WO2013054310A1 - Système et procédé de calcul d'itinéraires - Google Patents

Système et procédé de calcul d'itinéraires Download PDF

Info

Publication number
WO2013054310A1
WO2013054310A1 PCT/IB2012/055563 IB2012055563W WO2013054310A1 WO 2013054310 A1 WO2013054310 A1 WO 2013054310A1 IB 2012055563 W IB2012055563 W IB 2012055563W WO 2013054310 A1 WO2013054310 A1 WO 2013054310A1
Authority
WO
WIPO (PCT)
Prior art keywords
pollution
route
noise
air
value
Prior art date
Application number
PCT/IB2012/055563
Other languages
English (en)
Portuguese (pt)
Inventor
José Fernando GOMES MENDES
Paulo Jorge GOMES RIBEIRO
Original Assignee
Universidade Do Minho
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Universidade Do Minho filed Critical Universidade Do Minho
Publication of WO2013054310A1 publication Critical patent/WO2013054310A1/fr

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
    • G01C21/3461—Preferred or disfavoured areas, e.g. dangerous zones, toll or emission zones, intersections, manoeuvre types, segments such as motorways, toll roads, ferries

Definitions

  • the present invention is a method and navigation system for determining routes. More specifically, it includes a method that determines less noisy and polluted routes in particular that pedestrians or cyclists should follow.
  • Navigation and route planning systems are usually geared towards the circulation of motor vehicles, namely automobiles.
  • motor vehicles namely automobiles.
  • soft or active modes the market offers a scarcer and less diverse set of solutions.
  • active modes are considered to be the most economically, socially and environmentally sustainable modes, since mobility is guaranteed by its own means (without engines) and the emission of pollutants into the atmosphere and noise is considered null. .
  • the active modes do not have any protection against external agents derived from pollution, as in the case of automobiles that have comfortable cabin and fitted with filters of various species.
  • US 2011/0161002 is a method for a navigation system to determine pedestrian routes between a given origin and destination. It consists of displaying a set of messages specifically for the pedestrian mode that will be used in the navigation process.
  • the described invention presents in detail the overall process of a pedestrian navigation system, having regard to its design in terms of hardware / software relationships. It presents a data collection structure on a geographical basis at the level of traffic infrastructure and pedestrian points of interest. Data are collected for the creation of databases on a geographical basis for two geometric elements of these bases, the segments and the orientation nodes, which correspond to the ends of a segment.
  • Data that may be related to pedestrian circulation will be collected for geographical areas referred to as organized and disorganized, and in the case of segments raised their geographical position and other attributes related to circulation, such as speed limit, directions traffic, road class, among others.
  • At the level of the nodes is raised its georeferenced positioning (latitude, longitude) and the necessary characteristics to allow the orientation of pedestrians during their travels.
  • some data that may be collected may include the following attributes at both node and segment levels: the accessibility level of wheelchairs, if they are child and pet-friendly, if the areas are well or poorly lit, very or poorly moved areas, noisy / quiet, poorly smelled / polluted, protected from rain or not, bicycles are prohibited, outlined by trees, paved / unpaved areas, grassy area, dirty area, and other information.
  • attributes related to pollution and noise are mentioned, however they are presented in a slight way and only as attributes of characterization of streets and intersections. No method of evaluation and measurement is mentioned and therefore gives the idea that the collection is purely qualitative on a descriptive basis (eg yes / no) and may at most be nominal in character (eg weak, medium, good).
  • Route calculation may present a tool where users may enter other data or attributes such as personal preferences and has been referred to as an example of "avoiding polluted areas".
  • the route calculation is based on the data collected and existing in the geographic databases, and various optimization criteria can be used such as the minimization of the time traveled, the distance, or any other criteria, and any calculation algorithm can be employed to route determination.
  • EP 2372305 is a method for a navigation system to determine pedestrian routes between a particular origin and destination.
  • the method assesses a wide range of possible paths by assessing the safety cost to pedestrians, this cost represents the safety risk to the pedestrian.
  • this cost represents the safety risk to the pedestrian.
  • it indicates a path where it is possible to move the pedestrian safely between origin and destination, provided that continuity is ensured between all elements of the route, since the pedestrian infrastructure integrates elements such as a network. walks and pedestrian crossings, such as crosswalks, tunnels and overpasses.
  • the method provides a route guidance that minimizes the cost associated with pedestrian safety.
  • the structure of the navigation system consists of a geographical database and a route calculation program which will be processed on a computer.
  • the navigation system is considered a set of hardware / software components, which go through the positioning definition until the information passes between the server where the route calculations are performed and the navigation equipment.
  • the navigation system is initially based on the creation of a geographical database based on the characterization of the infrastructures that make up a road network. and particularly the sidewalk network adjacent to the pathways of that network.
  • Data are collected for the creation of geographic databases for two geometric elements, the lines (segments) and the points designated by us, which correspond to the ends of a segment.
  • Line segments may also assume the role of pedestrian links that include exclusively pedestrian paths such as squares, pedestrian underpasses, overpasses, stairs, squares, pedestrian streets, etc.
  • some attributes that would be raised to form the database such as the speed limit, traffic volumes, traffic directions, road class, among other duly georeferenced physical characteristics.
