Passage to India Analysis Free Essays

Stylistics (writing) From Wikipedia, the free reference book | This article’sâ toneâ or style may not mirror the comprehensive tone utilized on Wikipedia. See Wikipedia’sâ guide to composing better articlesâ for recommendations. (October 2010)| Stylisticsâ is the examination and understanding of writings from a phonetic point of view. We will compose a custom exposition test on Section to India Analysis or then again any comparative point just for you Request Now As an order it linksâ literary criticismâ andâ linguistics, however has no self-ruling space of its own. 1][2] The favored object of expressive examinations isâ literature, yet not solely â€Å"high literature† yet in addition different types of composed messages, for example, content from the areas ofâ advertising,â pop culture,â politicsâ orâ religion. [3] Stylistics additionally endeavors to set up standards equipped for clarifying the specific decisions made by people and social gatherings in their utilization of language, such asâ socialisation, the creation and gathering ofâ meaning, criticalâ discourse analysisâ andâ literary analysis. Different highlights of stylistics incorporate the utilization ofâ dialogue, including regionalâ accentsâ and people’sâ dialects, engaging language, the utilization ofâ grammar, for example, theâ active voiceâ orâ passive voice, the conveyance ofâ sentenceâ lengths, the utilization of particularâ language registers, and so on. What's more, stylistics is an unmistakable term that might be utilized to decide the associations between the structure and impacts inside a specific assortment of language. Accordingly, stylistics sees what is ‘going on’ inside the language; what the etymological affiliations are that the style of language uncovers. Contentsâ â [hide]â * 1 Early twentieth century * 2 Late twentieth century * 3 Literary stylistics * 3. 1 Poetry * 3. 2 Implicature * 3. 3 Tense * 3. 4 The purpose of verse * 4 See additionally * 5 Notes * 6 References and related perusing * 7 External links| â€â€â€â€â€â€â€â€â€â€â€â€â€â€â€â€- [edit]Early twentieth century The investigation of artistic style returns to Classical talk, yet current stylistics has its underlying foundations in Russian Formalism,[4]â and the related Prague School, in the mid twentieth century. In 1909, Charles Bally’s Traite de tylistique francaiseâ had proposed stylistics as a particular scholastic control to complementSaussurean linguistics. For Bally, Saussure’s semantics without anyone else couldn’t completely depict the language of individual articulation. [5] Bally’s program fitted well with the points of the Prague School. [6] Build ing on the thoughts of the Russian Formalists, the Prague School built up the idea ofâ foregrounding, whereby wonderful language stands apart from the foundation of non-artistic language by implies ofâ deviationâ (from the standards of regular language) orâ parallelism. 7] According to the Prague School, the foundation language isn’t fixed, and the connection among lovely and ordinary language is continually moving. [8] â€â€â€â€â€â€â€â€â€â€â€â€â€â€â€â€- [edit]Late twentieth century Roman Jakobsonâ had been a functioning individual from the Russian Formalists and the Prague School, before emigrating to America during the 1940s. He united Russian Formalism and American New Criticismâ in his Closing Statementâ at a gathering on stylistics at Indiana Universityâ in 1958. 9] Published as Linguistics and Poeticsâ in 1960, Jakobson’s address is frequently credited with being the primary intelligible plan of stylistics, and his contention was that the investigation of graceful language ought to be a sub-part of phonetics. [10] The poetic functionâ was one of six generalâ functions of languageâ he portrayed in the talk. Michael Hallidayâ is a significant figure in the improvement of British stylistics. [11] His 1971 study Linguistic Function and Literary Style: An Inquiry into the Language of William Golding’s ‘The Inheritors’â is a key exposition. 12] One of Halliday’s commitments has been the utilization of the termâ registerâ to clarify the associations among language and its specific situation. [13]For Halliday register is unmistakable fromâ dialect. Vernacular alludes to the constant language of a specific client in a particular geological or social setting. Register depicts the decisions made by the user,[14]â choices which rely upon three variables:â fieldâ (â€Å"what the participants†¦ are really occupied with doing†, f or example, talking about a particular subject or topic),[15]tenorâ (who is participating in the trade) andâ modeâ (the use to which the language is being put). Fowler remarks that various fields produce diverse language, most clearly at the level of vocabulary (Fowler. 1996, 192) The linguist David Crystalâ points out that Halliday’s ‘tenor’ remains as a generally equal term for ‘style’, which is an increasingly explicit option utilized by etymologists to maintain a strategic distance from uncertainty. (Precious stone. 