A travel planner , a travel planner , or route planner is a custom search engine used to find the optimal means of travel between two or more specified locations , sometimes using more than one mode of transportation. Searches can be optimized on different criteria, such as fastest , shortest , smallest change , cheapest . They may be constrained for example to go or arrive at a certain time, to avoid certain street points, etc. A single trip can use the order of some modes of transport, which means that the system may know about public transport services as well as the transport network. for private transportation. Travel planning or Travel planning is sometimes distinguished from route planning , where route planning is typically considered to use private modes such as driving, walking, or cycling, usually using a single mode at a time. Travel Planning or Travel shall instead use at least one mode of public transport operating in accordance with the announced schedule; Given that public transport services only depart at certain times (unlike private transport that can leave at any time), an algorithm must not only find the path to its destination but attempt to optimize it so as to minimize the waiting time spent on each leg.
In European Standards such as Transmodel travel planning is used specifically to describe route planning for passengers, to avoid confusion with a completely separate operational travel planning process to be made by public transport vehicles on such trips made.
Travel planners have been widely used in the travel industry since the 1970s by booking agents. The growth of the Internet, the proliferation of geospatial data, and the development of information technology in general have led to the rapid development of many internet-based browser-based intermodal travel planners such as Rome2rio, Google Transit, FromAtoB.com and DistancesBetween.com.
Travel planner can be used together with ticket and reservation system.
Video Journey planner
Basic features
The travel planner, also known as the travel planner, consists of the frontage user interface to collect travel requirements from users and presents travel trips proposed back to them, and travel planning engines travel which does the actual calculation of a possible itinerary, prioritizes it according to the optimization criteria of the user ( fastest, least change, cheapest , etc.) and returns the most satisfactory subset of them. The user interface can run on terminals, PCs, tablets, mobile or even speech-based devices and can integrate maps and location data to provide travel visualization or to simplify interaction with users. The travel planning machine can be either local or long distance and may have monolithic (all data in one search space) or distributed architecture (data for different regions divided among different machines , each with their own search space).
Simple machines include only public transport data for single mode , others multimodal , which include public transport data for some modes; sophisticated intermodal engines can also include road and trail routes to cover foot access to reach public transport stops and simultaneously calculate routes for private car journeys so users can make comparisons between public and private modes. Advanced travel planners can also use real-time data to improve their results; this use may be decorative , which annotates results with information about known incidents that might affect travel, or computation , dynamically uses the estimated time of departure and arrival from real time feeds such as the CEN Service Interface for Realtime Information to provide more accurate travel plans for trips to be made in the near future. What limit of back-end machine capabilities might be offered in the user interface. Available data limits the ability of back-end machines.
Input
Minimum input for the trip planner is the place of origin and destination and the date and time of travel (which can be delayed to the current moment). The interface can provide a variety of methods for finding and defining origin or destination, including specifying geocode place names, stop or station codes, street addresses, destination (ie, other public or destination objects) or spatial coordinates ( usually determined by using interactive web maps - the current location can also be obtained from GPS location services or from IP address search). The location search function of the trip planner will usually first complete the origin and destination to the nearest known node on the transport network to calculate the itinerary of a known public transport travel data collection.
Depending on the travel planning engine and the data set available for that, many other additional inputs may be supported, for example:
- Which transport modes are included or excluded.
- Whether to limit travel time by arrival time, departure time - or to allow flexible windows where travel can take place.
- Preferred routing for travel via intermediate stop points.
- Travel optimization preferences: for example shortest journey versus at least number of changes .
- Travel cost optimization preferences: for example, cheapest versus most convenient .
- Accessibility preferences: free steps, wheelchair access , etc., and whether to allow additional time for connections.
- Access preferences: how long the user is prepared to quit, etc.
- Class of travel and facilities in it desired.
- Jamming preferences: at least versus shortest travel , etc.
- Relevant information to choose the cheapest rates and options: user type ( adult, child, senior, student, etc.), travel card ownership, etc.
- etc.
Output
After the trip planner has calculated and prioritized a trip or a series of possible journeys, this is presented to the user as a list for users to choose from, they may or may be displayed on the map. Again, depending on the capabilities of planners and available data, the results may include;
- Time and departure point of trip from stop or station, possibly with the right platform to use and even boarding point on the platform.