  • some data that may be collected may include the following attributes at the node, segment, and pedestrian link level, such as the type of pavement of the sidewalks, the accessibility level of the wheelchair, the suitability for circulation of children and pets, whether the areas are well or poorly lit, areas that are very or not busy, noisy / quiet, smelly / polluted, protected from rain or not, bicycles are prohibited, outlined by trees, paved areas / unpaved, grassy area, dirty area, and other information.
  • origin and destinations can be identified by geographical coordinates. Route calculation can present a tool where users can enter other data, or attributes, such as personal preferences.
  • the route calculation is based on the data collected and existing in the geographic databases that give rise to a pedestrian maneuver table that will be used in the calculation of the safest pedestrian routes, and this table includes in addition to the information given previously more pedestrian safety-related attributes, such as whether pedestrian crossing is signaled.
  • Route calculation may use various optimization criteria such as minimizing time traveled, distance, or any other type of criteria, and any route calculation algorithm may be employed.
  • route calculation identifies more than one possible solution, the route that optimizes safety and / or efficiency and / or minimizes the complexity of the routes, particularly at intersections, is selected.
  • a cost function is created that evaluates the cost of the trip, and for this purpose weights are assigned to the network segments and nodes according to some criteria, such as: existence of black spots (accidents), volumes and speed. traffic, identification of the occurrence of works, weather, crime levels, passing through some Points of Interest, among other factors.
  • the method has as its main objective to ensure the safest route calculation and therefore environmental aspects are not relevant in the route calculation process, It is found that the process of processing the databases is very different from that presented in the present invention.
  • US patent application 2008/0312819 aims to produce a pedestrian planning and navigation system and method that can integrate driving into motor vehicles
  • the invention is more oriented to use on a University Campus and aims to customize pedestrian routes by enhancing campus and community locations while ensuring navigation options that address the length of pedestrian paths and safety factors. Each user can choose a safer or faster path.
  • Route calculation includes the following steps: generate a source and a destination; generate a safety factor; assign each segment a length and safety factor; calculate at least one route and ensure its representation.
  • the route generation system is based on a network of lines and points based on a geographic information system. For each segment its length is calculated, a value that translates into safety through the objective assessment of that section's risk factor (safety rating) and a safety factor.
  • Routes are measured by minimizing the weights resulting from the combination of the risk factor with the user-defined safety factor, for this purpose the optimization algorithm uses the criterion of minimizing the distance multiplied by that weight.
  • the multiplier contaminating the distances is only one, which simultaneously contemplates the existing pollution situation and the user's preference, ie the multiplier always depends on the pollutant concentration (noise and pollution). . It is further added that one of the aims of the present invention is to minimize the impact of pollution rather than to find the shortest way.
  • the length of the route and the route may vary because the relative magnitude of the multiplier values for the different pollutant concentration classes and noise levels may vary greatly depending on the aggravation the user wishes to attribute to the maximum allowable concentration value. of pollutant.
  • the safest route may, at the limit, have segments with different levels of pedestrian safety, as the pedestrian may choose exclusively to favor speed over safety, ie to assign zero weight. to the safety factor.
  • the multiplier variation in relation to the pollutant concentration depends on a fuzzy function.
  • the way in which pedestrian exposure risk is assessed is not defined and will be quantified on an ordinal scale from 0 to 10 which can be corrected by a user, which guarantees some lack of objectivity .
  • the maximum value of the multiplier associated with the maximum pollutant concentration defined by the legislation is that it will be possible to define the level of aggravation imposed to the different values of the pollutant concentration, obtaining various types of routes, healthier, healthier, moderately healthier, among others.
  • different levels of safety are not defined, ie the user only chooses between having a shorter route or a safer route.
  • the present invention is a method of generating environmentally sound routes in an original and innovative urban environment since it minimizes the impact of noise and air pollution on walking and cycling in the route planning process. or any other active mode of transport.
  • the originality and innovation lies in the contamination process of the pedestrian and cyclable network axes by noise pollutants, environmental noise, and various atmospheric pollutants, namely PM10 particles.
  • Concentration values for various pollutant species and environmental noise levels are extracted from long-term hourly maps. These maps result from the application of pollutant dispersion simulation models and the propagation of environmental noise, and specific programs such as CadnaA are used for this purpose.
  • the results of the simulations are maps in vector format or raster type. This way they can be used in a Geographic Information System, which will allow the use of these values in the phase contamination phase and consequently in the route calculation.
  • the characterization of the influence and affect of pollutants on the networks presupposes the average hourly assessment of noise levels and pollutant concentration for long-term scenarios, which are estimated and obtained for annual periods.
  • the values of these levels and concentrations will be transformed into multipliers that derive from the use of fuzzy functions for each pollutant, intended to translate the evolution of the effect of these pollutants on human health.