1985, 292) Halliday’s third category,â mode, is the thing that he alludes to as the representative association of the circumstance. Downes perceives two particular angles inside the class of mode and recommends that in addition to the fact that it describes the connection to the medium: composed, spoken, etc, yet in addition portrays theâ genreâ of the content. Downes. 1998, 316) Halliday alludes to kind as pre-coded language, language that has not just been utilized previously, however that predetermines the determination of printed implications. The linguist William Downes â makes the point that the foremost trait of register, regardless of how curious or different, is that it is clear and promptly unmistakable. (Downes. 1998, 309) â€â€â€â€â€â€â€â€â€â€â€â€â€â€â€â€- [edit]Literary stylistics In The Cambridge Encyclopedia of Language, Crystal sees that, by and by, most elaborate examination has endeavored to manage the complex and ‘valued’ language inside writing, I. . ‘literary stylistics’. He proceeds to state that in such assessment the degree is once in a while limited to focus on the all the more striking highlights of scholarly language, for example, its ‘deviant’ and anomalous highlights, as opposed to the more extensive structures that are found in entire messages or talks. For instance, the minimized language of verse is bound to uncover the insider facts of its development to theâ stylisticianâ than is the language of plays and books. (Gem. 1987, 71). [ edit]Poetry Just as traditional styles of language there are the capricious †the most clear of which isâ poetry. In Practical Stylistics, HG Widdowsonâ examines the conventional type of theâ epitaph, as found on tombstones in a burial ground. For instance: His memory is cherished today As in the hour he died. (Ernest C. Draper ‘Ern’. Kicked the bucket 4. 1. 38) (Widdowson. 1992, 6) Widdowson mentions that such assumptions are normally not exceptionally fascinating and recommends that they may even be excused as ‘crude verbal carvings’ and rough verbal unsettling influence (Widdowson, 3). By and by, Widdowson perceives that they are an undeniable endeavor to pass on sentiments of human misfortune and protect tender memories of a cherished companion or relative. Be that as it may, what might be viewed as graceful in this language isn't such a great amount in the formulaicâ phraseologyâ but in where it shows up. The section might be given undue worship correctly on account of the dismal circumstance in which it is put. Widdowson proposes that, not at all like words unchangeable in a burial ground, verse is unconventional language that vibrates with between literary ramifications. Widdowson. 1992, 4) Two issues with a complex investigation of verse are noted by PM Wetherill in Literary Text: An Examination of Critical Methods. The first is that there might be an over-distraction with one specific element that may well limit the criticalness of others that are similarly significant. (Wetherill. 1974, 133) The second is that any endeavor to consider a to be as esse ntially an assortment of expressive components will in general disregard different ways whereby importance is delivered. (Wetherill. 1974, 133) [edit]Implicature In ‘Poetic Effects’ from Literary Pragmatics, the linguist Adrian Pilkingtonâ analyses the possibility of ‘implicature’, as actuated in the past work of Dan Sperber and Deirdre Wilson. Implicature might be separated into two classifications: ‘strong’ and ‘weak’ implicature, yet between the two boundaries there are an assortment of different other options. The most grounded implicature is what is decidedly suggested by the speaker or author, while more vulnerable implicatures are the more extensive prospects of implying that the listener or peruser may finish up. Pilkington’s ‘poetic effects’, as he terms the idea, are those that accomplish most importance through a wide exhibit of powerless implicatures and not those implications that are essentially ‘read in’ by the listener or peruser. However the distinctive moment at which feeble implicatures and the listener or reader’s guess of importance wander remains exceptionally abstract. As Pilkington says: ‘there is no obvious off point between suspicions which the speaker unquestionably underwrites and presumptions inferred simply on the hearer’s duty. ’ (Pilkington. 991, 53) what's more, the complex characteristics of verse can be viewed as a backup to Pilkington’s lovely impacts in understanding a poem’s m

Climate Change Essay Example | Topics and Well Written Essays - 1000 words

