Real Traffic Conditions Research Articles

Impact of Roadside Advertising Structures on Traffic Safety

The focus of research presented in this paper is quantification of the relationship between the traffic safety and roadside advertising structures along a selected road in urban environment. In order to determine correlation, statistical analysis of traffic safety indicators was performed. Then identificcation of characteristics of advertising structures and analysis was done by using multi-criteria evaluation in order to determine their impact on driver distraction. Determination of driver distraction was performed by testing the drivers in real traffic conditions, using specialized measuring equipment. The indicators derived from the research were then analyzed using the methods of regression analysis, and safety.

Performance Evaluation of Modified Cyclic Max-Pressure Controlled Intersections in Realistic Corridors

Max-pressure (MP) signal timing is an actuated decentralized signal control policy. Rigorous mathematical studies have proven the stability properties and established the benefits of different MP policies. However, theoretical studies make assumptions about traffic properties that may not represent reality and whose effects are not explored much in the literature under realistic traffic conditions. This study focuses on examining how different variations of MP perform in realistic scenarios and on finding the most practical policy among those for implementation in real roads. Microsimulation models of seven intersections from two corridors, County Road (CR) 30 and CR 109 from Hennepin County, Minnesota were created. Real-life demand and current signal timing data provided by Hennepin County were used to make the simulations as close to reality as possible. In this paper, we compare the performance of current actuated-coordinated signal control with an acyclic MP and two variations of cyclic MP policies. We present the performance of different control policies as delay, throughput, worst lane delay, and number of phase changes. We also present how different parameters affect the performance of the MP policies. We found that better performance can be achieved with a cyclic MP policy by allowing phase skipping when no vehicles are waiting. Our findings also suggest that most of the claimed performance benefits can still be achieved in real-life traffic conditions even with the simplified assumptions made in the theoretical models. In most cases, MP control policies outperformed current signal control.

Structural and Parametric Analysis of the Geometric, Physical and Mechanical Characteristics of the Support Surface

Cross -country ability is the actual problem of modern mechanical engineering. This parameter affects the ability to deliver various goods to hard-to-reach and remote places. Since the cross-country ability of vehicles is largely determined by the technical solutions and parameters implemented in the design, and cannot be significantly improved if necessary for off-road transportation, despite the labor intensity of work on arranging the route almost only for a single passage, it often remains the only available way to align the cross-country ability level with real traffic conditions. The scheme for modeling physical and mechanical characteristics considered in the work has a feature that simplifies the calculations: statistical estimates of the cross-country ability can be carried out on a complex of related to each other in time and space separate states that are not on independent realizations of random functions of the macro-, micro-profile and physical and mechanical properties of the soil.

Ecological aspects of using mixtures of canola oil with n-hexane in diesel engine

The article discusses the results of research on the use of canola oil and canola oil with the addition of n-hexane in a compression-ignition engine. An engine with a Common Rail injection system was tested in real traffic conditions on the road and on a chassis dynamometer. The tested fuels were fed to the engine by an additional fuel supply system. An analysis of the effect of the addition of n-hexane on the emission of the main components of toxic exhaust gases was carried out. The proposed solution may contribute to extending the service life of currently used compression ignition engines due to the improvement of the ecological properties of this type of drive sources.

Energy consumption of a passenger car with a hybrid powertrain in real traffic conditions

The analysis of energy consumption in a hybrid drive system of a passenger car in real road conditions is an important factor determining its operational indicators. The article presents energy consumption analysis of a car equipped with an advanced Plug-in Hybrid Drive System (PHEV), driving in real road conditions on a test section of about 51 km covered in various environmental conditions and seasons. Particular attention was paid to the energy consumption resulting from the cooperation of two independent drive units, analyzed in terms of the total energy expenditure. The energy consumption obtained from fuel and energy collected from the car’s batteries for each run over the total distance of 12,500 km was summarized. The instantaneous values of energy consumption for the hybrid drive per kilometer of distance traveled in car’s real operating conditions range from 0.6 to 1.4 MJ/km, with lower values relating to the vehicle operation only with electric drive. The upper range applies to the internal combustion engine, which increases not only the energy expenditure in the TTW (Tank-to-Wheel) system, but also CO2 emissions to the environment. Based on the experimental data, the curves of total energy consumption per kilometer of the road section traveled were determined, showing a close correlation with the actual operating conditions. Obtained values were compared with homologation data from the WLTP test of the tested passenger car, where the average value of energy demand is 1.1 MJ/km and the CO2 emission is 23 g/km.