  • the so-called "contaminated distances" that result from the product of the actual distances by the selected multiplier are calculated, called the contamination of distances and is expressed by:
  • R1, R2, R3 and R4 are arbitrary and depend on the type of pollutant.
  • K1 and K2 K2 in this specific example correspond to the value of 1 / Ki, but this is not required) are arbitrary and depend on the intended distance adjustment intensity.
  • the healthy route generation model for active modes of transport will be used in route calculation programs whose impedance values (optimization variable) will correspond to a contaminated distance.
  • This model will enable innovative planning and navigation solutions to be created in route planners available on digital platforms as well as in mobile navigation systems (portable smartphones or GPS).
  • One of the main advantages of the present invention is related to the fuzzy preprocessing phase, in which the road map vector map is subsegmented into subsegments established by noise and air pollution classes.
  • This gives a new road network map that accurately reflects air and noise pollution indicators, which has the advantage that it can be used transparently and without any adaptation to the usual routing optimization algorithms. That is, there is no need for any change in the route planning engine, while a much more accurate simulation is obtained than currently available.
  • Another advantage is that these benefits are achieved without excessive impact on the computational load involved.
  • Yet another advantage is linked to the fact that the computational load involved is easily adjusted by manipulating the parameters of the present invention, namely the number of classes chosen for the basis of subsegmentation.
  • Figure 1 Schematic representation of healthy route generation flowchart for active (pedestrian and cycling) modes of transport.
  • Figure 2 Schematic representation of fuzzy functions of multipliers KH and KL.
  • Figure 3 Schematic representation of fuzzy functions of the WH and WL multipliers.
  • Figure 4 Schematic representation of the contamination of distances at axle level.
  • Figure 5 Schematic representation of Braga's road network produced by Navteq in 2011).
  • Figure 6 Example schematic representation of multiplier assignment for noise levels for the period from 11:00 to 12:00.
  • Figure 7 Example schematic representation of polygons aggregation with noise level between 75 and 80 dB (A)).
  • Figure 8 Schematic representation of the multipliers' allocation to the road network.
  • Figure 9 Example schematic representation of the transformation of a section of a street after overlapping with pollution maps.
  • Figure 10 Example schematic representation of the shortest route calculation between two points using the ESRI network analyst.
  • Figure 11 Example schematic representation of the calculation of different routes between two points: a) less / moderately noisy; b) less / moderately polluted; c) healthier and healthier.
  • Figure 12 Schematic representation of examples of the variation of the various routes between points 1 and 2 at different times of the day.
  • Figure 13 Schematic representation of the calculated routes between two points (1 and 2) between 8 and 9 o'clock.
  • Figure 14 Schematic representation of the distance multiplication factor (k) is a function of the pollutant concentration level (r).
  • FIG. 15 Simplified schematic representation of the elements of an embodiment of the invention. Detailed Description of the Invention
  • the model for determining a healthy route is the construction of an information infrastructure based on a Geographic Information System, through which data from simulations of environmental noise levels and atmospheric pollutant concentration will be integrated into a given pedestrian network. cycling.
  • the core of innovation lies in the second point of the model that corresponds to the multipliers generation process and consequent determination of the contaminated distances.
  • Appropriate tools for the production of pollution maps are used upstream of this process, such as hourly pollutant concentration estimation and environmental noise level programs such as CadnaA, as well as the geographical platform that may use various types of pollution. such as ESRI's ArcGIS case.
  • the route generation phase involves the use of geographically based programs that incorporate route optimization programs and allow the cost variable to be assigned the values of the contaminated distances. These contaminated distances, particularly aggravated, may be referred to as impedances.
  • phase of distance contamination concerns the creation of impedances that will be attributed to the various network segments of the active modes of transport, based on long-term environmental noise maps, various air pollutants and Global pollution map for all hours of the day.
  • Impedance calculation is associated with the definition and characterization of a distance multiplicative factor whose purpose is to translate the effects on human health. noise levels and pollutant concentration, in particular PM10 particles.
  • the definition of the impedances to be used for contamination of road network axle distances should allow for the introduction of variability of various factors that influence the sensitivity of different humans, notably for very similar exposure levels of the concentration. of a particular pollutant.
  • the yy axis of the fuzzy functions represents the evolution of the multiplicative factor, while the xx axis shows the equivalent noise level - Leq (A) and the particle concentration - PM10.
  • the function is defined by the linear variation between the anchor values, called fuzzy control points, which are the minimum and maximum values of noise and particle concentration - PM10, defined according to the limits imposed by the legislation or, taking into account basis scientific studies for this purpose.
  • the limit values of the multiplicative factors K (noise) and W (PM10 particles) for the control points are set by the same at the beginning of the planning and navigation process. Healthy routes.
  • the user can make a strong or weak increase of distances by defining contaminated distances that will be used as optimization variables in the shortest path calculation process available in GIS software.