Environmental Change - Essay Example Portray three key discoveries of the AR4 report that are referenced in the Introduction Section. Key discoveries include: 1. An expansion in worldwide normal air and sea temperatures, across the board dissolving of day off ice and rising worldwide ocean levels 11 out of most recent 12 years from 1995-2006 position among the 12 most sizzling a long time on record Global ocean level ascent of 1.8mm from 1961-2003 Polar ice tops contracting †Artic ocean ice degree shrank 2.7% every decade Changes in precipitation †decrease in Mediterranean, Sahel, southern Africa and increment in eastern piece of North and South America, North Europe 2. Normal frameworks are being influencing by local environmental change, especially temperature increment Glacial overflow increment chilly lake sizes Hydrological impacts †increment spillover, prior spring top release, warming of lakes/streams, which impacts warm structure and water quality 3. Impacts of local environmental change in common and human condition are rising, albeit many are hard to recognize because of appropriation and non climatic drivers Agricultural changes †planting crops prior on in the year Increase in climatic wellbeing dangers, for example European 2003 warmth wave executed 15,000 individuals in France What is the distinction among characteristic and anthropogenic drivers of environmental change? Give a case of each. Common changes allude to climatic modifications in the Earth’s air that aren’t influenced by people. Cosmic Effects Terrestrial Effects Orbital changeability of the Earth Global geometry of landmass/sea conveyance Solar tempests and flares Ocean tide cycles Sunspot cycles Periodic sea flow changes, for example El Nino These procedures control the measure of suns radiation arriving at explicit latitudinal zones on Earth Volcanic emissions Anthropogenic drivers have additionally been featured as adding to environmental change and quickening the warming of the Earthà ¢â‚¬â„¢s climate. Models incorporate expanded CO? (280ppm from pre modern levels to 379pmm by 2005), consuming of petroleum derivatives, deforestation, CFC’s and mist concentrates and from farming, for example dairy animals discharging critical measures of methane. What is an ozone harming substance (GHG), and how have their levels changed in the climate changed since 1970? A GHG is a gas in the Earth’s air that adds to the nursery impact through engrossing and discharging radiation causing environmental change. They incorporate CO?, methane, nitrous oxide and halocarbons. Changes in the air groupings of ozone harming substances and mist concentrates, land spread and sun powered radiation modify the vitality adjusts of climatic frameworks. There has been a 70% expansion in worldwide GHG outflows because of human exercises between 1970-2004. CO? yearly outflows have expanded by 80% from 21 to 38 gigatonnes. CO? likewise speaks to 77% of complete anthropogenic GHG discha rges. Depict the SRES situations. What are they, and for what reason do we have more than one of them? SRES alludes to the situations depicted in the IPCC Special Report on Emission Scenarios. The SRES venture an expansion of benchmark worldwide GHG outflows by a scope of 9.7 to 36.7 GtCO? †eq (25% to 90%) between 2000-2030. The SRES situations are gathered into 4 situation families (A1, A2, B1, B2). They investigate elective advancement pathways, covering a wide scope of segment,

Stablecoins, Rather than Cryptocurrencies, Might be the Future of Money

Stablecoins, Rather than Cryptocurrencies, Might be the Future of Money There’s a lot of talk about how cryptocurrencies are the future. Many people expect them to revolutionize how we do trade.In any case, aren’t they a product of technology and innovation? And aren’t technology and innovation the driving forces behind change and convenience?Cryptocurrencies have certainly come a long way. Since 2009 when Bitcoin was created, there has been no going back.You would think that Bitcoin was all that was needed. Or maybe just a few alternatives would be good enough for the expected change. Not so.New cryptocurrencies are always coming up faster than they can be counted. By the end of 2018, there were over 2,500 cryptocurrencies.However, only 25 out of those made up 90% of the total market capitalization.And you know what? Bitcoin took 59% of the total market capitalization of those 25. clearly, Bitcoin still reigns.Still, the cryptocurrency journey has been long. But there is certainly some progress.Coinbase, a leading US crypto exchange saw user numbe rs grow from 0.4 million in Jan 2017 to 5.6 million by June 2018.Of all ICOs (the cryptocurrency version of IPOs), only 8% have become successful.Fraudsters have also developed an interest in cryptocurrencies. Each day, scams cost investors $9 million worth of cryptocurrencies.But even with achievements, something still holds them back.To a large extent, there’s one thing that is really making it difficult for cryptocurrencies to replace fiat money.If this one thing is taken care of, then the revolution will indeed take place.This challenge is the inability of cryptocurrencies to maintain stable prices.As a means of exchange, it’s necessary that the payment method used should be stable. There’s no way a currency will be changing value radically as witnessed in the case of cryptocurrencies.Consider the below graph showing the price of Bitcoin in the span of 1 week. Source: OmenicsMaking Cryptocurrencies StableEfforts have been made to make cryptocurrencies as stable as possible. Unfortunately, they haven’t paid off. The reason is connected to the fact that these currencies are decentralized in nature.If you