Simulated Traffic Conditions Research Articles

Performance and Lifecycle of Hot Asphalt Mix Modified with Low-Percentage Polystyrene and Polybutadiene Compounds

The paper investigates the improvement of bitumen mixture fatigue resistance and the rutting performance by using a specific low percentage of a styrene–butadiene–styrene (SBS) polymer, which contains polystyrene and polybutadiene compounds. A Fourier transform infrared (IR-FT) spectroscopy of the SBS polymer used in following test was carried out to ascertain the polybutadiene and polystyrene compound ratio, which may affect the modificant properties. Unmodified, low-percentage modified SBS, and common polymer-modified bitumen (PMB) as a reference were tested to ascertain the properties, fatigue resistance, and the rutting performance. The test results of the low-percentage modification with SBS are compared against unmodified mixtures and standard PMB mixtures. Finally, a simulation of the practical application was performed using the HDM-4 software (version 2.0), where the material research findings, with an emphasis on the rutting performance, were translated into the pavement performance with a varying binder course layer under simulated traffic conditions. Lifecycle analysis, with a focus on emissions production (CO2, SO2, and NOx) during pavement operation, was conducted for pavements with unmodified, low-percentage modified SBS, and standard PMB binder courses. The lifecycle analysis showed that a 3% modification of the binder course with the SBS polymer can extend the rutting parameter pavement lifecycle by approximately 34.5%, which is about half of the extension provided by the standard PMB modification. The resulting improvement in the pavement serviceability translated to a 9% reduction in CO2 and SO2 emissions and a 7.2% reduction in NOx emissions over a 20-year period.

Safe Navigation and Evasive Maneuvers Based on Probabilistic Multi-Controller Architecture

Automated Driving System (ADS) requires a high fidelity decision-making strategy to palliate to uncertain environment and changing dynamics of other road users. Considering the uniqueness of each traffic situation, the task of modeling every use-case is nearly impossible. One solution is to verify the safety of the decided/planned maneuvers during the vehicle’s navigation. This will give ability to the system to re-plan and evade any dangerous situation. The main focus of this work relies on guaranteeing safety of the ADS in sudden hazardous and risky situation. In this aim, an evasive strategy is proposed as a part of an overall Probabilistic Multi-Controller Architecture (P-MCA) designed for safe automated driving under uncertainties. This P-MCA is composed of several complementary interconnected modules, and addresses thus the full pipeline from risk assessment, path planning to decision-making and control for an ADS. The evasive strategy relies on two identified steps. The first step is performed through the decision-making framework, where a Sequential Decision Networks for Maneuver Selection and Verification (SDN-MSV) calculates a discrete evasive action maneuver based on defined situational criteria. The second step consists in computing the corresponding low-level control. It is based on the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) that allows the ego-vehicle to pursue the advised collision-free evasive maneuver to avert an accident and to guarantee the vehicle’s safety at any time. The reliability and the flexibility of the overall proposed P-MCA and its elementary components have been validated in simulated traffic conditions, with various driving scenarios, and in real-time.

TECHNICAL PROPERTIES AND RESEARCH CAPABILITIES OF THE TRUCK SIMULATOR OWNED BY THE MILITARY INSTITUTE OF AVIATION MEDICINE – A NEW PERSPECTIVE IN RESEARCH ON TRUCK DRIVERS

Abstract: This paper is aimed at presenting basic technical properties and possibilities of using the truck simulator owned by the Military Institute of Aviation Medicine (MIAM). The truck driving simulator is a stationary device, equipped with a six degrees of freedom (6 DoF|) motion system and reproducing the functionality of a truck on the basis of the Mercedes Benz Actros cabin. It is intended for conducting research as well as training truck drivers in simulated traffic conditions.

Theoretical Comparison of the Effects of Different Traffic Conditions on Urban Road Environmental External Costs

External costs that are associated with air pollution, climate change linked to greenhouse gas emissions (GHG), and noise are among the most important environmental externalities that are generated by road transport, which have been well monetized. This paper theoretically investigates the effects of different traffic conditions on the environmental external costs of urban roads where traffic flow is more complicated than un-interrupted traffic flows. A Monte Carlo method is used to theoretically simulate traffic speed in different traffic conditions. Subsequently, the emitted carbon dioxide (CO2), nitrogen oxides (NOx), carbon monoxide (CO), particulate matter (PM), sulfur dioxide (SO2), and noise were estimated in each of the theoretically simulated traffic conditions. Finally, the environmental external costs in each traffic condition were calculated taking the EU average costs values into account. The results showed that, when compared to free-flow condition, the total air pollutant and GHG external costs (€2010) have been increased by 6%, 31%, 44%, 50%, and 93% in under-saturated flow, accelerated flow, decelerated flow, congestion, and over-saturated congestion, respectively. Furthermore, the total noise cost (€2010/year/person exposed), as compared to free-flow condition, has been decreased by 2%, 11%, 12%, 36%, and 69% in accelerated flow, under-saturated flow, congestion, over-saturated congestion, and decelerated flow, respectively.

