Towards sustainable transport: wireless detection of passenger trips on public transport buses

An important problem in creating efficient public transport is obtaining data about the set of trips that passengers make, usually referred to as an Origin/Destination (OD) matrix. Obtaining this data is problematic and expensive in general, especially in the case of buses because on-board ticketing systems do not record where and when passengers get off a bus. In this paper we describe a novel and inexpensive system that uses off-the-shelf Bluetooth hardware to accurately record passenger journeys. Here we show how our system can be used to derive passenger OD matrices, and additionally we show how our data can be used to further improve public transport services.Comment: 13 pages, 4 figures, 1 tabl

A Policeless traffic ticketing system with autonomous vehicles

Besides being expensive, traffic violation monitoring systems rely heavily on a huge infrastructure that incurs installation, operational, and maintenance costs. Developing countries — where people do exhibit less traffic safety aware- ness — deployment of such systems becomes a daunting task. A police- men cannot be everywhere, and a policeman can also be bribed. With the above goals in mind, in this paper we present an infrastructure- less and police-less traffic violation detection system that relies solely on the broadcast messages between the vehicles and secure communication of the vehicles with the transportation authority. Each vehicle should be equipped with a small board box (or a smartphone) with a wifi antenna and 3G capability and subscription. The system is highly scalable and can include pedestrians with smartphones. It is active and operational wherever and whenever there are two participants in the range of each other. Each participant has two roles to bear simultaneously. The first one is to report and prove its location to the transportation authority. The second one is to report the presence of other vehicles in the neighborhood to the transportation authority and flag those that disobey the traffic rules acting as trustworthy and anonymous witnesses. This is a preliminary report on a still ongoing research project

Automatic Recognition of Public Transport Trips from Mobile Device Sensor Data and Transport Infrastructure Information

Automatic detection of public transport (PT) usage has important applications for intelligent transport systems. It is crucial for understanding the commuting habits of passengers at large and over longer periods of time. It also enables compilation of door-to-door trip chains, which in turn can assist public transport providers in improved optimisation of their transport networks. In addition, predictions of future trips based on past activities can be used to assist passengers with targeted information. This article documents a dataset compiled from a day of active commuting by a small group of people using different means of PT in the Helsinki region. Mobility data was collected by two means: (a) manually written details of each PT trip during the day, and (b) measurements using sensors of travellers' mobile devices. The manual log is used to cross-check and verify the results derived from automatic measurements. The mobile client application used for our data collection provides a fully automated measurement service and implements a set of algorithms for decreasing battery consumption. The live locations of some of the public transport vehicles in the region were made available by the local transport provider and sampled with a 30-second interval. The stopping times of local trains at stations during the day were retrieved from the railway operator. The static timetable information of all the PT vehicles operating in the area is made available by the transport provider, and linked to our dataset. The challenge is to correctly detect as many manually logged trips as possible by using the automatically collected data. This paper includes an analysis of challenges due to missing or partially sampled information in the data, and initial results from automatic recognition using a set of algorithms. Improvement of correct recognitions is left as an ongoing challenge.Comment: 22 pages, 7 figures, 10 table

A stochastic model of randomly accelerated walkers for human mobility

The recent availability of large databases allows to study macroscopic properties of many complex systems. However, inferring a model from a fit of empirical data without any knowledge of the dynamics might lead to erroneous interpretations [6]. We illustrate this in the case of human mobility [1-3] and foraging human patterns [4] where empirical long-tailed distributions of jump sizes have been associated to scale-free super-diffusive random walks called L\'evy flights [5]. Here, we introduce a new class of accelerated random walks where the velocity changes due to acceleration kicks at random times, which combined with a peaked distribution of travel times [7], displays a jump length distribution that could easily be misinterpreted as a truncated power law, but that is not governed by large fluctuations. This stochastic model allows us to explain empirical observations about the movements of 780,000 private vehicles in Italy, and more generally, to get a deeper quantitative understanding of human mobility.Comment: 10 pages, 6 figures + Supplementary informatio

Application of Geomatic techniques in Infomobility and Intelligent Transport Systems (ITS)

During last years, we assisted to an increment of mobility demand, implying the need of adequate infrastructure and efficient public transport. The deployment of informative services and Intelligent Transport Systems (ITS) assumed a fundamental importance to address mobility demand, strictly correlated to the territory characteristics. At the same time, mature Geomatic technologies, especially related to GPS differential positioning (both in real time and in post processing), mobile mapping systems (MMS), remotely sensed imageries (aerial, satellite and UAV platforms), archiving and management systems (Spatial Data Infrastructure - SDI) will play a crucial role. These applications to infomobility and ITS are described in this paper

ATG-PVD: Ticketing Parking Violations on A Drone

In this paper, we introduce a novel suspect-and-investigate framework, which can be easily embedded in a drone for automated parking violation detection (PVD). Our proposed framework consists of: 1) SwiftFlow, an efficient and accurate convolutional neural network (CNN) for unsupervised optical flow estimation; 2) Flow-RCNN, a flow-guided CNN for car detection and classification; and 3) an illegally parked car (IPC) candidate investigation module developed based on visual SLAM. The proposed framework was successfully embedded in a drone from ATG Robotics. The experimental results demonstrate that, firstly, our proposed SwiftFlow outperforms all other state-of-the-art unsupervised optical flow estimation approaches in terms of both speed and accuracy; secondly, IPC candidates can be effectively and efficiently detected by our proposed Flow-RCNN, with a better performance than our baseline network, Faster-RCNN; finally, the actual IPCs can be successfully verified by our investigation module after drone re-localization.Comment: 17 pages, 11 figures and 3 tables. This paper is accepted by ECCV Workshops 202