think of how fiat money works, the federal reserve (or any other central bank) is squarely in control.From the supply to the value, the central bank is in charge of keeping things in order.Of course, there are instances that even the central bank may find it difficult to do this. For example, in cases of extremely high inflation, all the normal actions which the central bank can take will offer little help.Such cases are however more of an exception than the norm. So generally, the control of money is central. Eliminating this central control is part of the vision of cryptocurrencies.And in all the research and innovation efforts, the solution seems to be stablecoins. At least as far as price stability is concerned.The stability of cryptoc urrencies will help drive adoption rates. Once that is done, there will be no stopping the revolution.But what are these stablecoins and how are they solving the stability problem?How Stablecoins Differ from Other CryptocurrenciesFirst of all, stablecoins are cryptocurrencies. They therefore have the same underlying technology as Bitcoin, Ethereum and the others.There is however a big difference which has been brought about by the need of stability as explained above.Stablecoins are cryptos which are meant to serve only this one purpose. With price value being stable, it will be easier for coin holders to be able to more easily determine the value of their holdings.Many of the stablecoins in operation attain their stability by undergirding their value using fiat money. The most common being the US dollar.This is referred to as collateral.Some however use different means to achieve the same results.There are at least three common types of collateral used by stablecoins.The type of co llateral is what usually differentiates them from one another at the highest level.TYPES OF STABLECOINSThe collateral used to make stablecoins stable is a form of asset. Since the asset has its own value, the value of the stablecoin then gets determined by the asset’s value.Whereas some assets are simple to understand, like the US dollar asset, some are relatively complex.Here is a brief discussion on the various types of collateral used.Fiat-CollateralizedThis is the most common and is also the easiest to understand of the three types.As the easiest to understand, it’s also the one which has received the highest adoption.And the currency used as collateral is the US dollar.Stablecoins having the US dollar as the underlying asset have attracted a lot of attention from stock traders. Early adopters have also jumped onto the bandwagon. Those new to the crypto world also find it easy to embrace them due to their simplicity.In this type, every coin is valued at $1. This means that t he rate of the coin to the dollar is 1:1.When the value of a coin is pegged at 1 US dollar, you can easily tell how much your investments are worth. In the real world of physical goods and services, you can determine how much you can own or do.For example, using the coin value, you can easily determine whether you can buy a new TV, car, home etc.The success in stability and adoption are however not without challenges.Fiat-collateralized stablecoins have been accused of going against the principle of decentralization.This is because fiat money is controlled by a central agency. All the control is therefore in the hands of that agency. As such, critics raise this as an issue and attempt to invalidate the coins.An example of this is Tether (USDT).Crypto-CollateralizedAnother form of collateral is using a different cryptocurrency. This has its own set of challenges.Naturally, all cryptos are unstable in their value. In order to achieve acceptable stability, these stablecoins peg their v alue on a mix of cryptocurrencies.This provides a shield because the coin does not depend on only one crypto as collateral.Still, these stablecoins are not fully stable and haven’t been embraced much. The fact that the mix of collateral is the same unstable cryptocurrencies makes it difficult to attain stability.All the same, these are more accepted among the cryptocurrency community compared to the fiat-collateralized coins. This is because they maintain decentralization.An example of this is MakerDAO/DAI Non-CollateralizedThese stablecoins are the most technically advanced of all three. Their lack of collateral is based on complex algorithms which find their basis in economics.Having no collateral, they rely on their own systems to control the supply and value of their coins. This is why they are also referred to as algorithmic stablecoins.As such, these coins handle both these aspects using the code specified during creation.The supply of any currency is directly connected to i ts value.Therefore, to reduce an oversupply which reduces the value, the system comes up with “bonds” for selling. As speculators buy these, the supply of the coins reduces.If the supply is too low, thereby increasing the price, more coins are issued. This has the effect of bringing the price back to the defined normal.Algorithmic stablecoins utilize the system of Seigniorage Supply to achieve