Excess Fuel Consumption Due to Selection of a Lower Than Optimal Gear—Case Study Based on Data Obtained in Real Traffic Conditions

Appropriate driving technique, in compliance with eco-driving principles, remains an effective method to reduce fuel consumption. The selection of the correct gear is one of the pertinent factors when driving a car with a manual gearbox. In this study we have analyzed fuel overconsumption based on data recorded in real traffic conditions for vehicles driven by experienced drivers, using a black-box model. It was found that the total share of trip time with a lower than optimal gear selected amounted to from c.a. 3% for motorway driving up to 28% on rural roads. The mean fuel consumption reduction factor (following selection of the next gear up) amounted to from c.a. 2% up to 20%, depending on the selected gear and type of driving. Unfortunately, the potential for reduction of fuel consumption is not evenly distributed over the entire operating area of the engine. Thus, the cumulative reduction of fuel consumption, due to selection of the optimal gear, amounted to from c.a. 0.2% for motorway driving up to 3–6%, for urban and rural driving. It was shown that due to the selection of the appropriate gear, there still exists a real possibility of reduction of fuel consumption, even in the case of experienced drivers.

Research of Distorted Vehicle Magnetic Signatures Recognitions, for Length Estimation in Real Traffic Conditions.

Reliable cost-effective traffic monitoring stations are a key component of intelligent transportation systems (ITS). While modern surveillance camera systems provide a high amount of data, due to high installation price or invasion of drivers’ personal privacy, they are not the right technology. Therefore, in this paper we introduce a traffic flow parameterization system, using a built-in pavement sensing hub of a pair of AMR (anisotropic magneto resistance) magnetic field and MEMS (micro-electromechanical system) accelerometer sensors. In comparison with inductive loops, AMR magnetic sensors are significantly cheaper, have lower installation price and cause less intrusion to the road. The developed system uses magnetic signature to estimate vehicle speed and length. While speed is obtained from the cross-correlation method, a novel vehicle length estimation algorithm based on characterization of the derivative of magnetic signature is presented. The influence of signature filtering, derivative step and threshold parameter on estimated length is investigated. Further, accelerometer sensors are employed to detect when the wheel of vehicle passes directly over the sensor, which cause distorted magnetic signatures. Results show that even distorted signatures can be used for speed estimation, but it must be treated with a more robust method. The database during the real-word traffic and hazard environmental condition was collected over a 0.5-year period and used for method validation.

Bluetooth 5 performance analysis for inter-vehicular communications

Previous work has demonstrated the feasibility of Bluetooth Low Energy (BLE) as an alternative technology for data transfers in inter-vehicular communication (IVC) scenarios. Bluetooth 5.x core specifications enhance the trade-off between energy requirements, communication range and flexibility. In this paper, we aim to analyse the potential of Bluetooth 5 features for VANET applications, proposing a connectionless communication system. By means of field experiments, we evaluate long range and 2 × speed features, defining a set of communication scenarios. This allows us to test both Bluetooth 5.x range and application throughput. The evaluation includes experiments of V2I communications carried out under real highway traffic conditions. The experiments conducted demonstrate that communication ranges up to 300 m may be achieved depending on the communications scenario. The results also show how throughput degrades as the distance between devices increases. The results obtained are used to discuss future work, aimed at deeper analysing Bluetooth 5 features for VANET applications, completing the development of our prototype and evaluating VANET connectionless communications with the features included in the latest Bluetooth 5.2 specification.

Control algorithm for the urban traffic using a realtime simulation

Many types of research have been interesting by real-time control of urban networks. This paper, basing on a simplified urban traffic model, proposes a novel control approach based on model predictive control concept to reduce congestion and improve the safety of cars on the roads. The contributions of this paper are: First, we consider vehicle heterogeneity, represented by a mathematical model called “S Model” and integrate it with a realtime simulator to evaluate the performance of controllers on real traffic conditions. Second, in order to assess each controller's success under particular circumstances, the structured network-wide traffic controller based on model predictive control (MPC) theory is compared to a fixed time controller (FTC). Using two scenarios, different indicators are tested, i.e total time spent, vehicle number, queue length. The results show that the model predictive control quickly converges, with the different scenarios, and further improves social welfare.

