Current paradigms in intelligent transportation systems

Intelligent transportation systems (ITS) constitute today a multidisciplinary field of study involving a large number of different research areas. As a consequence, it is difficult to achieve a structured view of ITS, which is necessary to unify efforts and as guidance for future developments. This study aims to identify the main paradigms in the field of ITS by semantically analysing studies related to this general topic. An understanding about which research is considered valuable by the research community to build upon may provide valuable insights in this field. As a result of the statistical treatment of data, up to 13 paradigms are obtained. The scope of these paradigms and the relationships between them have also been detailed, providing a structured vision of ITS synthesised in a map formMinisterio de Educación y Ciencia DPI2007- 60128Junta de Andalucía. Consejería de Innovación, Ciencia y Empresa P07-TIC-0262

Route planning methodology of an advanced traveller information system in Vilnius city

As a subsystem of an Intelligent Transportation System (ITS), an Advanced Traveller Information System (ATIS) disseminates real‐time traffic information to travellers. To help them with making better decisions on choosing their routes, a strong need to predict traffic congestion and to disseminate the predicted congestion information relating to travellers can be seen. This paper describes a methodology used by drivers for calculating an optimal driven route in Vilnius. The paper discusses how ATIS systems will likely evolve the experience of Information Service Providers (ISP) and optimal route planning calculations. A few methods of route planning have been taken into account. The paper presents the following types of route calculation: 1) the shortest route; 2) the quickest route; 3) the quickest forecasted route according to historical traffic information. Also, the paper deals with the architecture of the WEB based information system for drivers in Vilnius and analyzes data on traffic workflow. Furthermore, a comprehensive route planning procedure that forecasts data on driving time considering historical traffic is followed. First published online: 27 Oct 201

Integration of Real-time Traffic State Estimation and Dynamic Traffic Assignment with Applications to Advanced Traveller Information Systems

Accurate depiction of existing traffic states is essential to devise effective real-time traffic management strategies using Intelligent Transportation Systems (ITS). Existing applications of Dynamic Traffic Assignment (DTA) methods are mainly based on either the prediction from macroscopic traffic flow models or measurements from the sensors and do not take advantage of traffic state estimation techniques, which produce estimate of the traffic states with less uncertainty than the prediction or measurement alone. On the other hand, research studies highlighting estimation of real-time traffic state are focused only on traffic state estimation and have not utilized the estimated traffic state for DTA applications. This research introduces a framework which integrates real-time traffic state estimate with applications of DTA to optimize network performance during uncertain traffic conditions through traveller information system. The estimate of real-time traffic states is obtained by combining the prediction of traffic density using Cell Transmission Model (CTM) and the measurements from the traffic sensors in Extended Kalman Filter (EKF) recursive algorithm. The estimated traffic state is used for predicting travel times on available routes in a traffic network and the predicted travel times are communicated to the commuters by a variable message sign (VMS). In numerical experiments, the proposed estimation and information framework is applied to optimize network performance during traffic incident on a two route network. The proposed framework significantly improved the network performance and commuters’ travel time when compared with no-information scenario during the incident. The application of the formulated methodology is extended to model day-to-day dynamics of traffic flow and route choice with time-varying traffic demand. The day-to-day network performance is improved by providing accurate and reliable traveller information. The implementation of the proposed framework through numerical experiments shows a significant improvement in daily travel times and stability in day-to-day performance of the network when compared with no-information scenario. The use of model based real-time traffic state estimation in DTA models allows modelling and estimating behaviour parameters in DTA models which improves the accuracy of the modelling process. In this research, a framework is proposed to model commuters’ level of trust in the information provided which defines the weight given to the information by commuters while they update their perception about expected travel time. A methodology is formulated to model and estimate logit parameter for perception variation among commuters for expected travel time based on measurements from traffic sensors and estimated traffic state. The application of the proposed framework to a test network shows that the model accurately estimated the value of logit parameter when started with a different initial value of the parameter