this. And interestingly, this mode of operation is actually what is done by central banks.One of the ways central banks regulate the value of their currencies is by controlling supply. If there is an option which is truly technology driven, then it is this one.As with the other types, a challenge exists for these too. The bonds can be a tricky investment option since they have to guarantee a profit.An example of this is NuBits (USNBT).BENEFITS OF USING STABLECOINSStablecoins have undoubtedly ushered in a new dawn. This is especially for early adopters of technology and speculators.And as t heir stability continues dominating conversations, more entrants are coming into the market. This is how the market looked like as at May 2019. Source: Finance MagnatesTheir use has been embraced for a variety of reasons.Here are some of them.Make it Easy for Cryptocurrencies to be AdoptedThe original cryptocurrencies were difficult to understand, thus difficult to both appreciate and embrace. All the technical jargon and explanations left many believing that this was for geeks.It was difficult to prove their use in the real world of exchanging goods and services. But stablecoins are slightly different, especially the fiat-collateralized type.When you explain to a layman that stablecoins are a form of digital money, it’s easy to see how. The fact that one coin has the same value of one US dollar makes it easy to be understood.Once it’s understood, then adoption becomes easy. And if they can be widely accepted, then they will have achieved their goal.Reduced VolatilityAs their name suggests, these coins are intended to be stable in price. That is also the biggest reason for their developmentâ€"reduce price volatility.To t his end, all the three types are promising acceptable results. But of the three, the fiat-backed stablecoins are the winners this far.A coin like Tether   has already experienced a lot of success on this basis.The coins backed by other cryptocurrencies are yet to be widely embraced.This is because of the underlying challenges with cryptocurrencies generally being unstable.It thus doesn’t become easy to convince someone that a crypto will be stable yet it has its backing on an unstable asset.Can Be Easily ValuedStablecoins, especially the fiat-backed type can easily be valued. It’s actually as easy as just getting the account balance and using the dollar symbol to understand or communicate the value.For example, you may have 1,000 Gemini Dollars. This simply means that you have 1,000 US dollars. This will make it easy for adoption into the daily transactions in the world.For example, a camera may cost $100. To buy it, you will only need 100 Gemini dollars. This means that to enab le payments at the POS, only a stablecoin payment option may be needed for the retail outlets.When developers come up with these, everything will flow quite easily.Faster and Cheaper Money TransferBeing a digital solution, there are bound to be many advantages of this technology. One of them is that they facilitate faster and cheaper money transfer.Imagine a situation where it usually cost your bank $2 to transfer money to your relative in another country. This is the total cost from the employee, power bill and audit for human error.Now imagine all these removed. Probably the cost of system audits is 50 cents. If the bank is to use an advanced means for the transfer, it will be both cheaper and faster.This is what JP Morgan is doing using their JPM Coin.LIMITATIONS OF USING STABLECOINSNothing can be all advantageous and lack any disadvantages.As stablecoins continue to grow towards maturity, it pays to consider their shortcomings.This will help you determine whether to jump in righ t now or to adopt a wait-and-see attitude.Most are Only Backed with the USDThere are several stablecoins which are already enjoying some degree of acceptance.These are mostly the fiat-backed types. Whereas that is a good thing, there is one potential drawback.Most of them are pegged on the US dollar.This might be as a result of many of the companies being American. It might also be due to the fact that the US dollar is the currency used in international trade as well as in holding reserves.Either way, this may prove problematic. Being new and with little proof of tested and verified long-running successes, over-reliance on the dollar may not be the best idea.As it is, some countries and regions are already toying with the idea of abandoning the dollar for use with reserves. Some are suggesting different currencies for reserves while others are looking to return to gold.Since stablecoins are aiming at replacing fiat money, consistency is a must. Just as fiat money was initially based on gold , the same needs to apply to stablecoins.But having one currency as the backbone of stablecoins may not work for the long-term.In any case, as a technological solution, other countries will obviously want their currencies to be the collateral.And just how practical will it be, for instance, for China and Iran to run their stablecoins on the USD?Do Not Factor in InflationIf you are an