Quiet paths for people : developing routing analysis and Web GIS application

Altistuminen saasteille saattaa vähentää merkittävästi aktiivisten liikkumismuotojen, kuten kävelyn ja pyöräilyn terveyshyötyjä. Yksi liikenteestä johtuvista saasteista on melu, joka voi aiheuttaa terveyshaittoja, kuten kohonnutta verenpainetta ja stressiä. Aikaisemmissa tutkimuksissa ja selvityksissä melulle altistumista on arvioutu yleensä kotipaikan suhteen ja liikkumisen aikana tapahtuva altistus on jäänyt vähemmälle huomiolle. Koska liikkumisen aikainen (dynaaminen) melualtistus saattaa muodostaa merkittävän oan kaupunkilaisten päivittäisestä kokonaismelualtistuksesta, tarvitaan kehittyneempiä menetelmiä dynaamisen melualtistuksen arvioimiseen ja vähentämiseen. Tässä tutkielmassa kehitin kävelyn reititysmenetelmän ja sovelluksen, jolla voi 1) etsiä lyhimmän reitin, 2) mallintaa kävelyn aikaisen melualtistuksen ja 3) löytää vaihtoehtoisia, hiljaisempia reittejä. Sovellus hyödyntää OpenStreetMap-tieverkostoaineistoa ja mallinnettua aineistoa tieliikenteen tyypillisistä päiväajan melutasoista. Reitinetsintä perustuu kehittämääni melukustannusfunktioon ja alhaisimman kustannuksen reititysanalyysiin. Melukustannukset lasketaan sovelluksessa lukuisilla eri meluherkkyyskertoimilla, minkä ansiosta sovellus löytää useita vaihtoehtoisia (hiljaisempia) reittejä. Jotta eri reittien meluisuutta (melualtistuksia) voidaan vertailla, kehitin sarjan melualtistusindeksejä. Tapaustutkimuksessa tutkin Helsingistä tehtävien työmatkojen aikaisia melualtistuksia; selvitin rekistereihin perustuvien työmatkojen mukaiset joukkoliikennereitit ja tutkin reittien kävelyosuuksien aikaisia melualtistuksia reitittämällä kävelyreitit uudestaan kehittämälläni reitityssovelluksella. Lisäksi tutkin hiljaisempien reittivaihtoehtojen mahdollistamia vähennyksiä melualtistuksissa tapaustutkimuksessa mallinnetuilla kävelyreiteillä. Tapaustutkimuksen tulokset indikoivat, että tyypilliset dynaamiset melualtistukset vaihtelevat huomattavasti eri asuinpaikkojen välillä. Toisaalta merkittävä osa melulle altistumisesta on mahdollista välttää hiljaisemmilla reittivaihtoehdoilla; tilanteesta riippuen, hiljaisemmat reitit tarjoavat keskimäärin 12–57 % vähennyksen altistuksessa yli 65 dB melutasoille ja 1.6–9.6 dB keskimääräisen vähennyksen reittien keskimääräisessä melutasossa. Altistuksen mahdolliseen vähennykseen näyttäisivät vaikuttavan ainakin 1) melualtistuksen suuruus lyhimmällä (ts. verrokki) reitillä, 2) lyhimmän reitin pituus, eli etäisyys lähtö- ja kohdepisteen välillä reititysgraafissa ja 3) hiljaisemman reitin pituus lyhimpään reittiin verrattuna. Julkaisin hiljaisten kävelyreittien reitityssovelluksen avoimena web-rajapintapalveluna (API - Application Programming Interface) ja kehitin hiljaisten kävelyreittien reittioppaan mobiilioptimoituna web-karttasovelluksena. Kaikki tutkielmassa kehitetyt menetelmät ja lähdekoodit ovat avoimesti saatavilla GitHub-palvelussa. Yksilöiden ja kaupunkisuunnittelijoiden tietoutta dynaamisesta altistuksesta melulle (ja muille saasteille) tulisi lisätä kehittämällä altistusten arviointiin ja vähentämiseen kehittyneempiä analyyseja ja sovelluksia. Tässä tutkielmassa kehitetty web-karttasovellus havainnollistaa hiljaisten reittien reititysmenetelmän toimivuutta tosielämän tilanteissa ja voi näin ollen auttaa jalankulkijoita löytämään hiljaisempia, ja siten terveellisempiä, reittivaihtoehtoja. Kun ympäristöllisiin altistuksiin perustuvaa reitinetsintää kehitetään pidemmälle, tulisi pyrkiä huomioimaan useampia erillisiä altistuksia samanaikaisesti ja siten reitittämään yleisesti ottaen terveellisempiä reittejä.It is likely that journey-time exposure to pollutants limit the positive health effects of active transport modes (e.g. walking and cycling). One of the pollutants caused by vehicular traffic is traffic noise, which is likely to cause various negative health effects such as increased stress levels and blood pressure. In prior studies, individuals’ exposure to community noise has usually been assessed only with respect to home location, as required by national and international policies. However, these static exposure assessments most likely ignore a substantial share of individuals’ total daily noise exposure that occurs while they are on the move. Hence, new methods are needed for both assessing and reducing journey-time exposure to traffic noise as well as to other pollutants. In this study, I developed a multifunctional routing application for 1) finding shortest paths, 2) assessing dynamic exposure to noise on the paths and 3) finding alternative, quieter paths for walking. The application uses street network data from OpenStreetMap and modeled traffic noise data of typical daytime traffic noise levels. The underlying least cost path (LCP) analysis employs a custom-designed environmental impedance function for noise and a set of (various) noise sensitivity coefficients. I defined a set of indices for quantifying and comparing dynamic (i.e. journey-time) exposure to high noise levels. I applied the developed routing application in a case study of pedestrians’ dynamic exposure to noise on commuting related walks in Helsinki. The walks were projected by carrying out an extensive public transport itinerary planning on census based commuting flow data. In addition, I assessed achievable reductions in exposure to traffic noise by taking quieter paths with statistical means by a subset of 18446 commuting related walks (OD pairs). The results show significant spatial variation in average dynamic noise exposure between neighborhoods but also significant achievable reductions in noise exposure by quieter paths; depending on the situation, quieter paths provide 12–57 % mean reduction in exposure to noise levels higher than 65 dB and 1.6–9.6 dB mean reduction in mean dB (compared to the shortest paths). At least three factors seem to affect the achievable reduction in noise exposure on alternative paths: 1) exposure to noise on the shortest path, 2) length of the shortest path and 3) length of the quiet path compared to the shortest path. I have published the quiet path routing application as a web-based quiet path routing API (application programming interface) and developed an accompanying quiet path route planner as a mobile-friendly web map application. The online quiet path route planner demonstrates the applicability of the quiet path routing method in real-life situations and can thus help pedestrians to choose quieter paths. Since the quiet path routing API is open, anyone can query short and quiet paths equipped with attributes on journey-time exposure to noise. All methods and source codes developed in the study are openly available via GitHub. Individuals’ and urban planners’ awareness of dynamic exposure to noise and other pollutants should be further increased with advanced exposure assessments and routing applications. Web-based exposure-aware route planner applications have the potential to help individuals to choose alternative, healthier paths. When developing exposure-based routing analysis further, attempts should be made to enable simultaneously considering multiple environmental exposures in order to find overall healthier paths