Dynamic routing with ant system and memory-based decision-making process

Dynamic routing is an essential tool for today’s cities. Dynamic routing problems can be solved by modelling them as dynamic optimization problems (DOPs). DOPs can be solved using Swarm Intelligence and specially ant colony optimization (ACO) algorithms. Although different versions of ACO have already been presented for DOPs, there are still limitations in preventing stagnation and premature convergence and increasing convergence rate. To address these issues, we present an in-memory pheromone trail and an algorithm based on it (named AS-gamma) in the framework of ACO. In-memory pheromone trail is effectively increasing diversity after a change in an environment. Results of experimenting AS-gamma in three scenarios on a real-world transportation network with different simulated traffic conditions demonstrated the effectiveness of the presented in-memory pheromone trail method. The advantages of AS-gamma over three existing DOP algorithms have been illustrated in terms of solutions quality. Offline performance and accuracy measures indicate that AS-gamma faces less stagnation, premature convergence and it is suitable for crowded environments.

ESTIMATED ASSESSMENT OF THE POTENTIAL IMPACT OF DRIVERASSISTANCE SYSTEMS USED IN AUTOMATED VEHICLES ON THE LEVEL OF ROAD SAFETY IN POLAND

Strengthening road safety in the face of the enormous development of the automotive in recent decades is crucial. The safety benefits of automated vehicles are paramount. Automated vehicles have the potential to remove human error in road traffic, which will help protect drivers and passengers, as well as pedestrians and bicyclists. The carried-out forecasts are pioneering for Polish road traffic conditions. In England, studies have been carried out to determine the estimated impact of autonomous vehicles on road safety in simulated traffic conditions on the motorway. In Poland, preliminary forecasts of the reduction in the number of road accidents were made; however, they were based on other assumptions. Therefore, estimating the impact of using autonomous vehicles in order to increase the level of road safety is an innovative activity for Polish road conditions. For the purposes of this article, available statistical data on vehicles registered in Poland, their equipment with advanced driver-assistance systems as well as accident data and their causes were analyzed. A diagnosis of Road Safety in Poland in 2018 (base year for further estimations) was made, taking into account the trend of recent years together with an indication of the most common causes of road accidents. These data were compiled with statistical data from other countries about the influence of driversupport systems on traffic safety. Possible potential for increasing Road Safety in Poland by the year 2030 was estimated. The analyses were prepared assuming different types of processes related to traffic, road safety, and the recent development of the passenger car fleet in Poland. Presented results show four scenarios of road safety change, where the number of accidents is reduced with statistical average of 5000 reduction in the year 2030. These expectations are based on various predictable factors connected with upgrade of car fleet quality and take into account changes in road safety observed in recent years. Based on the current trend of driving automation and rapid development of driver-support systems, the provided estimations were found reliable and likely. The conducted research shows the benefits and the need for the use of driver-assistance systems in vehicles as they can measurably affect the level of road safety.

Electromagnetic Energy Harvesting Technology: Key to Sustainability in Transportation Systems

The convergence of concerns about environmental quality, economic vitality, social equity, and climate change have led to vast interest in the concept of sustainability. Energy harvesting from roadways is an innovative way to provide green and renewable energy for sustainable transportation. However, energy harvesting technologies are in their infancy, so limited studies were conducted to evaluate their performance. This article introduces innovative electromagnetic energy harvesting technology that includes two different mechanisms to generate electrical power: a cantilever generator mechanism and a rotational mechanism. Laboratory experimental tests were conducted to examine the performance of the two mechanisms in generating power under different simulated traffic conditions. The experimental results had approximately root mean square power 0.43 W and 0.04 W and maximum power of 2.8 W and 0.25 W for cantilever and rotational, respectively. These results showed promising capability for both mechanisms in generating power under real traffic conditions. In addition, the study revealed the potential benefits of energy harvesting from roadways to support sustainability in transportation systems. Overall, the findings show that energy harvesting can impact sustainable transportation systems significantly. However, further examination of the large-scale effects of energy harvesting from roadways on sustainability is needed.