investor, you know that you can never value your investments at a 1:1 rate to the dollar. Neither can you do the same with any currency.Why?There is inflation to be factored in.One principle of investment says that the value of money held today is not the same as of money to be received tomorrow. This is referred to as the Time Value of Money. For example, you may buy 1,000 stablecoins. At the moment of purchase, your investment is worth $1,000. However, what happens if the rate of inflation rises?With a higher inflation rate, the value of money reduces.The 1:1 rate of value stays the same. If $1 becomes less valuable, so does your investment. This means that stablecoins do not provide investors any considerable protection against inflation.Fiat-Collateralized Type Aren’t DecentralizedAs cryptocurrencies, stablecoins need to maintain a decentralized nature.This is one of the criticisms the fiat-backed type is battling. And although it has already taken off and seems to be gaining popularity, some are rejecting it for being centralized.The fiat-collateralized stablecoins have three main points of control.The first is the underlying assetâ€"in most cases the USD. The US dollar is itself controlled by a central agency. As such, it is a centralized system. Secondly, the money used to back the coins must be available in a physical sense for the sake of withdrawals back to USD.That money is usually stored in a bank.That is another party introduced right there. Mind you, the bank is controlled by its own management.It’s also under the control of the same central agency contr olling the USDâ€"the federal reserve.The third point of control is the organization running the stablecoin.The way cryptocurrencies originally function, is by setting all the rules in the code. There is very little change from external sources that can be done to change how things work. If there is a need for change, forks are developed.But in the case of these coins, change can be introduced at various levels. This is against the philosophy of cryptocurrencies being decentralized.Requires Faith in the Underlying AssetOne of the biggest limitations is the need to have faith in the underlying asset.If the coin is backed by the USD, then you must have faith in the USD.You must first of all believe that it is a worthy asset to back your coins on. Although the US dollar has for decades enjoyed the faith of many, geopolitics can easily bring about changes to this.And before that even happens, there is already a stablecoin backed by the Euro and a stablecoin backed by the Japanese Yen.The se inconsistencies might be okay for local trade. But for international trade, there has to be one asset being used just as the USD is currently being used.CONCLUSIONStablecoins are under continuous development and improvement.Still, they have already established themselves as a possible future of money.If only the challenges facing them can be conclusively addressed, then we might experience the biggest change of the millennium.

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Analysis Of The Poem The Second Coming - 1586 Words

W.B. Yeats has written many different works but his most interesting is his poem â€Å"The Second Coming. This paper will conclude three summarized sources along with the writer’s opinion of the three sources of criticism of Yeats’ poem. A. Rhagu starts out comparing a thesis by Edward Proffitts to Yeats’ â€Å"rough beast† in The Second Coming. The thesis is that the â€Å"rough beast†, sphinx, is both male and female combined, but most do not actually support this thesis since â€Å"if all the creature has a sex, it would be male† which does seem true since anything female is usually overlooked. Yeats describes his beast being fully male and not even female as Proffitts’ thesis suggests because â€Å"adding a female element to it would dilute the terrifying nature of the creature† as if to say if this rough beast was female, it would not be seen as high and mighty as it is seen. If it was female it would dampen the â€Å"rea der’s imagination† of the sphinx itself. Rhagu then says that they do not know the location of the sphinx itself because it is â€Å"somewhere in the sands of the desert† in this poem. Rhagu says that the speaker states that â€Å"there are things to come† because the sleeping sphinx is that of the â€Å"civilization† of man. The sphinx is going throughout time in a â€Å"peaceful stony sleep† until it wakes up from a â€Å"nightmare† whereby the â€Å"security of civilization contains the seeds for its own destruction†, where the sphinx is thought to be the â€Å"rough beast† in the poem. Rhagu then tells theShow MoreRelatedSonnet Analysis : Ozymandias And The Second Coming1253 Words   |  6 Pages Sonnet Analysis: Ozymandias and The Second Coming Name: Date: Sonnet Analysis: Ozymandias and The Second Coming Ozymandias and The Second Coming are interesting pieces that easily capture the attention of the reader. From the titles to themes and other literary elements, it is indisputable that indeed these pieces qualify for analysis. 