  • the user only chooses the level of aggravation according to a numerical scale of integer values, where for example 3.0 corresponds to the maximum value of the coefficient KH and WH which will give rise to a strong contamination of the distances and in turn the minimum value will automatically be in a preferred embodiment defined by the algorithm as 1/3.
  • the option for a strong aggravation implies that the algorithm assigns three times the actual distance to distances contaminated by pollution levels above the upper anchor value and to values below the lower anchor value the distances will be converted into a distance. third of the actual distance.
  • the multiplicative factor variation is linear.
  • weak aggravations is geared towards obtaining routes that are intended for regular use, such as commuting, as pedestrians or cyclists will be willing to extend their route to achieve healthier route, but without requiring them to significantly increase travel times and length of the route.
  • the routes generated from the attribution of a strong aggravation involve the circulation by less polluted paths than those determined using a weak aggravation and, of course, those without any aggravation of the distances (shortest path).
  • anchor values are defined on the basis of the maximum permissible noise (Lden) values associated with different zones as set out in the General Noise Regulation. Since the temporal coverage of the production of healthy routes covers all hours of the day, limit values for night time (Ln) will not be used, as the objective is to minimize the effects on people's health when walking. on foot or by bike. Similarly, exposure limits for mixed zones at night are equal to the limit for sensitive zones during the day and correspond to 55 dB (A), as shown in Table 1. Thus, only the use of the limits imposed is permissible. to Lden in defining the fuzzy function for all hours of the day.
  • Lden maximum permissible noise
  • the contaminated distance equals the actual distance for values between 55 and 65 dB (A), which include the values between boundaries associated with the sensitive and mixed zones for Lden.
  • A For anchor values corresponding to the upper and lower limits of K, whether in the case of a strong or weak impedance, a margin of 10 dB (A) (by analogy with the values defined for the same zones as Ln and Lden.
  • values below 35 dBA do not correspond to reality) above and below the limits of Lden, as shown in Tables 1 and 2 and the graph in Figure 2.
  • the contamination phase consists of:
  • the treatment of the road network consists of checking the continuity of the links between axles, particularly at the intersection level. It is necessary to ensure that the axes of the study area are all represented, both for pedestrian and cycling traffic, as this will be the basic structure for route generation.
  • the definition of the directions of the road axes is another aspect to be taken into account, as it is a necessary condition for bicycle circulation and can be done at this stage or at the beginning of the route generation phase.
  • this question does not arise because it is not restrictive as pedestrians can move both ways in any square, sidewalk or verge.
  • Figure 5 shows the road network for the study area in vector format with the database treatment described above.
  • the attribute table associated with the road network must have a vast set of information that can be used in navigation algorithms for soft modes and other modes of transport, including:
  • Cartography producers' databases such as Navteq already contain this vast array of information, but their use must be preceded by field validation.
  • the pollution mapping software allows the export of calculation grids in various formats, such as raster files and vector files of lines and polygons of the same level of pollution.
  • Software such as CadnaA presents these export possibilities in their menus, which facilitates the use of pollution map data in other types of GIS programs, such as ESRI's ArcGIS.
  • the multiplier value was calculated for each of these classes according to the fuzzy functions defined in Table 4, considering a heavy (K Heavy) to obtain a noisy route. , or a faint (K Light) for a moderately noisy route.
  • Figure 6 shows an example of the noise multipliers (K) affecting the period from 11:00 to 12:00. It should be noted that at this stage each class corresponds to a set of polygons represented in each row of the attribute table, as shown in Figure 7.
  • Overlaying the network with maps and capturing multiplier values through the line-on-polygon operator implies segmentation of the intersected axes by the polygons.
  • the base road network of the study area ie without any overlap, consists of 1206 segments.
  • the road network was divided into 6618 segments.
  • Figure 9 shows a 280-meter long stretch of Rua D. Pedro V of Braga, divided into 67 segments, reflecting a large variation in the combination of noise values. and PM10 concentration in this section, between 11 and 12 hours.
  • the contamination process ends with the calculation of the contaminated distances resulting from the multiplier product by the associated segment length.
  • four contaminated distances can be directly determined: dKH, dKL, dWH and dWL, which will be used as cost variables in the generation of the least noisy, moderately noisy, least polluted and moderately polluted route. It should be clarified here that these qualifying route expressions are relative in character, reporting a level (less and moderate) than the shortest route.
  • the healthiest route results from the average of the multipliers KH and WH, giving rise to the distance dKWH.
  • the healthy route results from the average of the multipliers KL and WL, giving rise to the distance dKWL.
  • the map which underlies a certain set of geographic features that translate into a datum.
  • the definition of the datum corresponding to each map is crucial for some operations, such as the measurement of areas and distances, among many others.
  • the process of validating the healthy routes model consists of calculating two environmental indices, relating to noise and the average PM10 concentration for a given route and comparing them with the indices associated with the shorter route.
  • Figure 13 shows the shortest route and the six routes with the least health impact due to environmental aspects, between points 1 and 2, for the period from 8:00 to 9:00.
  • Table 7 provides a set of data for each route, such as extension, contaminated extent and noise and particle exposure rates, complemented by data comparing said route attributes with the shortest route. .