Study to Compare CO2 Emissions from M1 Bharat Stage VI Passenger Vehicles at Chassis Dynamometer and Indian Real Traffic Conditions

<div class="section abstract"><div class="htmlview paragraph">Bharat Stage VI (BS VI) emission norms are already introduced in India from 1st April 2020. The implementation of BS VI emission standards essentially brings Indian motor vehicle regulations on par with most stringent International standards. The BS VI regulation also mandated Real Driving Emission (RDE) measurement with objective to limit regulated pollutants esp. NO<sub>X</sub> & PN during real use of vehicle. For M1 passenger vehicles Carbon Dioxide (CO<sub>2</sub>) emissions measured in Lab is also regulated under CAFÉ (Corporate Average Fuel Economy) however, CO<sub>2</sub> emission during Real on Road Driving is not regulated. So, this study was carried out to compare CO<sub>2</sub> on real road traffic conditions with standard lab conditions. This study was done on a set of BS VI compliant vehicles with diverse characteristic such as engine capacity, fuel type. These vehicles were tested on a chassis dynamometer in a vehicle-emissions laboratory under well-defined & controlled ambient conditions for temperature and humidity as per regulation specified in AIS 137 part 3 and then the same group of vehicles were tested on road using PEMS (Portable Emission Measurement System) equipment as per regulation specified in AIS 137 Part 3 Chapter 20. On road tests were carried out on working day during working hours in the city of Pune. This paper analyses & summarizes the change in CO<sub>2</sub> emission of these M1 passenger vehicles from lab to on road running, on the basis of different vehicle characteristics and also on the basis of different traffic condition i.e., city & highway traffic.</div></div>

Evaluating Influence of On-Road Parameter Variation in HD Application Using Virtual Approach for Upcoming IRDE Norms

<div class="section abstract"><div class="htmlview paragraph">Real Driving Emission (RDE) norms have changed the way vehicles are required to be calibrated and developed. This has moved the legislative requirements from predictable lab conditions to more realistic, real world conditions. Current Indian legislation allows certification for Heavy Duty (HD) applications on engine level and therefore decoupled from vehicle and the real world scenarios such as uncertainty and randomness in driver behavior, traffic conditions, road profiles, ambient conditions etc. which are not captured. Upcoming RDE legislation to be implemented in year 2023, has made it necessary to integrate engine with vehicle to consider the impact of various parameters on engine operating points and therefore on tail pipe emissions. This paper focusses upon the methodology developed using RDE cycle generator tool (RCG) for generating on-road parameters which influences the zone of engine operation and resulting emission levels. At ARAI, we have established a calibration strategy for Heavy Duty Commercial Vehicles for BS-VI RDE using virtual technique, which can be easily extendable to passenger vehicles as well. Virtual Test Bed (VTB) approach gives advantage to include all possible variations during early stages of vehicle calibration and therefore making it more robust. RDE Cycle Generator (RCG) module from AVL is used to generate GPS based road profile data including gradients and realistic traffic conditions. The module is capable to consider Indian legislative requirements for HD application requirements. The well validated Real Time (RT) HD vehicle plant model capable of complying to BS-VI norms is considered for evaluating influence of different parameters. Different routes are generated by varying parameters such as driver characteristics, traffic conditions, start and stop criteria etc. The vehicle is operated virtually under all possible extreme conditions to evaluate the engine-operating zone and accordingly revisit the calibration requirements to avoid surprises during real vehicle testing. The convenience of changing any critical parameter on RCG and then running vehicle virtually on VTB has benefitted in reducing the time and efforts for calibration and focusing more on calibration work and thus will help in achieving In-Service Conformity (ISC) requirements more confidently.</div></div>

Driving errors, estimated performance and individual characteristics under simulated and real road traffic conditions – A validation study