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The three main things that is analyzed by Homers book is that to do his extended simile on his poem he first establishes what event is occurring and he will be talking about on his next lines, when the regular poem doesn’t need to establish that onRead MoreCritical Analysis Of I Heard A Fly Buzz When I Died1381 Words   |  6 Pagesdeath. Her famous poem, I Heard a Fly Buzz When I Died, talks about death and the decay of the body. According to Helen Vendler’s Dickinson: Selected Poems and Commentaries, it gives an analysis of the I Heard a Fly Buzz When I Died in line 7 of the poem the king will be coming and will reclaim what belongs to him and when he comes it will be witnessed by the bystanders in the room. The King is coming for the deceased and coming to claim the soul. Death is the central part of this poem as it is a person

Bus Frequency Determination Using Passenger Count Data Free Essays

Tmnspn. Rcs:A Vol. 18A. We will write a custom essay sample on Bus Frequency Determination Using Passenger Count Data or any similar topic only for you Order Now No. 516. pi. 439153. Printed m ths U. S. A. 1984 0191-2607’81 s3. @3+m Pcrmon Rss L:d. BUS FREQUENCY DETERMINATION PASSENGER COUNT DATA Department USING of Civil Engineering, Transportation Research Institute, Tcchnion-Israel Technology, Haifa, Israel (Received 21 February 1983; in revised form 5 December 1983) Institute of Abstract-The importance of ridership information has led transit properties to increase the amount of manually collected data or alternatively to introduce automated surveillance techniques. Naturally, the bus operators are expected to gain useful information for operations planning by obtaining more accurate passenger counts. This paper describes and analyzes several appropriate data collection approaches for the bus operator in order to set the bus frequencies/headways efficiently. Four different methods are presented to derive the bus frequency: two are based on point check (maximum load) data and two propose the use of ride check (load profile) data. A ride check provides more complete information than a point check, but at a greater cost, and there is a question as to whether the additional information gained justifies the expense. Based on available old profiles, the four methods provide the bus scheduler with adequate guidance in selecting the type of data collection procedure. In addition, the scheduler can evaluate the minimum expected bus runs when the load standard is released and avoid overcrowding (in an average sense) at the same time. Alternative timetables are also investigated in conjunction with minimizing the required bus runs and number of buses for a single route. In this way, the derived headways can be analyzed within an acceptable range while considering the possible changes incurred indirectly to the fleet size. The integration between resource. saving and frequency determination procedures allows the scheduler’s performance to be improved. 1. IN7’RODUCI’ION AND ORJECTIVES It is well known that transit demand varies systematically by season, day-of-the-week, time of day, location and direction of travel. However, the absence of accurate data on travel patterns at the route level has made it impossible to deploy transit resources to match these variations and thus to increase the efficiency of system operation. Accurate ridership information is needed for transit planning and scheduling and also to comply with external reporting requirements (e. g. Section 15 of the U. S. Urban Mass Transportation Act). Consequently, some transit operators have started to use automatic passenger counters while others are adding more checkers to collect the data manually. The primary objective of passenger counts, from the transit operator’s viewpoint, is to set vehicle frequencies/headways efficiently on each route. Other uses of ridership information are in revenue estimation and measurement of dynamic patronage trends. The topic addressed in this paper is two-fold. The first segment involves the setting of bus frequencies in order to maintain adequate service quality and minimize the number of buses required by the schedule. The second is an evaluation tool to efficiently allocate the cost for gathering appropriate passenger load data at the route level. It is common to almost all bus operators worldwide for load profile information along the entire iThis study was written while the author was in 1982 at the Transportation Systems Center (IX), Cambridge, Massachusetts, U. S. A. TSC Support is gratefully acknowledged. 