Abstract

L'invention concerne un système et un procédé pour calculer des itinéraires, le procédé consistant à obtenir des polygones avec des attributs de pollution atmosphérique et sonore à partir de cartes horaires (carte de pollution), chaque polygone correspondant à une classe de pollution atmosphérique et sonore à partir d'un numéro prédéfini de classes de pollution atmosphérique et sonore; à segmenter chacun des segments du réseau routier par intersection avec lesdits polygones en sous-segments (modèle de contamination des distances); à déterminer la distance corrigée des sous-segments, par application, à distance réelle de chaque sous-segment, de facteurs de multiplication de pollution sonore (K) et de pollution atmosphérique (W) obtenus par connaissance de la valeur moyenne de la classe de pollution respective (carte des distances contaminées); à calculer l'itinéraire avec les sous-segments et les distances corrigées, réduisant la distance corrigée totale (navigation) de manière à obtenir les itinéraires souhaités (itinéraire sain, moins bruyant, moins pollué):
PCT/IB2012/055563 2011-10-12 2012-10-12 Système et procédé de calcul d'itinéraires WO2013054310A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
PT105929A PT105929B (pt) 2011-10-12 2011-10-12 Sistema e método de cálculo de rotas
PT105929 2011-10-12

Publications (1)

Publication Number Publication Date
WO2013054310A1 true WO2013054310A1 (fr) 2013-04-18

Family

ID=47470042

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/IB2012/055563 WO2013054310A1 (fr) 2011-10-12 2012-10-12 Système et procédé de calcul d'itinéraires

