Microsimulation models incorporating both demand and supply dynamics

There has been rapid growth in interest in real-time transport strategies over the last decade, ranging from automated highway systems and responsive traffic signal control to incident management and driver information systems. The complexity of these strategies, in terms of the spatial and temporal interactions within the transport system, has led to a parallel growth in the application of traffic microsimulation models for the evaluation and design of such measures, as a remedy to the limitations faced by conventional static, macroscopic approaches. However, while this naturally addresses the immediate impacts of the measure, a difficulty that remains is the question of how the secondary impacts, specifically the effect on route and departure time choice of subsequent trips, may be handled in a consistent manner within a microsimulation framework. The paper describes a modelling approach to road network traffic, in which the emphasis is on the integrated microsimulation of individual trip-makers’ decisions and individual vehicle movements across the network. To achieve this it represents directly individual drivers’ choices and experiences as they evolve from day-to-day, combined with a detailed within-day traffic simulation model of the space–time trajectories of individual vehicles according to car-following and lane-changing rules and intersection regulations. It therefore models both day-to-day and within-day variability in both demand and supply conditions, and so, we believe, is particularly suited for the realistic modelling of real-time strategies such as those listed above. The full model specification is given, along with details of its algorithmic implementation. A number of representative numerical applications are presented, including: sensitivity studies of the impact of day-to-day variability; an application to the evaluation of alternative signal control policies; and the evaluation of the introduction of bus-only lanes in a sub-network of Leeds. Our experience demonstrates that this modelling framework is computationally feasible as a method for providing a fully internally consistent, microscopic, dynamic assignment, incorporating both within- and between-day demand and supply dynamic

Estimation and Control of Traffic Relying on Vehicular Connectivity

Vehicular traffic flow is essential, yet complicated to analyze. It describes the interplay among vehicles and with the infrastructure. A better understanding of traf-fic would benefit both individuals and the whole society in terms of improving safety, energy efficiency, and reducing environmental impacts. A large body of research ex-ists on estimation and control of vehicular traffic in which, however, vehicles were assumed not to be able to share information due to the limits of technology. With the development of wireless communication and various sensor devices, Connected Vehicles(CV) are emerging which are able to detect, access, and share information with each other and with the infrastructure in real time. Connected Vehicle Technology (CVT) has been attracting more and more attentions from different fields. The goal of this dissertation is to develop approaches to estimate and control vehicular traffic as well as individual vehicles relying on CVT. On one hand, CVT sig-nificantly enriches the data from individuals and the traffic, which contributes to the accuracy of traffic estimation algorithms. On the other hand, CVT enables commu-nication and information sharing between vehicles and infrastructure, and therefore allows vehicles to achieve better control and/or coordination among themselves and with smart infrastructure. The first part of this dissertation focused on estimation of traffic on freeways and city streets. We use data available from on road sensors and also from probe One of the most important traffic performance measures is travel time. How-ever it is affected by various factors, and freeways and arterials have different travel time characteristics. In this dissertation we first propose a stochastic model-based approach to freeway travel-time prediction. The approach uses the Link-Node Cell Transmission Model (LN-CTM) to model traffic and provides a probability distribu-tion for travel time. The probability distribution is generated using a Monte Carlo simulation and an Online Expectation Maximization clustering algorithm. Results show that the approach is able to generate a reasonable multimodal distribution for travel-time. For arterials, this dissertation presents methods for estimating statistics of travel time by utilizing sparse vehicular probe data. A public data feed from transit buses in the City of San Francisco is used. We divide each link into shorter segments, and propose iterative methods for allocating travel time statistics to each segment. Inspired by K-mean and Expectation Maximization (EM) algorithms, we iteratively update the mean and variance of travel time for each segment based on historical probe data until convergence. Based on segment travel time statistics, we then pro-pose a method to estimate the maximum likelihood trajectory (MLT) of a probe vehicle in between two data updates on arterial roads. The results are compared to high frequency ground truth data in multiple scenarios, which demonstrate the effectiveness of the proposed approach. The second part of this dissertation emphasize on control approaches enabled by vehicular connectivity. Estimation and prediction of surrounding vehicle behaviors and upcoming traffic makes it possible to improve driving performance. We first propose a Speed Advisory System for arterial roads, which utilizes upcoming traffi

2nd Symposium on Management of Future motorway and urban Traffic Systems (MFTS 2018): Booklet of abstracts: Ispra, 11-12 June 2018

The Symposium focuses on future traffic management systems, covering the subjects of traffic control, estimation, and modelling of motorway and urban networks, with particular emphasis on the presence of advanced vehicle communication and automation technologies. As connectivity and automation are being progressively introduced in our transport and mobility systems, there is indeed a growing need to understand the implications and opportunities for an enhanced traffic management as well as to identify innovative ways and tools to optimise traffic efficiency. In particular the debate on centralised versus decentralised traffic management in the presence of connected and automated vehicles has started attracting the attention of the research community. In this context, the Symposium provides a remarkable opportunity to share novel ideas and discuss future research directions.JRC.C.4-Sustainable Transpor