BackgroundThe suitability of driving simulators for the prediction of driving behaviour in road traffic has been able to be confirmed in respect of individual assessment parameters. However, there is a need for overarching approaches that take into account the interaction between various influencing factors in order to establish proof of validity. The aim of this study was to explore the validity of our driving simulator in respect of its ability to predict driving behaviour based on participants‘ observed driving errors and driver’s individual characteristics. Method41 healthy participants were assessed both in a Smart-Realo-Simulator and on the road. By means of linear modelling, the correlation between observed driving errors was investigated. In addition, the influence of self-reported and externally assessed driving behaviour as well as individual parameters (education and training; driving history) were analysed. ResultsBy including these factors, 58% of the variance could be explained. For observed driving errors, a relative validity was established. For self-reported and externally assessed driving behaviour, an absolute to relative validity emerged. The amount of time spent in education and training proved to have a significant influence on driving performance in the simulator, but not on the road. DiscussionIn general, our results confirmed the validity of our driving simulator with regard to observed and self-reported driving behaviour. It emerged that education and training as potential indicators of cognitive resources played a differential role regarding the study conditions. Since real road driving is considerably automated in experienced drivers, this result suggests that simulation-related behavioural regulation is challenged by additional cognitive demands as opposed to behavioural regulation extending to real road driving. However, the source of these additional cognitive demands remains currently elusive and may form the subject of future research.

The Model of the Optimal Number of Public Transport Vehicles in Mixed Traffic Flow Conditions: A Case Study

Bus passenger transport is very important for sustainable urban mobility, and due to the characteristics of the street network, it is usually realized in the conditions of mixed traffic flow. Disturbances and sudden changes of traffic flow parameters occurring in the street network in a mixed traffic flow affect the disruptions in schedule and travel time of all vehicles in the traffic flow, including public transport (PT) vehicles. In order to keep to the planned schedule in the peak hours of PT lines carried out in the conditions of mixed traffic flow, the operators introduce new vehicles or reduce the vehicles’ dwell time at terminuses, which is often impossible to do. The use of a larger number of public transport vehicles increases the fuel consumption, pollutants’ emission, and the operating costs. In this paper, a network optimization model was developed for defining the influence of the change of traffic flow parameters in a mixed traffic flow on travel time of PT vehicles. The model takes into consideration uncertain time unevenness of the change of traffic flow parameters, which enables determining the optimization of travel time and defining the necessary number of public transport vehicles for the purpose of keeping to the planned schedule. In order to develop the transport model, counting and analysis of the characteristics of traffic flow at 61 intersections on the city territory were carried out. The model was tested on bus line number 4 of PT in Novi Sad. The model showed that it is possible to achieve certain savings regarding the number of vehicles with the unchanged headway, that is, the unchanged level of service which is offered to the users. With the application of the model in real traffic conditions, significant savings, as well as operating and external costs’ reduction, can be achieved, which contributes to the sustainability of public bus transport in urban environments.

Improving traffic and emergency vehicle clearence at congested intersections using fuzzy inference engine

Traffic signals play an important role in controlling and coordinating the traffic movement in cities especially in urban areas. As the traffic is exponentially increasing in cities and the pre-timed traffic light control is insufficient in effective timing of the traffic lights, it leads to poor traffic clearance and ultimately to heavy traffic congestion at intersections. Even the Emergency vehicles like Ambulance and Fire brigade are struck at such intersections and experience a prolonged waiting time. An adaptive and intelligent approach in design of traffic light signals is desirable and this paper contributes in applying fuzzy logic to control traffic signal of single four-way intersection giving priority to the Emergency vehicle clearance. The proposed control system is composed of two parallel controllers to select the appropriate lane for green signal and also to decide the appropriate green light time as per the real time traffic condition. Performance of the proposed system is evaluated by using simulations and comparing with pre-timed control system in changing traffic flow condition. Simulation results show significant improvement over the pre-timed control in terms of traffic clearance and lowering of Emergency vehicle wait time at the intersection especially when traffic intensity is high.

