Positioning Accuracy of Vehicle Trajectories for Road Applications

Global Navigation Satellite Systems (GNSS) has become a kind of positioning standard due to the high penetration rate of this technology on mass market ITS applications. However, this positioning technique remains a real challenge for very demanding services. This paper reports on a practical and methodological approach for the evaluation of the GNSS positioning and attitude of vehicles in real life conditions. Test scenarios have been set up with several positioning sensors mounted on a vehicle for the collection of raw data on different road sections. The measurement of a high quality reference trajectory allowed to estimate position accuracy under different environmental conditions. We will show in detail the results and identify some typical situations where the quality of GNSS-only positioning is reduced and may impact the level of ITS services, e.g. road user charging or safety applications

Position Accuracy with Redundant MEMS IMU for Road Applications

The diversity of road applications and intelligent transportation systems (ITS) makes the definition of positioning integrity a real challenge because the requirements are changing from one application to another. Even within liability or safety critical applications, the role of positioning may vary if the application layer requires a position at specific location (e.g. emergency call) or a series of positions along a vehicle’s trajectory (e.g. transport of dangerous goods). -- This paper is focusing on the positioning assessment of vehicle trajectories collected by different navigation sensors (GNSS and redundant MEMS Inertial Measurement Units (R-IMU)) in real test scenarios. Single GNSS, integrated GNSS and R-IMU are compared to a high quality ground truth solution based on a high-end navigation system. The low cost equipment is based on a single frequency GNSS receiver combined with four IMUs (triad of accelerometers and gyroscopes) of the same type. The architecture and the algorithms for the sensors integration have been developed at EPFL and are used on several mobile platforms (land vehicles, ultra-light planes, micro-drones). A series of measurements of different kind and thus dynamics have been conducted by EPFL and NTUA during a scientific mission form the COST Action TU1302 on Satellite Positioning Performance Assessment for Road Transport (SaPPART). Several test scenarios were performed in different traffic and environmental conditions in order to face with challenging GNSS signal reception. Road sections have been selected ranging from open sky condition (e.g. rural roads) down to poor GNSS reception (e.g. urban road network). The evaluation of the positioning quality is done by comparing the position-output from several solutions: single GNSS, D-GNSS, integrated GNSS/R-IMU. The comparison to a reference trajectory of precisely time-stamped positions allows to calculate and to plot along-track as well as cross-track differences. This visualisation of the results make sense for many road applications like road user charging (RUC), pay as you drive and some advanced driver assistance systems (ADAS). Finally, this quality assessment of vehicle positioning in real conditions will be a valuable material for future simulations of navigation systems in severe conditions. This contribution is fully adequate to the goals of the COST Action SaPPART, especially for the definition of the performance assessment methodology

SaPPART Guidelines: Assessment of positioning performance in ITS applications

This deliverable, entitled guidelines, is the third outcome of SaPPART COST Action, a European network of scientists and stakeholders that aims to promote smart use of GNSS technology in the field of intelligent road transport and mobility. It discusses the performance assessment of the GNSS-based Positioning terminals (GBPT), which is generally under the responsibility of the system integrators in the road market of GNSS. The aim of this document is to provide guidelines for generic test procedures for the evaluation of GBPT performance, either by field tests, simulations or their combination, compliant with the concepts and the definitions already established in the SaPPART White Paper (TMI 1) and Handbook (TMI 2). The document is intended to provide the reader with a helpful tool for planning the GBPT testing procedures by both discussing the testing in general and by providing some detailed practical information