Country Status (2)

Country Link
PT (1) PT105929B (fr)
WO (1) WO2013054310A1 (fr)

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130080053A1 (en) * 2011-09-27 2013-03-28 International Business Machines Corporation Dynamic route recommendation based on pollution data
CN104006821A (zh) * 2014-05-28 2014-08-27 英华达（南京）科技有限公司 一种导航方法和系统
CN106018210A (zh) * 2015-03-26 2016-10-12 福特全球技术公司 车载微粒传感器数据分析
WO2017051411A1 (fr) * 2015-09-24 2017-03-30 Agt International Gmbh Modélisation en temps quasi réel de dispersion de la pollution
CN108827842A (zh) * 2018-04-13 2018-11-16 安徽新华学院 一种基于pm2.5的空气质量最优路径规划方法及系统
CN108932357A (zh) * 2017-05-27 2018-12-04 中国科学院遥感与数字地球研究所 一种大气颗粒物的微物理特性到光学散射特性的计算方法

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104931061A (zh) * 2014-03-20 2015-09-23 昆山研达电脑科技有限公司 过滤噪音的路径规划装置及其方法
GB2569986A (en) * 2018-01-08 2019-07-10 Continental Automotive Gmbh Method and system of mapping emissions
WO2019233584A1 (fr) * 2018-06-07 2019-12-12 Telefonaktiebolaget Lm Ericsson (Publ) Serveurs d'itinéraire de carte, terminaux mobiles et procédés et produits-programmes d'ordinateur associés
EP3628971A1 (fr) * 2018-09-26 2020-04-01 Valeo Systemes Thermiques-THS Procédé mis en uvre par ordinateur et système de détermination d'un itinéraire

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080312819A1 (en) 2007-06-12 2008-12-18 Arup Banerjee Pedestrian mapping system
JP2009223514A (ja) * 2008-03-14 2009-10-01 Toyota Motor Corp プローブカーシステム並びにプローブカーシステムが配信する情報に応じて動作する車載空調システム及びナビゲーションシステム
JP2009229397A (ja) * 2008-03-25 2009-10-08 Denso Corp 運転支援システム
US20090309744A1 (en) * 2008-06-13 2009-12-17 National Taiwan University System and method of detecting air pollution, route-planning method applied to said detection system, and warning method of air pollution
US20110161002A1 (en) 2004-06-30 2011-06-30 Devries Steven P Method of Collecting Information for a Geographic Database for use with a Navigation System
EP2372305A2 (fr) 2010-03-30 2011-10-05 Navteq North America, LLC Procédé de fonctionnement d'un système de navigation pour fournir une route piétonne

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US3066188A (en) * 1959-08-14 1962-11-27 Bendix Corp Unbalanced autotransformer audio amplifier
EP0578788A1 (fr) * 1991-11-01 1994-01-19 Motorola, Inc. Systeme de planification de l'itineraire d'un vehicule
CN101526365B (zh) * 2009-04-07 2012-12-12 深圳市凯立德科技股份有限公司 模糊导航方法及装置

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110161002A1 (en) 2004-06-30 2011-06-30 Devries Steven P Method of Collecting Information for a Geographic Database for use with a Navigation System
US20080312819A1 (en) 2007-06-12 2008-12-18 Arup Banerjee Pedestrian mapping system
JP2009223514A (ja) * 2008-03-14 2009-10-01 Toyota Motor Corp プローブカーシステム並びにプローブカーシステムが配信する情報に応じて動作する車載空調システム及びナビゲーションシステム
JP2009229397A (ja) * 2008-03-25 2009-10-08 Denso Corp 運転支援システム
US20090309744A1 (en) * 2008-06-13 2009-12-17 National Taiwan University System and method of detecting air pollution, route-planning method applied to said detection system, and warning method of air pollution
EP2372305A2 (fr) 2010-03-30 2011-10-05 Navteq North America, LLC Procédé de fonctionnement d'un système de navigation pour fournir une route piétonne