- A travel map showing the path footage on the map.
- Route map showing network topology.
- Stop the area map and other directions to identify stopping location in place up and down.
- Information about the signs leading up shown on the vehicle to identify the right transport vehicle to take.
- Information about the transfer times required to make access and foot connections.
- Step-by-step instructions to follow the access foot to a stop, enter a major station or intersection such as the airport, or make a transfer on the link foot, including the accessibility characteristics of each step.
- Information about the accessibility characteristics of vehicles on certain legs ( wheelchairs, wheelchairs , etc.).
- Information about on-stop and on-board facilities ( parking, buffet cars, wifi, etc.).
- Information about expected disruptions or delays in certain modes or legs of travel.
- Information on the price of tickets available for travel.
Additional features
Some travel planners integrate information services apart from point-to-point travel planning to their user interface, for example to provide schedules for routes, real-time arrivals and departure at stops, or real-time disturbance notices. Additional visualizations may be offered; Google, for example, has a Gantt chart like 'Schedule explorer' which can be used to visualize the relative time of various travel plans. Another powerful visualization is the Isochrone map which shows relative travel time as relative distance.
Trip planner can also have more than one user interface, with each optimized for different purposes. For example, an online standalone service performed with a Web browser, an interface for call center agents, one for use on mobile devices, or a special interface for users with visual impairments.
Some commercial travel planners incorporate aspects of shopping discovery for accommodation and activities and price comparison for some aspects of travel.
Maps Journey planner
History
Antecedents
Paper-based schedules designed for manual travel planning on public transport were developed in the 19th century, primarily by George Bradshaw who published the Bradshaw Guide, the first compilation of the world rail schedule] in 1839. This became the definitive guide to British rail routes and schedule, combine data from different rail companies into a common format. It serves to establish both the standard data sets of the stop and services, the workflow to collect data regularly from various providers and update the data set, and the market for travel information products. Equal publications developed for other countries.
The theoretical basis for computer-based travel planning was provided in 1956 by the Edsger W. Dijkstra algorithm to find the shortest path between nodes in the graph. The graph theory itself stems from Euler's consideration of the problem of route planning - the Seven Bridges KÃÆ'¶nigsberg.
System precursors
In the 1970s and 1980s, national rail operators such as the British Rail, Deutsche Bahn and major metropolitan transit authorities London Transport developed an internal system for managing data for print schedules and to support operations. The national rail operator also developed a reservation system that typically has the ability to ticket offices and retailers to find available travel between the origin and destination to book tickets.
Separate development of electronic travel planning capabilities takes place in flight, starting somewhat earlier as part of the evolution of the airline reservation system relating to the real-time seating stock management of airlines. The earliest of these Saber systems was launched in 1960 by American Airlines, others including Apollo (United Airlines (1972) and rival Galileo CRS and the Amadeus system created by a consortium of different European airlines in 1987. All are mainframe-based with terminals OLTP remotely and became widely used by travel agencies to find air travel, trains and boats.
First generation system
In the late 1980s and early 1990s, several national railway operators and major metropolitan transit authorities developed their own specialized travel planners to support their customer demand services. These typically run on mainframes and are accessed internally by terminals by their own staff at customer information centers, call centers, and at ticket booths to answer customer questions. Data comes from a schedule database used to publish print schedules and to manage operations and some include simple route planning capabilities. The HAFA schedule information system developed in 1989 by the German company Hacon, (now part of Siemens AG) is an example of such a system and was adopted by the Swiss Federal Railways (SBB) and Deutsche Bahn in 1989. The "Route" London, now TfL, used prior to the development of an on-line planner and covering all public transport services in London, is another example of OLTP mainframe travel planner and includes a large database of popular tourist destinations and destinations in London.