Impact of public transport strikes on the road network: The case of Athens

Public transport strikes comprise a form of traffic disruption affecting “normal” traveller behaviour, and result in the increase of traffic congestion, traffic accidents and air pollution. Travellers modify their trip characteristics in anticipation of strike effects, while their behaviour depends on various factors including individual characteristics, trip flexibility, available transport modes and attitudes towards them. This study explores the effect of public transport strikes on traffic conditions utilising loop detector data and, in particular, examining the impacts on traffic flow, mean speed and travel time. The city of Athens is used as a reference case. The analysis employs descriptive statistics, as well as the design of generalised linear models to capture the impact of public transport strikes on traffic conditions, and to define the contributing spatio-temporal factors affecting the impacts. Study results highlighted the increase of congestion as expressed through all explored indicators, as a result of the strikes. In particular, increased traffic flow (up to 30%), reduced mean speed (up to 27%) and increased travel times (up to 25%) were observed at the majority of the explored sites. Public transport strike coverage and time of day were found to be the dominant factors. Other contributing factors were found to be day of the week and site-specific characteristics including: the existence of tolls; site location relative to the centre of Athens; and the existence of traffic lights on the explored links. The results of this study can form the basis for the design and implementation of targeted countermeasures that mitigate congestion effects, as well as measures promoting green transport resulting in travellers adopting more sustainable trip routines in the city of Athens

Modelling the Effect of Mobile Phone Use on Driving Behaviour Considering Different Use Modes

Mobile phone use while driving is a major cause of driver distraction, affecting driving performance and increasing accident risk. Governments have responded to this with the implementation of legislation prohibiting the use of mobile phones, under specific conditions, mainly adopting the hands-free use. Still, mobile phone is a cause of several types of distraction rather than just manual. This study explores the effect of mobile phone use while driving via a simulator experiment. Participants drive under various types of mobile phone use mode- namely, handheld, hands-free (wired earphone), and speaker to capture this effect. Results highlight the effect of mobile phone use, regardless of the use mode, on driving behaviour through specific indicators: maximum driving speed, reaction time, and lateral position. In particular, considering the aforementioned parameters the handheld mode demonstrates safer driving behaviour compared to the speaker mode. The results of this study stress the need for a reconsideration of the present legislation

Impact of mobile phone use on driving performance: findings from a simulator study

Mobile phone use while driving is one of the most common driver distractions and one of the main causes of"br" traffic accidents. This research aims to investigate the impact of mobile phone use on drivers’ behaviour in urban"br" and rural road networks. A driving simulator experiment with 50 participants was carried out, who drove under"br" different types of mobile phone distraction (no distraction, handheld conversation, handsfree conversation,"br" speaker mode conversation). Within the framework of the statistical analysis, discrete choice models were"br" designed to investigate the influence of mobile phone use, as well as other relevant parameters, on driving"br" behaviour considering maximum driving speed, reaction time and standard deviation of lateral position. Based"br" on the findings of the present research, mobile phone conversation is significantly affecting driving performance"br" causing lower drivers’ maximum speeds and higher reaction times and standard deviations of the lateral position

Identification of Contributory Factors That Affect the Willingness to Use Shared Autonomous Vehicles

Shared autonomous vehicles (SAVs) aspire to change not only vehicles but also the way people and goods move in urban areas. However, the promotion of such services, that is, whether travelers are willing to share their trips with other service users, is still a challenge. This study aims to examine the contributory factors that influence the willingness of individuals to use shared autonomous vehicles by simultaneously identifying the differences in terms of preferences with conventional competitive transport modes, namely, private cars and public transport. A stated preference experiment combined with perception ratings was designed and conducted in Athens, Greece. Based on the collected responses, a multinomial logit model was estimated. The results show that the flexibility of SAVs and, particularly, the possibility of performing door-to-door trips has a serious added value that travelers are willing to pay. Compared with public transport, additional waiting time does not increase the disutility. Furthermore, people who belong to high-education and -income groups expressed a higher willingness to use SAVs and socialize while traveling. The familiarity of each potential user with technology is a necessary precondition. Lastly, it is confirmed that environmentally conscious people are more positive about using these new services

Prospective and limitations

This article investigates the prospective and limitations in the application of potential intelligent transport system (ITS) functions to reduce accident risks, using a cause‐treatment relationship. The main causes of road accidents are described and appropriate ITS solutions (including advanced driver assistance systems and advanced traveller information systems) are presented as countermeasures. Anticipated impacts are discussed and indicate that several ITS have the potential of improving road safety and addressing specific accident causes. However, attention is required on particular aspects of their implementation as they may trigger adverse effects by imposing behavioural adaptation risks, and overestimation and over‐reliance on system capabilities. Further, user acceptability and strategic implementation issues are paramount to the successful introduction of these systems."b