Simulating Drivers' Decision-making Under Information Dissemination

Nos dias de hoje, informação de trânsito precisa e actualizada é bastante importante para os viajantes chegarem ao seu destino mais rápido e em segurança. É neste aspecto que os Sistemas de Informação ao Viajante ou Advanced Travellers Information Systems (ATIS), se inserem nos Sistemas Inteligentes de Transporte. Tirando partido das novos serviços Web e tecnologias wireless de comunicação estes sistemas fornecem informação valiosa antes, durante e até após a viagem, sendo, sistemas que recolhem, analisam e transmitem informação útil para os viajantes.O objectivo deste trabalho é analisar o comportamento dos condutores num meio com disseminação de informação. Assim, será necessário criar uma plataforma que possibilite a implementação de condutores e infraestruturas de gestão e controlo utilizado os Sistemas Multi-Agente (MAS) como paradigma de modelação para a criação da nossa sociedade artificial e como paradigma de programação no aspecto de análise e simulação de todo o processo

The development of a generic step-wise framework for achieving a multimodal platform in a development country environement

Paper presented at the 33rd Annual Southern African Transport Conference 7-10 July 2014 "Leading Transport into the Future", CSIR International Convention Centre, Pretoria, South Africa.With information and technology becoming such a vital commodity in everyday life, it can be argued that informed travellers are the key to successful future transport services. Fortunately, it is recognised that the development of a multimodal transport system is needed in providing integrated traveller information. The relating challenges and the applicable considerations in attaining such an integrated system were researched. Following from this, a generic sequential framework that facilitates multimodal data integration and traveller information as a precursor to a fully integrated multimodal system was developed. In this framework four focus areas, related to the implementation requirements of the application environment considered, were identified. These areas are based on the premise that current technological evolvements need to be exploited in order to breach the missing intelligent link between the various application environments. The focus areas are: 1) the multimodal transport network and the design and modelling thereof, 2) the role of Intelligent Transport Systems (ITS) in achieving a multimodal platform, 3) the need for and the design criteria of a centralised database, and 4) the need for and the travel information requirements of a multimodal Journey Planner (JP). The establishment of such a concise framework (along with its associated steps in attaining multimodal information) will go a long way towards providing the impetus, and eradicate the barriers, in achieving sustainable traveller information services. Ideally, South Africa (SA) will be able to empower a better transport service that spans across the nation’s social barriers.This paper was transferred from the original CD ROM created for this conference. The material was published using Adobe Acrobat 10.1.0 Technology. The original CD ROM was produced by CE Projects cc. Postal Address: PO Box 560 Irene 0062 South Africa. Tel.: +27 12 667 2074 Fax: +27 12 667 2766 E-mail: [email protected]

Strategic Trip Planning: Striking a Balance Between Competition and Cooperation

In intelligent transportation systems, cooperative mobility planning is considered to be one of the challenging problems. Mobility planning as it stands today is an in- dividual decision-making effort that takes place in an environment governed by the collective actions of various competing travellers. Despite the extensive research on mobility planning, a situation in which multiple behavioural-driven travellers partic- ipate in a cooperative endeavour to help each other optimize their objectives has not been investigated. Furthermore, due to the inherent multi-participant nature of the mobility problem, the existing solutions fail to produce ground truth optimal mobil- ity plans in the practical sense - despite their claimed and well proven theoretical optimality. This thesis proposes a multi-module team mobility planning framework to address the team trip planning problem with a particular emphasis on modelling the inter- action between behaviour-driven rational travellers. The framework accommodates the travellers’ individual behaviours, preferences, and goals in cooperative and com- petitive scenarios. The individual behaviours of the travellers and their interaction processes are viewed as a team trip planning game. For this game, a theoretical anal- ysis is presented, which includes an analysis of the existence and the balancedness of the final solution. The proposed framework is composed of three principal modules: cooperative trip planning, team formation, and traveller-centric trip planning (TCTP). The cooper- ative trip planning module deploys a bargaining model to manage conflicts between the travellers that could occur in their endeavour to discover a general, satisfactory solution. The number of players and their interaction process is controlled by the team formation module. The TCTP module adopts an alternative perspective to the individualized trip-planning problem in the sense that it is being behavioural driven problem. This allows for multitudes of traveler centric objectives and constraints, as well as aspects of the environment as they pertain to the traveller’s preferences, to be incorporated in the process. Within the scope of the team mobility planning frame- work, the TCTP is utilized to supply the travellers with personalized strategies that are incorporated in the cooperative game. The concentration problem is used in this thesis to demonstrate the effectiveness of the TCTP module as a behavioural-driven trip planner. Finally, to validate the theoretical set-up of the team trip planning game, we introduce the territory sharing problem for social taxis. We use the team mobility framework as a basis to solve the problem. Furthermore, we present an argument for the convergence and the efficiency of a coarse correlated equilibrium. In addition to the validation of a variety of theoretical concepts, the territory sharing problem is used to demonstrate the applicability of the proposed framework in dealing with cooperative mobility planning problems