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
"Advanced Topics in Environmental Health and Air Pollution Case Studies", 29 August 2011, INTECH, ISBN: 978-9-53-307525-9, article GILLES MAIGNANT ET AL: "Air Pollution and Urban Morphology: A Complex Relation or How to Optimize the Pedestrian Movement in Town", XP055053280, DOI: 10.5772/16802 *
P. RIBEIRO ET AL: "Route planning for soft modes of transport: healthy routes", URBAN TRANSPORT XVII, vol. 1, 6 June 2011 (2011-06-06), Southampton, UK, pages 677 - 688, XP055053300, ISSN: 1746-4498, ISBN: 978-1-84-564520-5, DOI: 10.2495/UT110571 *
SU J G ET AL: "Designing a route planner to facilitate and promote cycling in Metro Vancouver, Canada", TRANSPORTATION RESEARCH PART A: POLICY AND PRACTICE, PERGAMON, AMSTERDAM, NL, vol. 44, no. 7, 1 August 2010 (2010-08-01), pages 495 - 505, XP027063448, ISSN: 0965-8564, [retrieved on 20100528], DOI: 10.1016/J.TRA.2010.03.015 *

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130080053A1 (en) * 2011-09-27 2013-03-28 International Business Machines Corporation Dynamic route recommendation based on pollution data
CN104006821A (zh) * 2014-05-28 2014-08-27 英华达（南京）科技有限公司 一种导航方法和系统
CN106018210A (zh) * 2015-03-26 2016-10-12 福特全球技术公司 车载微粒传感器数据分析
WO2017051411A1 (fr) * 2015-09-24 2017-03-30 Agt International Gmbh Modélisation en temps quasi réel de dispersion de la pollution
CN108932357A (zh) * 2017-05-27 2018-12-04 中国科学院遥感与数字地球研究所 一种大气颗粒物的微物理特性到光学散射特性的计算方法
CN108932357B (zh) * 2017-05-27 2020-10-20 中国科学院遥感与数字地球研究所 一种大气颗粒物的微物理特性到光学散射特性的计算方法
CN108827842A (zh) * 2018-04-13 2018-11-16 安徽新华学院 一种基于pm2.5的空气质量最优路径规划方法及系统

Also Published As

Publication number Publication date
PT105929B (pt) 2014-11-17
PT105929A (pt) 2013-04-12

Similar Documents

Publication Publication Date Title
WO2013054310A1 (fr) Système et procédé de calcul d'itinéraires
Foltête et al. Urban layout, landscape features and pedestrian usage
Nicoară et al. A GIS based network analysis for the identification of shortest route access to emergency medical facilities
Chen et al. Multi-scale and multi-modal GIS-T data model
Mölter et al. Influence of walking route choice on primary school children's exposure to air pollution—A proof of concept study using simulation
Nourian et al. Modelling walking and cycling accessibility and mobility: The effect of network configuration and occupancy on spatial dynamics of active mobility
CN104217126A (zh) 一种基于低空气污染暴露风险道路路径选择方法
Iseki et al. A new approach for bikeshed analysis with consideration of topography, street connectivity, and energy consumption
Sevtsuk et al. Predicting pedestrian flow along city streets: A comparison of route choice estimation approaches in downtown San Francisco
JP6460572B2 (ja) 生活圏設定支援装置、プログラム、および記憶媒体
Chen et al. Rail transit ridership: station-area analysis of Boston’s Massachusetts Bay transportation authority
Jafari et al. Building the road network for city-scale active transport simulation models
CN113793500B (zh) 城市交通道路可计算路网的构建方法及系统
El Masri et al. Road grade estimates for bicycle travel analysis on a street network
Daniel et al. How steep is that street?: Mapping ‘real’pedestrian catchments by adding elevation to street networks
Bashkanov et al. Exploiting openstreetmap-data for outdoor robotic applications
Macias Alternative methods for the calculation of pedestrian catchment areas for public transit
Arora et al. Transportation network model and network analysis of road networks
Zhang et al. An improved method for urban Walk Score calculation considering perception of the street environment
Kondrateva et al. An isochrones based public transport stops optimization technique
Jezek et al. Estimation of response time for ground ambulance transport
Gallagher et al. Missing links: How social paths can improve pedestrian accessibility to light rail
Ludwig et al. Comparison of simulated fast and green routes for cyclists and pedestrians
Treccani et al. Accessible path finding for historic urban environments: feature extraction and vectorization from point clouds
Zhou et al. Why do we hardly see people with visual impairments in the street? A case study of Changsha, China

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 12808888

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 12808888

Country of ref document: EP

Kind code of ref document: A1