CT-Mapper: Mapping Sparse Multimodal Cellular Trajectories using a Multilayer Transportation Network

Mobile phone data have recently become an attractive source of information about mobility behavior. Since cell phone data can be captured in a passive way for a large user population, they can be harnessed to collect well-sampled mobility information. In this paper, we propose CT-Mapper, an unsupervised algorithm that enables the mapping of mobile phone traces over a multimodal transport network. One of the main strengths of CT-Mapper is its capability to map noisy sparse cellular multimodal trajectories over a multilayer transportation network where the layers have different physical properties and not only to map trajectories associated with a single layer. Such a network is modeled by a large multilayer graph in which the nodes correspond to metro/train stations or road intersections and edges correspond to connections between them. The mapping problem is modeled by an unsupervised HMM where the observations correspond to sparse user mobile trajectories and the hidden states to the multilayer graph nodes. The HMM is unsupervised as the transition and emission probabilities are inferred using respectively the physical transportation properties and the information on the spatial coverage of antenna base stations. To evaluate CT-Mapper we collected cellular traces with their corresponding GPS trajectories for a group of volunteer users in Paris and vicinity (France). We show that CT-Mapper is able to accurately retrieve the real cell phone user paths despite the sparsity of the observed trace trajectories. Furthermore our transition probability model is up to 20% more accurate than other naive models.Comment: Under revision in Computer Communication Journa