Second generation system
In the 1990s with the advent of [personal computers] with sufficient memory and processor power for travel planning (which is relatively expensive in terms of memory and processor requirements), systems were developed that could be installed and run on mini computers and personal computers.. The first digital public transport system planning system for microcomputers was developed by Eduard Tulp, an informatics student at the University of Amsterdam on an Atari computer. He was hired by Dutch Railways to build a digital travel planner for rail services. In 1990 the first digital travel planner for Dutch Railways (on floppy disks) was sold to be installed on PCs and computers for off-line consultation. The principles of its software program were published in a Dutch university paper in 1991. It was soon extended to cover all public transport in the Netherlands.
Another pioneer is Hans-Jakob Tobler in Switzerland. The product Finajour , used for PC DOS and MS-DOS is Switzerland's first electronic schedule. The first published version was sold for the period of 1989/1990.
A further development of this trend is to deploy travel planners to smaller platforms such as mobile devices such as [[] HAFAS Pocket], a Windows CE version of Hafas launched in 1998 that compresses apps and entire train schedules from Deutsche Bahn to six megabytes and runs as a stand-alone application.
Initial Internet-based system
Internet development allows HTML-based user interfaces to be added to allow for direct request of travel planning systems by the general public. A test web interface for HaFA, launched as the official railroad planner of Deutsche Bahn in 1995 and evolved over time into the main Deutsche Bahn site. In 2001, Transport for London launched the world's first large-scale multimodal travel planner for a world-wide city covering all modes of transport in London as well as rail routes to London; this uses a travel planning machine supplied by [3] Mentz Gmbh] from Munich after previous attempts in the late 1990s to add a web interface to the TfL mainframe internal trip planner that failed to scale. Internet travel planners for major transport networks such as national railways and major cities must maintain extremely high demand levels that require optimized software architecture to maintain that traffic. The world's first mobile travel planner for a large metropolitan area, the WAP-based interface to London using the Mentz engine, was launched in 2001 by startup company London Kizoom Ltd, which also launched the UK's first railroad travel planner for mobile internet in 2000, WAP service, followed by SMS service. Started in 2000, the Travel service provides all parts of the UK with regional multi-modal travel planning on buses, coaches and trains. The web based travel planner for British rail was launched by UK National Rail Inquiries in 2003.
An early public transport planner usually requires a stop or station specified for the end point. Some also support entering the name of a tourist attraction or other popular destination by storing the closest stopping table to the destination. This is then extended with the ability to add addresses or coordinates to offer the right point for point planning.
Important for the development of large scale multisode travel planning in the late 1990s and early 2000s was a standardized parallel development to encode stop and scheduling data from many different operators and workflow arrangements to collect and distribute data on a regular basis. This is more challenging for modes such as buses and coaches, where there are a large number of small operators rather than trains, which typically involve only a few large operators that have an exchange format and an existing process to operate their networks. In Europe, which has a dense and sophisticated public transport network, the Transmission Transmodel reference model for Transmodel was developed to support the process of creating and aligning standard formats at both national and international levels.
Distributed travel planner
In the 2000s, several major projects developed a distributed travel planning architecture to enable separate travel planning federations each covering a specific area to create composite engines covering a very large area.
- The UK Transport Direct Portal, launched in 2004 by the UK Department of Transportation, uses the JourneyWeb protocol to connect eight separate regional machines that include data from 140 local transport authorities in England, Scotland and Wales as an integrated engine. The well-integrated portal of road planners and public transport allows comparison between travel time mode, C02 trace etc...
- The German Delfi project developed a distributed travel planning architecture used to create a German regional planner federation, launched as a prototype in 2004. This interface was further developed by the German TRIAS project and led to the development of the CEN Standard [[| Open API for distributed travel planning ']] (CEN/TS 17118: 2017) was published in 2017 to provide a standardized interface for travel planners, incorporating features from JourneyWeb and EU-Spirit and utilizing the SIRI Protocol Framework and Transmodel reference model.
- The European EU Spirit project develops long-haul travel planners between different parts of Europe
Second generation Internet system
Public transport planners have proven to be very popular (for example in 2005 Deutsche Bahn already has 2.8 million requests per day and the travel planning site is some of the highest trade information sites in each country that owns it.The ability to buy tickets for trips to found trips is getting ever improving the utility and popularity of the site, early implementations such as Trainline UK offer mail delivery, this is already equipped in most European countries with self-service printing and mobile fulfillment methods, is now the main sales channel for most rail and air transport operators.