Utilization of evacuation model for airports using risk based fire safety scenario

This report focuses the use of egress models to study the airport evacuation with special focus on security doors in case of total evacuation in airport terminal buildings. Case studies are made in arrival hall and departure hall of the airport terminal based on the scenarios identified in a preliminary risk analysis carried out in the terminal. Evacuation strategies are employed in the two different cases to study the evacuation based on the one way flow and counter-flow through security doors. This report presents the generalized method of designing an airport terminal based on the design peak hour passengers and the risk based fire safety method to identify the high fire risk locations with respect to the occupant evacuation safety. The evacuation strategies have been modeled in two simulation software tools (Pathfinder and LegionEvac) to compare the total evacuation time. The comparison between the models is discussed based on the total evacuation time. Based on the evacuation time, further evacuation strategies are simulated to study the flow pattern and evacuation problems with respect to airport environment. In the result section, critical factors which affect the airport evacuation and suggestion for optimization is discussed

A Policeless traffic ticketing system with autonomous vehicles

Besides being expensive, traffic violation monitoring systems rely heavily on a huge infrastructure that incurs installation, operational, and maintenance costs. Developing countries — where people do exhibit less traffic safety aware- ness — deployment of such systems becomes a daunting task. A police- men cannot be everywhere, and a policeman can also be bribed. With the above goals in mind, in this paper we present an infrastructure- less and police-less traffic violation detection system that relies solely on the broadcast messages between the vehicles and secure communication of the vehicles with the transportation authority. Each vehicle should be equipped with a small board box (or a smartphone) with a wifi antenna and 3G capability and subscription. The system is highly scalable and can include pedestrians with smartphones. It is active and operational wherever and whenever there are two participants in the range of each other. Each participant has two roles to bear simultaneously. The first one is to report and prove its location to the transportation authority. The second one is to report the presence of other vehicles in the neighborhood to the transportation authority and flag those that disobey the traffic rules acting as trustworthy and anonymous witnesses. This is a preliminary report on a still ongoing research project

Multifaceted Faculty Network Design and Management: Practice and Experience Report

We report on our experience on multidimensional aspects of our faculty's network design and management, including some unique aspects such as campus-wide VLANs and ghosting, security and monitoring, switching and routing, and others. We outline a historical perspective on certain research, design, and development decisions and discuss the network topology, its scalability, and management in detail; the services our network provides, and its evolution. We overview the security aspects of the management as well as data management and automation and the use of the data by other members of the IT group in the faculty.Comment: 19 pages, 11 figures, TOC and index; a short version presented at C3S2E'11; v6: more proofreading, index, TOC, reference

Motion Hub, the implementation of an integrated end-to-end journey planner

© AET 2018 and contributorsThe term “eMobility” and been brought into use partly to encourage use of electric vehicles but more especially to focus on the transformation from electric vehicles as products to electrified personal transport as a service. Under the wider umbrella of Mobility-as-a-Service (MaaS) this has accompanied the growth of car clubs in general. The Motion Hub project has taken this concept a step further to include not just the car journey but the end-to-end journey. The booking of multifaceted journeys is well established in the leisure and business travel industries, where flights, car hire and hotels are regularly booked with a single transaction on a website. To complete an end-to-end scenario Motion Hub provides integration of public transport with electric vehicle and electric bike use. Building on a previous InnovateUK funded project that reviewed the feasibility of an integrated journey management system, the Motion Hub project has brought together a Car Club, a University, and EV infrastructure company, a bicycle hire company with electric bicycle capabilities and a municipality to implement a scheme and test it on the ground. At the heart of the project has been the development of a website that integrates the public transport booking with the hire of electric vehicles or bicycles. Taking the implementation to a fully working system accessible to members of the public presents a number of significant challenges. This paper identifies those challenges, details the progress and success of the Motion Hub and sets out the lessons learnt about end-to-end travel. The project was fortunate to have as its municipal partner the Council of a sizeable South East England town, Southend-on-Sea. With a population of 174,800 residents with good road, rail and air links there is considerable traffic in and out of the town. The Council has already shown its commitment to sustainable transport. In the previous six years it had installed a number of electric vehicle charging points for use by the public and latterly had trialled car club activity. An early challenge in the project was the location of physical infrastructure in an already crowded municipal space in order to provide the local ‘spokes’ of the system. In addition to its existing charging points, Southend now has four locations where electric cars can be hired, five where electric bikes are available and the local resources to maintain these assets. Combining a number of web-based services and amalgamating their financial transactions is relatively straightforward. However, introducing the potential for public transport ticketing as well raises additional security, scale and financial constraints. The project has engaged with major players and regulators across the public transport industry.Peer reviewe