Decentralized network level adaptive signal control by multi-agent deep reinforcement learning

Adaptive traffic signal control systems are deployed to accommodate real-time traffic conditions. Yet travel demand and behavior of the individual vehicles might be overseen by their model-based control algorithms and aggregated input data. Recent development of artificial intelligence, especially the success of deep learning, makes it possible to utilize information of individual vehicles to control the traffic signals. Several pioneering studies developed model-free control algorithms using deep reinforcement learning. However, those studies are limited to isolated intersections and their effectiveness was only evaluated in ideal simulated traffic conditions by hypothetical benchmarks. To fill the gap, this study proposes a network-level decentralized adaptive signal control algorithm using one of the famous deep reinforcement methods, double dueling deep Q network in the multi-agent reinforcement learning framework. The proposed algorithm was evaluated by the real-world coordinated actuated signals in a simulated suburban traffic corridor which emulates the real-field traffic condition. The evaluation results showed that the proposed deep-reinforcement-learning-based algorithm outperforms the benchmark. It is able to reduce 10.27% of the travel time and 46.46% of the total delay.

Energy harvesting and evaluation of a novel piezoelectric bridge transducer

A novel bridge transducer based on the cymbal design has been developed for energy harvesting from impact loading by vehicle-induced deformations on pavement. The bridge transducer consists of a 2 mm thick 32 × 32 mm square soft PZT ceramic and hardened steel end caps. A unique electrode design enables the PZT to be poled along its length, effectively utilizing d33 mode for enhanced energy generation. The effective d33, of d33eff of a bridge transducer is 19,000 pC/N and the effective piezoelectric voltage coefficient, g33eff, is 2150 × 10−3 Vm/N. When compared to the conventional cymbal transducer design, horizontal poling increases energy and voltage considerably. Each loading at 600 lbs generates 0.83 mJ of energy from the prototype transducer module with 64 transducers in parallel. Loading under simulated traffic conditions at 500 lb and 5 Hz generates 2.1 mW at a resistive load of 330 kOhm. The reliability and cycles to failure of the transducer design is studied and the transducers are evaluated after 50,000 loading cycles. Inconsistency in the epoxy layer thickness has been identified as the cause of premature failure.

Hardware-in-the-Loop Testing of Connected and Automated Vehicle Applications: A Use Case for Queue-Aware Signalized Intersection Approach and Departure

Most existing studies on connected and automated vehicle (CAV) applications apply simulation to evaluate system effectiveness. Model accuracy, limited data for calibration, and simulation assumptions limit the validity of evaluation results. One alternative approach is to use emerging hardware-in-the-loop (HIL) testing methods. HIL test environments enable physical test vehicles to interact with virtual vehicles from traffic simulation models, providing an evaluation environment that can replicate deployment conditions at early stages of CAV technology implementation without incurring excessive costs related to large field tests. In this study, a HIL testing system for vehicle-to-infrastructure (V2I) CAV applications is developed. The involved software and hardware includes a physical CAV controlled in real time, a traffic signal controller, communication devices, and a traffic simulator (VISSIM). Such HIL systems increase validity by considering the physical vehicle’s trajectories—which are constrained by real-world factors such as GPS accuracy, communication delay, and vehicle dynamics—in a simulated traffic environment. The developed HIL system is applied to test a representative early deployment CAV application: queue-aware signalized intersection approach and departure (Q-SIAD). The Q-SIAD algorithm generates recommended speed profiles based on the vehicle’s status, signal phase and timing (SPaT), downstream queue length, and system constraints and parameters (e.g., maximum acceleration and deceleration). The algorithm also considers the status of other vehicles in designing the speed profiles. The experiment successfully demonstrated this functionality with one test CAV driving through one intersection controlled by a fixed-timing traffic signal under various simulated traffic conditions.

Using an Agent‐Based Simulation to Evaluate the Performance of Control Algorithms for an Intelligent Traffic Light System

AbstractThis paper examines a case study for using an agent‐based model to evaluate potential solutions to the ubiquitous problem of automobile traffic. The overall objective is to use simulations to evaluate the performance of intelligent traffic light system control algorithms to improve traffic flow along an entire section of highway. The approach uses an agent‐based modeling tool to simulate the flow of traffic using several different traffic control algorithms. The methodology includes steps to define the measures of effectiveness, simulation parameters, traffic control algorithms, and identify a simulation tool, followed by simulating the algorithms, and evaluating the performance results. Several alternative algorithms were evaluated including single‐intersection control and multi‐intersection synchronized flow. The initial results show a significant performance difference between the control algorithms. However, simulated traffic conditions need to be validated, along with further model refinements, before a final assessment of the algorithm performance can be made.