3D oceanographic data compression using 3D-ODETLAP

This paper describes a 3D environmental data compression technique for oceanographic datasets. With proper point selection, our method approximates uncompressed marine data using an over-determined system of linear equations based on, but essentially different from, the Laplacian partial differential equation. Then this approximation is refined via an error metric. These two steps work alternatively until a predefined satisfying approximation is found. Using several different datasets and metrics, we demonstrate that our method has an excellent compression ratio. To further evaluate our method, we compare it with 3D-SPIHT. 3D-ODETLAP averages 20% better compression than 3D-SPIHT on our eight test datasets, from World Ocean Atlas 2005. Our method provides up to approximately six times better compression on datasets with relatively small variance. Meanwhile, with the same approximate mean error, we demonstrate a significantly smaller maximum error compared to 3D-SPIHT and provide a feature to keep the maximum error under a user-defined limit

The Merits of Sharing a Ride

The culture of sharing instead of ownership is sharply increasing in individuals behaviors. Particularly in transportation, concepts of sharing a ride in either carpooling or ridesharing have been recently adopted. An efficient optimization approach to match passengers in real-time is the core of any ridesharing system. In this paper, we model ridesharing as an online matching problem on general graphs such that passengers do not drive private cars and use shared taxis. We propose an optimization algorithm to solve it. The outlined algorithm calculates the optimal waiting time when a passenger arrives. This leads to a matching with minimal overall overheads while maximizing the number of partnerships. To evaluate the behavior of our algorithm, we used NYC taxi real-life data set. Results represent a substantial reduction in overall overheads

Application-based COVID-19 micro-mobility solution for safe and smart navigation in pandemics

Short distance travel and commute being inevitable, safe route planning in pandemics for micro-mobility, i.e., cycling and walking, is extremely important for the safety of oneself and others. Hence, we propose an application-based solution using COVID-19 occurrence data and a multi-criteria route planning technique for cyclists and pedestrians. This study aims at objectively determining the routes based on various criteria on COVID-19 safety of a given route while keeping the user away from potential COVID-19 transmission spots. The vulnerable spots include places such as a hospital or medical zones, contained residential areas, and roads with a high connectivity and influx of people. The proposed algorithm returns a multi-criteria route modeled on COVID-19-modified parameters of micro-mobility and betweenness centrality considering COVID-19 avoidance as well as the shortest available safe route for user ease and shortened time of outside environment exposure. We verified our routing algorithm in a part of Delhi, India, by visualizing containment zones and medical establishments. The results with COVID-19 data analysis and route planning suggest a safer route in the context of the coronavirus outbreak as compared to normal navigation and on average route extension is within 8%–12%. Moreover, for further advancement and post-COVID-19 era, we discuss the need for adding open data policy and the spatial system architecture for data usage, as a part of a pandemic strategy. The study contributes new micro-mobility parameters adapted for COVID-19 and policy guidelines based on aggregated contact tracing data analysis maintaining privacy, security, and anonymity

Route Optimization System

This final year project is focused on creating a route generation application that can find the best route on a real road network. The distinct lack of route optimization systems or route generation system in Malaysia was the motivational factor behind this project. It is a collaborative project between another final year student and me. I will be concentrating on finding the best algorithm for calculating the shortest distance between two points on a digital map. After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). This algorithm is an exact algorithm that is specifically for finding the shortest route in a network. It has been used in other networks beside roads, for instance, pipe networks or railway networks. The method used to develop this project is Rapid Application Development (RAD). Using that process, we have settled on Java as our development platform as we found it able to both implement DA and the GIS component (map display and manipulation). The software that we came up with allows the user to select a point of origin on the map and a destination point and expect the software to highlight the best route onthe map as well as output the road names in that route, from the origin to the destination. It will also give the user the total distance from origin to destination. It does not take into account the amount of time that the drivermight take to travel that distance. This project is just the first step in creating a more robust route generation system for the Malaysian market. The potential for this project to be propagated on a mobile platform can also be considered due to its Java platform