Optimizing Transportation Systems with Information Provision, Personalized Incentives and Driver Cooperation

Poor performance of the transportation systems has many detrimental effects such as higher travel times, increased travel costs, higher energy consumption, and greenhouse gas emissions, etc. This thesis optimizes the transportation systems by addressing the traffic congestion problem and climate change impact resulting from the inefficient operation of these systems. I first focus on the key player of the transportation systems e.g., human being/traveler, and model travelers\u27 route choice behavior with real-time information. In this study, I define looking-ahead behavior in route choice as a traveler\u27s taking into account future diversion possibilities enabled by real-time information in a network with random travel times. Subjects participated in route-choice experiments in a driving simulator as well a PC-based environment. Three types of maps in increasing levels of complexity and information availability are used. Aggregate data analysis shows that network complexity negatively affects subjects\u27 ratio of choosing the risky route given an experiment environment. Higher cognitive load in the driving simulator results in a higher level of risk aversion than in the PC-based environment for the simplest map. I specify and estimate a mixed logit model with two latent classes, looking-ahead and myopic, taking into account the panel effect. The estimated latent class membership function suggests that some subjects can look ahead while others are myopic in making their route choices, and drivers learn to look ahead over time. The experiment environment plays a role in the risk attitude of myopic subjects. A bias against information is found for subjects who look ahead, however, is not significant among myopic subjects. I then shift my focus to influencing the travel patterns of individual travelers to reduce the energy and environmental impacts of the transportation sector. I present the system optimization (SO) framework of Tripod, an integrated bi-level transportation management system aimed at maximizing energy savings of the multi-modal transportation systems. From the user\u27s perspective, Tripod is a smartphone app, accessed before performing trips. The app proposes a series of alternatives each with an amount of tokens which the user can later redeem for goods or services. The role of SO is to compute the optimized set of tokens associated to the available alternatives, in order to minimize the system-wide energy consumption, under a limited token budget. I present a method to solve this complex optimization problem and describe the system architecture, the multimodal simulation-based optimization model and the heuristic method for the on-line computation of the optimized token allocation. I then present the framework with the simulation results. Finally, I optimize the systems travel time by addressing the equity issue of congestion pricing. I propose an alternative approach to an equitable and Pareto-improving transportation systems based on cooperation among travelers assisted by defector penalty. Theoretical analysis shows the existence condition of the cooperative scheme for heterogeneous value of time (VOT) of travelers. I formulate a mathematical programming problem for the optimal cooperative scheme problem in a general network with Pareto-improving constraints and practical considerations on the length the cooperation cycle. I then conduct computational tests on a simple network and evaluate the solutions in terms of efficiency improvement (total system travel time) and equitability (Gini index)

A dynamic route choice model for public transport networks with boarding queues

The concepts of optimal strategy and hyperpath were born within the framework of static frequency-based public transport assignment, where it is assumed that travel times and frequencies do not change over time and no overcrowding occurs. However, the formation of queues at public transport stops can prevent passengers from boarding the first vehicle approaching and can thus lead to additional delays in their trip. Assuming that passengers know from previous experience that for certain stops/lines they will have to wait for the arrival of the 2nd, 3rd, …, k-th vehicle, they may alter their route choices, thus resulting in a different assignment of flows across the network. The aim of this paper is to investigate route choice behaviour changes as a result of the formation and dispersion of queues at stops within the framework of optimal travel strategies. A new model is developed, based on modifications of existing algorithms