Heterogenous motorised traffic flow modelling using cellular automata

Traffic congestion is a major problem in most major cities around the world with few signs that this is diminishing, despite management efforts. In planning traffic management and control strategies at urban and inter urban level, understanding the factors involved in vehicular progression is vital. Most work to date has, however, been restricted to single vehicle-type traffic. Study of heterogeneous traffic movements for urban single and multi-lane roads has been limited, even for developed countries and motorised traffic mix, (with a broader spectrum of vehicle type applicable for cities in the developing world). The aim of the research, presented in this thesis, was thus to propose and develop a model for heterogeneous motorised traffic, applicable to situations, involving common urban and interurban road features in the western or developed world. A further aim of the work was to provide a basis for comparison with current models for homogeneous vehicle type. A two-component cellular automata (2-CA) methodology is used to examine traffic patterns for single-lane, multi-lane controlled and uncontrolled intersections and roundabouts. In this heterogeneous model (binary mix), space mapping rules are used for each vehicle type, namely long (double-unit length) and short (single-unit length) vehicles. Vehicle type is randomly categorised as long (LV) or short (SV) with different fractions considered. Update rules are defined based on given and neighbouring cell states at each time step, on manoeuvre complexity and on acceptable space criteria for different vehicle types. Inclusion of heterogeneous traffic units increases the algorithm complexity as different criteria apply to different cellular elements, but mixed traffic is clearly more reflective of the real-world situation. The impact of vehicle mix on the overall performance of an intersection and roundabout (one-lane one-way, one-lane two-way and two-lane two-way) has been examined. The model for mixed traffic was also compared to similar models for homogeneous vehicle type, with throughput, queue length and other metrics explored. The relationship between arrival rates on the entrance roads and throughput for mixed traffic was studied and it was found that, as for the homogeneous case, critical arrival rates can be identified for various traffic conditions. Investigation of performance metrics for heterogeneous traffic (short and long vehicles), can be shown to reproduce main aspects of real-world configuration performance. This has been validated, using local Dublin traffic data. The 2-CA model can be shown to simulate successfully both homogeneous and heterogeneous traffic over a range of parameter values for arrival, turning rates, different urban configurations and a distribution of vehicle types. The developed model has potential to extend its use to linked transport network elements and can also incorporate further motorised and non-motorised vehicle diversity for various road configurations. It is anticipated that detailed studies, such as those presented here, can support efforts on traffic management and aid in the design of optimisation strategies for traffic flow

Optimization of Work Zone Segments on Urban Roads Using Cellular Automata Model in Mixed Traffic

Increased delays and reduced speeds in work zones leads to congestion. This can be improved by optimizing the work zone length. The focus of this study is to model work zones using cellular automata model and to find the effects of work zones on traffic flow. The methodology adopted in the study involved creating work-zone on the road by blocking some of the cells and then determining traffic characteristics such as delay and queue lengths for model validation. For this the lateral movement rules of the existing Cellular Automata model were modified in order to replicate the traffic movement near work zones. This model is calibrated and validated using data from work zone observed near a metro rail station in Delhi. From the analysis it was evident that the queue length increased with increase in the length of work zone. Several relationships were tried between delay and work zone length. Among them the rational form was found suitable

Modelling unsignalised traffic flow with reference to urban and interurban networks

A new variant of cellular automata (CA) models is proposed, based on Minimum Acceptable Space (MAP) rules, to study unsignalised traffic flow at two-way stop-controlled (TWSC) intersections and roundabouts in urban and interurban networks. Categorisation of different driver behaviour is possible, based on different space requirements (MAPs), which allow a variety of conditions to be considered. Driver behaviour may be randomly categorised as rational, (when optimum conditions of entry are realised), conservative, urgent and radical, with specified probabilities at each time step. The model can successfully simulate both heterogeneous and inconsistent driver behaviour and interactions at the different road features. The impact of driver behaviour on the overall performance of intersections and roundabouts can be quantified and conditions for gridlock determined. Theorems on roundabout size and throughput are given. The relationship between these measures is clearly non-monotonic. Whereas previous models consider these road features in terms of T-intersections, our approach is new in that each is a unified system. Hence, the relationship between arrival rates on entrance roads can be studied and critical arrival rates can be identified under varied traffic and geometric conditions. The potential for extending the model to entire urban and interurban networks is discussed