Google began adding travel planning capabilities to its product with Google Transit version in 2005, covering a trip in the Portland region, as described by TriMet's agency manager, Bibiana McHugh. This leads to the development of the Transit Freight Specification (GTFS), a format for collecting transit data for use in highly influential travel planners in the development of a PT data feed ecosystem covering many different countries. The successful use of GTFS as an output format available by major carriers in many countries has enabled Google to extend the scope of travel planners to more regions around the world. Google Transit travel planning capabilities are integrated into Google Map products in 2012.
The further evolution of the travel planning machine has seen the integration of real-time data so that future travel plans immediately take into account delays and real-time disruptions. UK National Rail demand added real-time to rail travel planners in 2007. It also has significantly integrated other types of data into trip planning outcomes such as intrusion notices, crowd rates, Co2 fees, etc. Travel planners from several major metropolitan cities such as the Transport for London trip planner have the ability to dynamically delay each station and the entire path so that a modified travel plan is generated during major annoyances that eliminate unavailable parts of the network. Another development is the addition of accessibility data and algorithmic capabilities to optimize the plan to consider certain disability requirements such as wheelchair access.
For the London 2012 Olympics, London enhanced travel planners were made which allowed the proposed trip results to be biased to manage the available capacity on various routes, spreading traffic to less crowded routes. Another innovation is the detailed modeling of all incoming and outgoing access points of any Olympic venues, (from PT stops to individual arena entrances) with actual predictions and queuing times to allow for security checks and other delays to be taken into account in recommended trip time.
An initiative to develop open source travel planners, the Open Trip Planner was sponsored by Portland, the Oregon transit agency, TriMet in 2009 and developed with the participation of agents and operators in the US and Europe; the full 1.0 version released in September 2016, enables smaller transit agencies and carriers to provide travel planning without paying a license fee of ownership.
Mobile app
The usefulness of mobile internet travel planners was changed by the launch of the Apple iPhone in 2007. Similar iPhones and smartphones like Android allow more intelligence to be placed on clients and offer larger formats and maps and even more usable interfaces can be created. The incorporation of the current spatial location of GPS mobile devices also simplifies some of the interactions. The first iPhone app for UK rail travel planning was launched by UK Startup Kizoom Ltd. in 2008 and a large market for travel planning and travel information applications was developed worldwide, with applications provided by both transport operators and third parties. In the UK this is greatly facilitated by the Transport's open data policy for London that makes travel planning engines and other data feeds available to third-party developers.
Sophisticated mobile apps like Citymapper now integrate multiple types of data feeds including trip planning for cities on every continent and provide a uniform user interface regardless of which country or city they are in.
Fashion-specific considerations
Public transport routing
For public transit, travel planner is limited by arrival or departure time. It can also support different optimization criteria - for example, the fastest route, the least change, the most accessible . Optimized by the cheapest price (, "the most flexible rate , etc.). Usually done by separate algorithms or machines, although travel planners who can refund ticket prices for travel they find can also offer sorting or filtering results based on price and product type.For long-distance rail and air travel planning, where price is a significant consideration in optimizing the price of the travel planner can suggest the cheapest date to travel for flexible customers for travel time.
Car route
Road leg planning is sometimes performed by separate subsystems in the trip planner, but may consider both single mode travel and intermodal scenarios (eg Park and Ride, kiss and ride, etc.). General optimizations for car routing are shortest route , fastest route , cheapest route and with restrictions for certain waypoints . Some advanced travel planners can take into account the average travel time on the road, or even the estimated real-time average travel time on the road.
Pedestrian route
A travel planner ideally will provide detailed routing for pedestrian access to stops, stations, points of interest etc. This will include the option to consider account accessibility requirements for different types of users, for example; 'no step', 'wheelchair access', 'no lift', etc.
Bicycle routing
Some travel planning systems can calculate bicycle routes, integrate all bike-accessible routes and often include additional information such as topography, traffic, road cycling infrastructure, etc. This system assumes, or allows the user to specify, preferences for a quiet or secure path, minimum elevation changes, bike paths, etc.