Alternative vehicle electronic architecture for individual wheel control

Electronic control systems have become an integral part of the modern vehicle and their installation rate is still on a sharp rise. Their application areas range from powertrain, chassis and body control to entertainment. Each system is conventionally control led by a centralised controller with hard-wired links to sensors and actuators. As systems have become more complex, a rise in the number of system components and amount of wiring harness has followed. This leads to serious problems on safety, reliability and space limitation. Different networking and vehicle electronic architectures have been developed by others to ease these problems. The thesis proposes an alternative architecture namely Distributed Wheel Architecture, for its potential benefits in terms of vehicle dynamics, safety and ease of functional addition. The architecture would have a networked controller on each wheel to perform its dynamic control including braking, suspension and steering. The project involves conducting a preliminary study and comparing the proposed architecture with four alternative existing or high potential architectures. The areas of study are functionality, complexity, and reliability. Existing ABS, active suspension and four wheel steering systems are evaluated in this work by simulation of their operations using road test data. They are used as exemplary systems, for modelling of the new electronic architecture together with the four alternatives. A prediction technique is developed, based on the derivation of software pseudo code from system specifications, to estimate the microcontroller specifications of all the system ECUs. The estimate indicates the feasibility of implementing the architectures using current microcontrollers. Message transfer on the Controller Area Network (CAN) of each architecture is simulated to find its associated delays, and hence the feasibility of installing CAN in the architectures. Architecture component costs are estimated from the costs of wires, ECUs, sensors and actuators. The number of wires is obtained from the wiring models derived from exemplary system data. ECU peripheral component counts are estimated from their statistical plot against the number of ECU pins of collected ECUs. Architecture component reliability is estimated based on two established reliability handbooks. The results suggest that all of the five architectures could be implemented using present microcontrollers. In addition, critical data transfer via CAN is made within time limits under current levels of message load, indicating the possibility of installing CAN in these architectures. The proposed architecture is expected to· be costlier in terms of components than the rest of the architectures, while it is among the leaders for wiring weight saving. However, it is expected to suffer from a relatively higher probability of system component failure. The proposed architecture is found not economically viable at present, but shows potential in reducing vehicle wire and weight problems

The mobility of older people, and the future role of Connected Autonomous Vehicles

This report was produced in the ‘Flourish’ Project, a successful participant in Innovate UK’s Connected and Autonomous Vehicles Collaboration Research & Development competition. Flourish set out to identify innovative solutions that address two distinct but related topics within the connected and autonomous vehicle (CAV) market which are seen to help realise market readiness of CAVs in the UK. Firstly, customer Interaction focusing on the customers’ needs and experience when using the technology; and secondly connectivity focusing on effective data analytics and ensuring that the cyber security and wireless connectivity elements of CAVs are safe by design.Older adults with ageing-related impairments were seen to be particular beneficiaries of CAV technology, allowing them to continue to be active contributors to the economy and society. As a result the project has focussed on the needs of this group, hopefully accelerating their ability to become early adopters of CAVs. It is expected that by addressing the needs of older people that the knowledge, services and capabilities that will be developed will also be exploitable by other age groups. Consequently, the key objective for this review was to develop an understanding and articulation of current mobility needs, any existing experience of CAV (or components of it) and older people’s future expectations of CAVs in respect of their mobility

Implicit personalization in driving assistance: State-of-the-art and open issues

In recent decades, driving assistance systems have been evolving towards personalization for adapting to different drivers. With the consideration of driving preferences and driver characteristics, these systems become more acceptable and trustworthy. This article presents a survey on recent advances in implicit personalized driving assistance. We classify the collection of work into three main categories: 1) personalized Safe Driving Systems (SDS), 2) personalized Driver Monitoring Systems (DMS), and 3) personalized In-vehicle Information Systems (IVIS). For each category, we provide a comprehensive review of current applications and related techniques along with the discussion of industry status, benefits of personalization, application prospects, and future focal points. Both relevant driving datasets and open issues about personalized driving assistance are discussed to facilitate future research. By creating an organized categorization of the field, we hope that this survey could not only support future research and the development of new technologies for personalized driving assistance but also facilitate the application of these techniques within the driving automation community</h2

Ergonomics of intelligent vehicle braking systems

The present thesis examines the quantitative characteristics of driver braking and pedal operation and discusses the implications for the design of braking support systems for vehicles. After the current status of the relevant research is presented through a literature review, three different methods are employed to examine driver braking microscopically, supplemented by a fourth method challenging the potential to apply the results in an adaptive brake assist system. First, thirty drivers drove an instrumented vehicle for a day each. Pedal inputs were constantly monitored through force, position sensors and a video camera. Results suggested a range of normal braking inputs in terms of brake-pedal force, initial brake-pedal displacement and throttle-release (throttle-off) rate. The inter-personal and intra-personal variability on the main variables was also prominent. [Continues.