Studying Non-coaxiality in Non-lane-based Car-following Behavior

In this paper, in order to study non-lane-based car-following, the non-coaxiality concept is defined, where there is a significant lateral difference between the leader and follower vehicle. Two main reasons for non-coaxiality were addressed by drivers in the interview: providing more visible distances beyond leader vehicle and increasing the possibility of escaping in sudden brakes to avoid rear-end collision. Results showed that non-lane-based behavior was due to the effect of the existence of other cars in the traffic flow. By reducing speed or increasing density, vehicles more affect each other.  But this trend will continue up until vehicles fill the free spaces. In other words, vehicles make others stick to the leader’s path in high-density flow. Studying the relationship between lateral distance and time headway demonstrated that time headway threshold for initiation of car-following behavior in Iranian drivers can be approximately 2 seconds. In this study, Overtaking was defined as a part or continuation of the non-lane-based driving behavior. For overtaking on the left, steering angle, the final lateral distance and the lateral speed difference between the follower and leader were 33%, 28% and 15% less than overtaking on the right

Identification of safety effects of infrastructure related measures, Deliverable 5.2 of the H2020 project SafetyCube

Identification of safety effects of infrastructure related measures, Deliverable 5.2 of the H2020 project SafetyCub

Threshold Queueing to Describe the Fundamental Diagram of Uninterrupted Traffic

Queueing because of congestion is an important aspect of road traffic. This paper provides a novel threshold queue that models the empirical shape of the fundamental diagram. In particular, we show that our threshold queue with two service phases captures the capacity drop that is eminent in the fundamental diagram of modern traffic. We use measurements on a Danish highway to illustrate that our threshold queue is indeed capable of capturing the fundamental diagram of real-world traffic systems. We furthermore indicate the modelling power of our threshold queue via a sensitivity study showing that our model is able to capture a wide range of shapes for the fundamental diagram

IEEE Access Special Section Editorial: Big Data Technology and Applications in Intelligent Transportation

During the last few years, information technology and transportation industries, along with automotive manufacturers and academia, are focusing on leveraging intelligent transportation systems (ITS) to improve services related to driver experience, connected cars, Internet data plans for vehicles, traffic infrastructure, urban transportation systems, traffic collaborative management, road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plans, and the development of an effective ecosystem for vehicles, drivers, traffic controllers, city planners, and transportation applications. Moreover, the emerging technologies of the Internet of Things (IoT) and cloud computing have provided unprecedented opportunities for the development and realization of innovative intelligent transportation systems where sensors and mobile devices can gather information and cloud computing, allowing knowledge discovery, information sharing, and supported decision making. However, the development of such data-driven ITS requires the integration, processing, and analysis of plentiful information obtained from millions of vehicles, traffic infrastructures, smartphones, and other collaborative systems like weather stations and road safety and early warning systems. The huge amount of data generated by ITS devices is only of value if utilized in data analytics for decision-making such as accident prevention and detection, controlling road risks, reducing traffic carbon emissions, and other applications which bring big data analytics into the picture

Structure and pressure drop of real and virtual metal wire meshes

An efficient mathematical model to virtually generate woven metal wire meshes is presented. The accuracy of this model is verified by the comparison of virtual structures with three-dimensional images of real meshes, which are produced via computer tomography. Virtual structures are generated for three types of metal wire meshes using only easy to measure parameters. For these geometries the velocity-dependent pressure drop is simulated and compared with measurements performed by the GKD - Gebr. Kufferath AG. The simulation results lie within the tolerances of the measurements. The generation of the structures and the numerical simulations were done at GKD using the Fraunhofer GeoDict software

Traffic fundamentals for A22 Brenner freeway by microsimulation models.

