changing remains a great challenge for autonomous vehicles(AV),especially in mixed and dynamic traffic scenarios.Recently,reinforcement learning(RL)has been widely explored for lane-changing decision makings in AVs with encouraging results demonstrated.However,the majority of those studies are focused on a single-vehicle setting,and lane-changing in the context of multiple AVs coexisting with human-driven vehicles(HDVs)have received scarce attention.In this paper,we formulate the lane-changing decision-making of multiple AVs in a mixed-traffic highway environment as a multi-agent reinforcement learning(MARL)problem,where each AV makes lane-changing decisions based on the motions of both neighboring AVs and HDVs.Specifically,a multi-agent advantage actor-critic(MA2C)method is proposed with a novel local reward design and a parameter sharing scheme.In particular,a multi-objective reward function is designed to incorporate fuel efficiency,driving comfort,and the safety of autonomous driving.A comprehensive experimental study is made that our proposed MARL framework consistently outperforms several state-of-the-art benchmarks in terms of efficiency,safety,and driver comfort.

Safety of motorised two wheelers in mixed traffic conditions:Literature review of risk factors

The ownership of motorised two wheelers(MTWs)has been on the rise across various countries across the globe.The growth has been especially higher in developing countries which have typical traffic characteristics and higher populations.This steady rise has resulted in increased accident and fatalities.This abrupt increase warranted attention from the researchers to carry out specific studies for MTWs,which have a very different behaviour as compared to cars in terms of physical and dynamic parameters.Moreover,the unique traffic patterns usually found in the developing countries pose an additional challenge to the researchers,since the conventional focus of transportation safety researchers was a homogeneous car-based traffic.Many such studies have been attempted,especially in the recent decades,which have considered various risk factors related to MTW safety.However,the studies have considered different sets of risk factors and have given surprising and even conflicting results.Therefore,a comprehensive review of the diverse studies needs to be carried out which incorporates all the risk factors considered in previous research.This study reviews such research papers which have analysed various risk factors related to safety of MTWs,especially in heterogeneous,non-lane based traffic.Specifically,this paper aims to incorporate results from those studies and highlight the conclusions from state of the art.The paper also discusses about the research gaps that are crucial for MTW safety in mixed traffic conditions.The review will be useful for researchers working in the field of MTW safety and for policy implementation and analysis.

Bicycle Conversion Factor Calibration at Two-Phase Intersections in Mixed Traffic Flows

Chinese traffic is typically composed of bicycles and motor vehicles on the same road. The efficiency of bicycle traffic in time and space at intersections was investigated for eight typical intersections in the cities of Tianjin, Shenyang, and Changchun, all in China, by means of video recording. Models were developed to calculate the through bicycle traffic and the left-turn bicycle traffic conversion factors in intersections where bicycles and motor vehicles share the same road. The results indicate that the through bicycle conversion factor is 0.28 and the left-turn bicycle conversion factor is 0.33. This conclusion differs from the current value used in China. More research on the conversion factor is necessary to evaluate the impact of intersections.

Capacity of Multi- vehicle- types Mixed Traffic Flow

：Based on the gap acceptance theory, the mixed traffic flow composed of r representative typesflows on the unsignalized intersection is set up. It is an extension of capacity model for one type vehicletraffic flow, and it is very fitter to the Chinese highway traffic condition than the other models.

Modelling behavioural interactions of drivers' in mixed traffic conditions

Mixed traffic conditions are often prevalent in developing economies such as India, China, Bangladesh, etc. and are characterised by the presence of multiple vehicle types. The presence of multiple vehicle types with varying dynamic and static characteristics results in vehicle-type dependent driving behaviours. For instance, drivers of small sized vehicles such as motorbikes accelerate and decelerate at will, maintain shorter safe gaps with the lead vehicles, and accept smaller lateral clearances to make lateral movements within and across lanes breaking the lane discipline. On the other hand, drivers of heavy vehicles such as trucks have less flexibility in performing the acceleration/deceleration and lateral movement operations. Thus, the representation of mixed traffic systems requires model- ling vehicle-type dependent driving behaviours. This paper first establishes the effect of vehicle type on the longitudinal and lateral movement behaviours of drivers using the trajectory data collected in India and subsequently presents the proposed vehicle-type dependent driver behavioural models based on the same dataset. The efficiency of the proposed models is tested by implementing them in a simulation framework compatible with non-lane-based movements of vehicles and cross validating with the field data. The results indicate better predictability of the driver behaviour and thus more realistic rep- resentation in the mixed traffic systems. Moreover, the simulator hinged upon the pro- posed behavioural models will be useful in evaluating alternate traffic improvement initiatives and help the transport planners to design the transport systems of developing countries in an efficient and sustainable manner.

Impact of connected and autonomous vehicles on traffic safety of mixed traffic flow:from the perspective of connectivity and spatial distribution

Equipped with high driving automation and advanced communication technologies, connected and autonomous vehicles (CAV) areexpected to possess a shorter reaction time and a wider vision,which are promising to improve traffic safety and efficiency. However,little attention has been paid to the effect of connectivity and spatial distribution on the safety performance of mixed traffic flow. Inthis paper, we attempt to investigate the impact of CAV on traffic safety considering these factors. To this end, a car-following modelfor CAV is proposed first. Then, the cooperative driving strategy for CAVs is designed. Precisely, the feedback gains of the informationare adjusted in real-time and are designed based on the derived stability criterion of the mixed traffic flow. Microscopic simulations ofmixed traffic flow in traffic oscillation are designed and conducted to explore how the distribution and connectivity of CAV affect thesafety performance ofmixed traffic flow. Simulation results show that increasing the penetration rate of CAV is promising to shift thesafety performance ofmixed traffic flow. In addition, the safety performance of mixed traffic flow is related to the spatial distributionand communication range of CAV. Besides, increasing communication range does not inevitably improve the safety performance ofmixed traffic flow when the penetration rate of CAV is low. Moreover, it is also found from the spatial–temporal trajectory of themixedtraffic flow that introducing CAV can mitigate the propagation of the stop-and-go wave and increase the throughput.