Data requirements
The trip planner depends on a number of different types of data and this quality and range of data limits their ability. Some travel planners integrate many types of data from multiple sources. Others can work with just one mode, such as flight schedules between airports, or just use street addresses and networks for driving directions.
Contextual data
Data point of interest
Passengers do not travel because they want to go to a particular station or stop, but because they want to go to some interesting destinations, such as sports arenas, attractions, shopping centers, parks, courts of law, etc., Etc. Many travel planners allow users to search for such "POINT", either by name or by category ( museum, stadium, prison, etc.). Data sets that are systematically named, geocoded and categorized as commercially obtainable destinations, for example, a UK PointX data set, or derived from an open source data set such as the Open Street Map. Large operators like Transport for London or National Rail have historically developed well-developed data sets for use in their Customer Call centers, along with information about links to nearby stops. For points of interest that cover large areas, such as parks, country houses or stadiums, proper geocoding of the entrance is important.
Gazetteer Data
User interface travel planning can be made more useful with Gazetteer data integration. This can be attributed to a stop to help with a particular stop search, for example for disambiguation; there are 33 places called Newport in the US and 14 places in the UK - a Gazetteer can be used to distinguish which and also in some cases to indicate the relationship of transportation exchanges with city and city center that passengers want to reach - for example only one of five airports London is actually in London. Data for this purpose usually comes from an additional layer in the map data set as provided by Esri, Ordnance Survey, Navtech, or specific data sets such as the National Transport Gazetteer National UK.
Road data
Road network data
Road trip planners, sometimes referred to as route planners , use road and path network data to calculate routes by using only network connectivity (i.e. travel can be run at any time and not limited by schedule). The data can come from one or more public, commercial or crowdsourced datasets such as TIGER, Esri or OpenStreetMap. The fundamental data is good for calculating foot access to reach public transport stops, and to calculate road trips on their own right. Basic representations are graphs of nodes and edges (ie points and links). The data can be annotated further to help travel planning for various modes;
- Road data can be characterized by the type of road (highway, main road, path, path, etc.), turn restrictions, speed limits etc., as well as average travel time at different times of the day on different day types ( Business Day, Weekend, Public Holidays, etc.), so accurate trip time predictions can be offered
- Cycle path and path data can be annotated with characteristics such as cycle route number, traffic level, surface, lighting, etc. which affect its usefulness by cyclists.
- Path data can be annotated with accessibility characteristics such as step, elevator, wheelchair access, ramps, etc., etc., as well as safety indicators (eg lighting, CCTV, help point) so that the limited travel plan accessibility can be calculated.
Real-time data for road
The advanced road travel planner takes into account the real-time state of the network. They use two main feed types to do this, obtained from a data path service using interfaces such as Datex II or UTMC.
- Situational data , which describes planned, structured incidents, events and roadworks that may be network-related; is used to decorate travel plans and road maps to show the current bottleneck and location of the incident.
- Associate traffic flow data , which provides a quantitative measurement of the flow of current on each monitored network link; this can be used to calculate the actual conditions when calculating the predicted trip time.
Public transport data
Stop data
The location and identity of public transport access points such as buses, tram and stop trainers, stations, airports, ferry landing and ports are fundamental to travel planning and stop data sets are an important layer of transport data infrastructure. To integrate stops with spatial search engines and routing paths they geocode. To integrate them with schedules and routes, they are given unique identifiers in the transport network. In order to be recognized by passengers, they are given official names and may also have public short codes (eg three-letter IATA codes for airports) for use in the interface. Historically, different operators often use different identifiers for the same termination and termination of numbers is not unique in a country or even a region. Systems for managing discontinuation data, such as the International Railway Station location station (UIC) station set or the UK National Access Point (NaPTAN) system for stop numbers provide the means to ensure unique and stop numbers are fully explained, greatly facilitating data integration. Time-exchange formats such as GTFS, TransXChange or NeTEx include stopping data in spatial data formats and such as OpenStreetMap allowing identifiers to cease to be geocoded.