La tesi di dottorato ha avuto come tema lo studio e l’applicazione di un modello di micro-simulazione del traffico in ambito autostradale. Essa si compone di quattro capitoli, con ognuno dei quali si è voluto sintetizzare e descrivere il lavoro di studio e ricerca svolto durante il suddetto corso di Dottorato di Ricerca. L’obiettivo principale del presente lavoro di tesi è stato quello di mettere a punto una metodologia finalizzata all’ottenimento delle relazioni fondamentali di deflusso in ambito autostradale attraverso il software di microsimulazione del traffico Aimsun. Come risulta infatti noto dalla letteratura scientifica, le relazioni fondamentali del deflusso sono utilizzate nel campo dell’ingegneria stradale per determinare il livello di servizio di alcune infrastrutture, quali ad esempio tronchi autostradali, al fine di fornire un’informazione utile alla previsione delle diverse condizioni operative di deflusso che si possono registrare su di esse. Nello specifico, la prima parte del lavoro di tesi è stata incentrata sullo sviluppo di una metodologia di calibrazione basata sulle relazioni velocità-densità nel processo di calibrazione di un modello di microsimulazione, visto che le predette relazioni rappresentano il fenomeno del traffico in un ampio range di condizioni operative e ben sintetizzano tutte le informazioni che possono essere raccolte sul campo su due delle tre variabili chiave del deflusso. Il confronto tra i dati di campo e i dati simulati è stato inizialmente condotto usando l’analisi statistica come tecnica di pattern recognition. In particolare, un segmento autostradale in condizioni non congestionate è stato scelto come caso studio; a partire dai dati rilevati sull’autostrada A22 del Brennero, sono state sviluppate regressioni statistiche tra le variabili del traffico. Analoghe relazioni sono state ottenute usando il software di microsimulazione del traffico Aimsun, che ha permesso di riprodurre le condizioni di campo e di variare alcuni parametri, finché è stato ottenuto un buon adattamento tra i dati di campo e i dati simulati. Nella fase di calibrazione manuale del modello di traffico in Aimsun è stato però difficile valutare l’effetto della variazione contemporanea di più parametri sugli output del modello. Ciò ha limitato sicuramente la scelta dei parametri del modello sui quali intervenire durante il processo di calibrazione e di valutare la risposta dello stesso anche in condizioni di funzionamento dell’autostrada diverse da quelle già considerate (tratto instabile della curva di deflusso). Per superare questo problema, nella fase finale del lavoro di tesi, è stato definito un algoritmo genetico in grado di calibrare in modo automatico i parametri del modello di microsimulazione e restituire così un “ottimo” set di valori in grado di minimizzare gli scarti fra i valori simulati e quelli osservati nella realtà. Ciò ha consentito un notevole risparmio di tempo rispetto alla procedura di calibrazione manuale precedentemente applicata. Un altro obiettivo del presente lavoro è stato finalizzato alla stima dell’impatto dei mezzi pesanti sulla qualità della circolazione per l’autostrada A22 del Brennero attraverso i risultati ottenuti in microsimulazione mediante i quali è stato infatti possibile calcolare i coefficienti di equivalenza (Passenger Car Equivalents Factor (PCEs)) tra i mezzi pesanti e le autovetture.In this work of PhD Thesis a methodology to find fundamentals diagrams by microsimulations will be presented. As it is know from scientific literature, the fundamental diagram relates two of the three variables: average speed (v), flow (q) and density (k) to each other. If two of these variables are known, the third can be derived using the relation q = kv. Therefore, if only one variable is known, and the fundamental diagram is known, the traffic state can be determined. The fundamental relationship is largely used in road infrastructure engineering, e.g. in the level-of-service evaluation of basic freeway or multilane segments. The present work of PhD thesis starts by introducing the fundamental diagram using Edie’s definitions and the use of speed- density diagrams. Another objective will be to analyzed a method that include an automated technique based on genetic algorithm (GA) for automating the process of calibration of the parameters in order to reproduce the fundamentals diagrams of the A22 Brenner freeway. A further important objective will be to evaluate the impact of heavy vehicle on the quality of flow of the A22 Brenner freeway by calculating the Passenger Car Equivalents Factor (PCEs) between heavy vehicles and cars based on the results obtained in microsimulation. The calculation of PCE (Passenger Car Equivalents) will be done in general terms in order to compare the results with those published in the Highway Capacity Manual (HCM, 2010) resulting from experimental studies