Freight vehicle routing with reliable link travel times: a method based on network fundamental diagram

This paper presents a procedure for the solution of the Vehicle Routing Problem (VRP) based on reliable link travel times. They are obtained as a combination of spatially disaggregated and aggregated data about simulated traffic conditions on an urban road network. The disaggregated data concern the congested link travel times, which are traditionally used as variable to be minimized in VRP. The novelty of this research article consists in the introduction of spatially aggregated data, which are estimated by means of the Network Fundamental Diagram (NFD). In a within-day dynamic context, they are a measure of reliability of travel times because they could anticipate the latter ones’ variation in the short term. The equation of reliable link travel times is composed of a congestion term, expressing the traditional congested link travel times (or generalized costs), and a reliability term, which depends on the fundamental diagram of the link and the NFD of the homogeneous cluster of adjacent links. The proposed procedure has been validated and applied for two real test cases. NFDs data are used in the proposed link travel time function to calculate reliable travel times. The reliable link travel times are used for the solution of VRP to obtain optimal routes of freight vehicles.

Test and assessment method of Automotive Safety Systems (SSB) particularly to monitor traffic incidents

The rapid development of telematics, particularly mobile telephony (GSM), wireless data transmission (GPRS) and satellite positioning (GPS) noticeable in the last decade, resulted in an almost unlimited growth of the possibilities for monitoring of mobile objects. These solutions are already widely used in the so-called “Intelligent Transport Systems” - ITS and affect a significant increase for road safety. The article describes a method of testing and evaluation of Car Safety Systems (Polish abbreviation - SSB) especially for monitoring traffic incidents, such as collisions and accidents. The algorithm of SSB testing process is also presented. Tests are performed on the dynamic test bench, part of which is movable platform with car security system mounted on it. Crash tests with a rigid obstacle are carried out instead of destructive attempts to crash test of the entire vehicle which is expensive. The tested system, depending on the simulated traffic conditions, is mounted in such a position and with the use of components, indicated by the manufacturer for the automotive safety system installation in a vehicle, for which it is intended. Then, the tests and assessments are carried out.

Behavior of Laterally Damaged Prestressed Concrete Bridge Girders Repaired with CFRP Laminates Under Static and Fatigue Loading

Many bridges are subject to lateral damage for their girders due to impact by over-height vehicles collision. In this study, the optimum configurations of carbon fiber reinforced polymers (CFRP) laminates were investigated to repair the laterally damaged prestressed concrete (PS) bridge girders. Experimental and analytical investigations were conducted to study the flexural behavior of 13 half-scale AASHTO type II PS girders under both static and fatigue loading. Lateral impact damage due to vehicle collision was simulated by sawing through the concrete of the bottom flange and slicing through one of the prestressing strands. The damaged concrete was repaired and CFRP systems (longitudinal soffit laminates and evenly spaced transverse U-wraps) were applied to restore the original flexural capacity and mitigate debonding of soffit CFRP longitudinal laminates. In addition to the static load tests for ten girders, three more girders were tested under fatigue loading cycles to investigate the behavior under simulated traffic conditions. Measurements of the applied load, the deflection at five different locations, strains along the cross-section height at mid-span, and multiple strains longitudinally along the bottom soffit were recorded. The study investigated and recommended the proper CFRP repair design in terms of the CFRP longitudinal layers and U-wrapping spacing to obtain flexural capacity improvement and desired failure modes for the repaired girders. Test results showed that with proper detailing, CFRP systems can be designed to restore the lost flexural capacity, sustain the fatigue load cycles, and maintain the desired failure mode.

THE DAIMLER-BENZ DRIVING SIMULATOR NEW TECHNOLOGIES DEMAND NEW INSTRUMENTS

SUMMARY A driving simulator is a computer-controlled tool to study the Interaction between driver and vehicle under simulated traffic conditions. It permits a controllable, reproducible and cost-effective study of vehicle parameters up to the limits of active safety under non-dangerous conditions. The paper will describe fully the concept, design and planned activities of the DAIMLER-BENZ DRIVING-SIMULATOR as well as report on the new possibilities of using the system as a research and development tool.

FOLLOWING DISTANCE ON THE HIGHWAY RELATED TO SPEED, TRIP DURATION, TRAFFIC, AND ILLUMINATION.

Following distances of fifteen drivers were measured at 33 and 55 mph, during day and night runs, at 4 intervals over 2-hr periods, and under 3 simulated traffic conditions. Consistent change in following distances occurred only for different speeds.