Quantification of the airport-related pollution under wintertime anticyclonic conditions from idealized large-eddy simulations

Airport-related pollution is quantified using an idealized numerical environment. 14-hour large-eddy simulations are run over a fictitious but representative regional airport under an academic wintertime anticyclonic situation with the atmospheric model Meso-NH. A simplified photo-chemical module is used and the model is coupled with an emission inventory providing realistic traffic conditions over a 0600–2000 UTC cycle. The emission inventory only includes aircraft related pollutants sources allowing us to isolate and quantify their contribution to local pollution. Two simulations are run in order to characterize the fine scale spatio-temporal evolution of the plume under simple and double traffic activity. Starting from an idealized quiescent and clean atmosphere, the NO2 concentrations reached over the platform range from 101 to 104 μg m−3. The air quality standards are transgressed near the emissions sources and over a large portion of the platform when the atmosphere is stably stratified. On a larger-scale, the airport-related emissions contribute to NO2 levels up to at least 50 μg m−3 over several square kilometers. The size of the areas affected by the plume is very sensitive to the traffic activity and grows at a rate which is higher than the activity increase itself. Conversely, a twofold augmentation of the traffic results in a less than twofold NO2 concentrations increase because of the non-linearity of the photo-chemical activity. Future contributions could be conducted with a more realistic configuration in order to quantify the interactions between this airport-related plume and the surrounding emissions.

The Performance of Demand Responsive Pelican Crossing at Midblock Pedestrian Crossing Facility

Pedestrians are travellers who are the most vulnerable to traffic accidents. In general, pedestrian safety in urban areas tends to be neglected. Lack of adequate pedestrian facilities, especially midblock pedestrian crossing facilities, has an impact on pedestrian safety. In order to improve pedestrian safety, therefore the Surakarta city government provides a pedestrian crossing facility, namely Pelican crossing. The existence of a Pelican crossing has an impact on road performance where the traffic and pedestrian flow is regulated by signal timing. The existing Pelican crossing is a type of pedestrian-actuated control logic with fixed-time operation. This study aims to design demand responsive Pelican crossing based on Vehicle Actuated Control Extension Principle (VAC EP) logic, where signal timing is based on real time traffic conditions. The performance of Pelican crossings at midblock pedestrian crossing facility is analysed by using a calibrated and validated VISSIM simulation model. The performance of the proposed Pelican crossing (VAC EP) is compared to the existing Pelican crossing. The simulation analysis results show that the proposed Pelican crossing (VAC EP) performance is better than the existing Pelican crossing, in terms of average pedestrian delay.

Energy management system of the hybrid ultracapacitor-battery electric drive vehicles

The search for new, alternative propulsion and energy sources in transport is one of the economic and technological priorities of the current decade. The modern development of hybrid drives and electric means of transport makes it possible to at least partially diversify conventional drive systems. The study discusses the use of a battery and ultraca-pacitor in electric vehicles. Simulation analyzes of energy flow were performed using the solutions of electric drive systems and various energy storage control algorithms. The research was carried out in relation to the use of braking energy, its conversion into electricity and its storage in a battery or ultracapacitor. The operating conditions of the battery and the ultracapacitor were assessed in terms of specific energy consumption while driving. The article pro-posed the use of a drive system connected in series, the last link of which was an ultracapacitor. Such a solution signif-icantly reduced the use of the battery as well as its regular charging-discharging. At the same time, it required the use of a high-capacity ultracapacitor, which contributed to increasing its charging time. The analyzes were carried out using standardized research tests as well as tests in real traffic conditions. The research was carried out with the use of the AVL Cruise software for the analysis of energy flow in vehicles; a middle class passenger vehicle was selected for the tests, equipped with an electrochemical battery and – in the next stage of the research – an ultracapacitor. Three research models were used: I) typical electric drive system; II) a system with the use of ultracapacitors ran by a simple control algorithm; III) a system with the use of ultracapacitors with an advanced control algorithm (the algorithm took into account the change of driving conditions to the ultracapacitor charging conditions). The advantages of using ultracapacitors in the electric drive of a vehicle were demonstrated, especially for results obtained in real traffic condi-tions. Analyzing the simulation tests results allowed to determine the most advantageous options of utilizing these systems, in particular in the aspect of increased possibilities of algorithms controlling the flow of electricity in the drive system.