Data topology of public transport network
For public transport networks with very high service frequencies, such as urban metro cities and inner city bus services, network topologies can also be used for route planning, with assumed average intervals rather than specific departure times. Data on rail and bus routes is also useful for visualizing results, for example, to plan rail routes on the map. National mapping agencies, such as the UK Ordnance Survey typically cover the Transport layer in their data set and the European INSPIRE framework includes links to public transport infrastructure in a series of strategic digital data. The CEN format of NeTEx allows physical layers (eg links of road and railway infrastructure) and logical layers (eg links between scheduled stop points on certain paths) of transport infrastructure to be exchanged
Schedule of public transport
Data on public transport schedules are used by travel planners to determine which trips are available at any given time. Historical rail data are widely available in national format, and many countries also have data buses and other modes in national formats such as VDV 452 (Germany), TransXChange (UK) and Neptune (France). Schedule data is also increasingly available in international formats such as GTFS and NeTEx. To allow the route to be projected onto the map, GTFS allows simple plot form specifications; while Transmodel-based standards such as CEN NeTEx, TransXChange also enable more detailed representations that can recognize constituent links and differentiate between different semantic layers.
Real-time prediction information for Public Transport
Trip planners may be able to enter real-time information into their database and consider them in the selection of the optimal route for travel in the near future. Automated vehicle location system (AVL) monitors the position of vehicles using GPS systems and can deliver real-time information and estimates to the travel planning system. Trip planner can use real-time interface such as CEN Service Interface for Real-Time Information to get this data.
Situation information
Situation is a software representation of an incident (eg security warning, cancellation or severe weather) or events that affect or may affect the transport network. The trip planner can integrate the situation information and use it to revise its travel planning calculations and annotate their responses to inform users via text and map representation. The trip planner will usually use a standard interface such as Siri, TPEG, or Datex II to get situation information.
Incidents are captured through an incident arresting system (ICS) by different operators and stakeholders, for example in a transport operator control room, by a broadcasting agency or by emergency services. Text and image information can be combined with travel results. Recent incidents may be considered in routing and visualized in an interactive map.
Technology
Usually travel planners use an efficient in-memory representation of networks and schedules to allow quick search of a large number of paths. Database queries can also be used where the number of nodes required to calculate small trips, and to access additional information related to travel. One machine may contain the entire transport network, and schedule, or allow for the calculation of distributed travel using a distributed travel planning protocol such as JourneyWeb or Delfi Protocol. The travel planning machine can be accessed by different front ends, using software protocols or a special application program interface for travel inquiries, to provide user interfaces on different types of devices.
The development of the travel planning engine has joined hands with the development of data standards to represent the stops, routes and schedules of the network, such as TransXChange, NaPTAN, Transmodel or GTFS ensuring that these fit together. The travel planning algorithm is a classic example of a problem in the field of computational complexity theory. Real-world implementation involves the tradeoff of computational resources between the accuracy, completeness of the answers, and the time required for calculation.
The sub-issue of route planning is a much easier problem to solve because it generally involves less data and fewer constraints. However, with the development of a "road schedule", linking different travel times to different streets, travel times are also increasingly relevant to route planners.
Algorithm
The trip planner uses a routing algorithm to look for graphs representing the transport network. In the simplest case where routing is independent of time, the graph uses the (directed) edge to represent the path/path segment and the node to represent the intersection. Routing on such graphs can be effectively achieved using any of a number of routing algorithms such as Dijkstra, A *, Floyd-Warshall, or Johnson's algorithm. Different weights such as distance, cost, or accessibility can be attributed to each edge, and sometimes with nodes (eg where there are traffic signals).
When time-dependent features such as public transport are included, there are several proposed ways to represent transport networks as graphics and different algorithms can be used such as RAPTOR
Commercial software
Distribution companies can incorporate route planning software into their fleet management systems to optimize route efficiency. Route planning arrangements for distribution companies will often include GPS tracking capabilities and advanced reporting features that enable dispatchers to prevent unplanned disruptions, reduce mileage, and plan more fuel-efficient routes.
See also
- Pathfinding
- Automotive navigation system
- Travel technology
- Public transport route planner
- Transmodel
- TPEG
- The Service Interface for Real Time Information
- Intelligent Transport System
- Multimodal transport
References
Source of the article : Wikipedia
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