ESTABLISHMENT OF A UNIFORM ROUTE GUIDANCE SYSTEM IN UKRAINE TAKING INTO ACCOUNT THE WORLD’S BEST PRACTICES TO IMPROVE ROAD SAFETY

Route guidance tools have a significant impact on road safety on public roads, as they carry important information on route guidance: provide drivers with information on the location on a specified road, regularly confirm the planned direction of movement, timely inform road users about the change of specified route direction and indicate the distance to the final object. This is very important information for the driver and it is difficult to overestimate it in road safety. Timely informing of drivers on the route direction will allow them carrying out adjustments in advance and feel confident on the road. Ensuring the completeness of route guidance information prevents emergency braking of vehicles in the area of traffic junctions and violation of the maneuvering rules to make a turn / turnaround in the right direction, and such maneuvers lead to road accidents. The establishment of a uniform route guidance system will reduce the road accident level and the cost of transportation due to excessive mileage of vehicles in the case of wrong route and help the drivers freely and easily get to their destination. The main need for information is felt by the drivers of vehicles whose actions directly impact the road safety. This, in turn, determines the basic principles and requirements for the composition, placement and choice of information tools. During the trip, the drivers need the information that would allow them navigating freely on the roads when passing the selected route that will relieve the stress of drivers and reduce the probability of road accidents, as well as increase the capacity of roads. It helps the drivers to adjust the previously selected route taking into account the real traffic conditions during the trip thereby minimizing the time consumption. To navigate the roads during movement, the drivers need the information about streets, objects and directions. Such information is provided by information signs, with which the road network must be equipped in sufficient quantity. The information provision should differ depending on the settlements, public roads and traffic conditions. A comprehensive solution of the issue of quality information provision to the road users can be achieved only by establishing a uniform route guidance system for road users which will take into account the needs for information of different categories of road users.

Simultaneous multi-objective optimization of a PHEV power management system and component sizing in real world traffic condition

Due to emission concerns as well as fuel shortages and expenses, plug-in hybrid electric vehicles (PHEVs) have become public and successful in the market. The performance of such vehicles can be mainly associated with energy management, powertrain system component sizes, and costs which are considered as the most effective factors improving fuel economy and reducing emissions. Since there is an interaction between the performances of these sub-systems, simultaneous optimization of control strategy and component sizing were developed in the presence of multi-objective optimization such as fuel consumption, emissions, as well as operating costs based on a genetic algorithm. For this purpose, a multi input fuzzy logic controller (MFLC) was designed at the first step for energy management system with regard to energy efficiency and batteries performance. Then, a novel simultaneous multi-objective constrained optimization approach was implemented to enhance optimally various coupling design parameters (optimization variables), conflicting design objectives (fuel economy, costs, and emissions), as well as non-linear constraints (vehicle dynamic and batteries performance). Accordingly, the simulation results showed that the proposed instantaneous optimization method was sufficient for improving fuel economy despite increases in the optimization variables and time taking multiple objectives and constraints into account. Besides, the results demonstrated that the designed multi-objective simultaneous optimization algorithm could respectively improve overall energy efficiency and emission reduction of the PHEV up to 7% and 10% for real-world driving cycle and also decreases the operational costs up to 12% approving its applicability. In the optimization process the batteries performance and vehicle dynamic were observed as the constraints to enhance the batteries safety and driver required performance. Finally, the sensitivity and the robustness of the proposed algorithm were verified through the variation of vehicle parameters as well as road and traffic conditions.

Effect of adaptive control on the LED street luminaire lifetime and on the lifecycle costs of a lighting installation

We report for the first time the effect of ageing due to adaptive control of lighting on the lifecycle costs of luminaire installations. Two types of LED street luminaire were aged (1) as the luminaire lit for 9 hours and then switched off for 3 hours and (2) under intensive ageing using adaptive control conditions mimicking presence of vehicles, where the luminaires were switched with 30-second interval between 100% and 20% power within the cycle of (1). The test continued for 32,000 hours. Luminaire lifetime was found to decrease by 10% due to the intensive adaptive control, which exaggerates the ageing as compared to real traffic conditions. We estimate that a realistic rate of dimming cycles would decrease the luminaire lifetime by 0–2%, increasing the lifecycle costs of a lighting installation by 0–0.7%. With a traffic-aware control system, capable of 50% energy saving in lighting, the lifecycle costs are estimated to reduce by 25% as compared to a similar LED luminaire installation without traffic-aware control, outweighing the costs due to the reduced lifetime. The smart controlling of lighting is considered as a useful way to meet future energy saving targets.