439 length of the bus route (ride check) to be gathered annually or every few years. Usually the most recent passenger load information will be at one or more selected stops along the route where the bus carries its heaviest loads (point check). A ride check provides more complete information than a point check, but is more expensive because either additional checkers are needed to provide the required data or an automated surveillance system is used. There is a question as to whether the additional information gained justifies the expense. The objective of this study is to explore the way in which a bus operator can use the old profile to determine whether the ride check method or the point check method is appropriate in collecting the new data. This paper attempts to achieve this objective through three major parts. First, a brief review is introduced, and thereafter four different methods are presented to derive the bus frequency: two are based on point check (max load) data and two propose the use of ride check (load profile) data. Second, a preliminary criterion is established for determining the appropriateness of each of the data collection methods. Third, in order to complete the evaluation of the point check and ride check methods, altemative timetables are derived along with consideration of the minimum fleet size at the route level. 2. POINT CHECK (MAX LOAD) AND RIDE CHECK (LOAD PROFILE) METHODS . 1 Review Generally, bus operators organize ride check surveys routinely at time intervals greater than or equal to one year and update their point check information 40 AVISHAI CEDER where P, is the average (over days) maximum number of passengers (max load) observed on-board in period j, c represents the capacity of a bus (number of seats plus the maximum allowable standees), and yj is the loa d factor during period j, 0 ;: 1. 0. For convenience, let us refer to the product y,c as d,, the desired occupancy on the bus at period j. The standard yi can be set so that 4. s equal to a desired fraction of the capacity (e. g. d, = number of seats). It is worth noting here that if P, is based on a series of measurements, one can take its variability into account. If the stochastic data allow, this can be done, for example, by replacing the average value in eqn (I) with P, + bZj where b is a predetermined constant and Z, is the standard deviation associated with P,. The max load data is usually collected by a trained observer who stands and counts at the bus stop believed to be located at the beginning of the max load section(s). This stop has usually been determined from old ride check data or from information given by a mobile supervisor. Often, these observers are told to count at only one stop during the whole day instead of moving to a different max load point at every period j. In this case the scheduling department identifies the point at which the bus is starting to carry a load associated with the heaviest daily load along the route. This method is referred to as Method I and can be written more explicitly as: $‘=? ,j=l,Z I ,†¦ , 9 several times a year for possible schedule revisions (see Vuchic, 1978). It is important to note that the frequency and the cross-sectional characteristics of these data collection procedures should be determined by the sampling techniques used. This statistical aspect, which is not part of this study, can be approached through a variety of literature about sampling and is mentioned specifically in Attanucci Ed al. (198 I). Schedule revisions range from completely new timetables for new or revised routes to daily adjustments that accommodate changes in working hours and school dismissal times. The methods used by the bus operator to set headways are commonly based on existing service standards. These standards are based on two requirements: (i) adequate spaces will be provided to meet passenger demand, and (ii) the upper bound value is placed on the headways to assure a minimum frequency of service. The first requirement is appropriate for heavily traveled route hours (e. g. peak period), and the second for lightly traveled hours. The first requirement is usually met by a widely used peak loud fucfor method (point check), which is similar to the max load procedure-both are explained below. The second requirement is met by the policy headway which usually does not exceed 60 min and in some cases is restricted to under 30 min. Occasionally, a lower bound value is set on the headway by the bus operator, based on productivity or revenue/cost measures. There are also mathematical programming techniques to approach simultaneously the problems of route design and service frequency (see Lampkin and Saalmans, 1967 for an example). Recently such a technique has been adopted to find the appropriate headway so as to maximize the social benefit subject to the constraints on total subsidy, fleet size, and bus occupancy levels (Furth and Wilson, 1981). This model may be shown to be useful in policy analysis. However, these mathematical programming models have not been generally adopted by transit schedulers since they are not sensitive to a great variety of system specific operational constraints. For example, they cannot simultaneously determine even spaced headways and uneven spaced headways for situations of scheduling exceptions. 2. 2 MUX loud methodr The purpose of the basic standard used by bus schedulers is to ensure adequate space to accommodate the maximum number of on-board passengers along the entire route, for a given time period (e. g. one hour). Let the time period be denoted asj. Based on the peak load factor, the number of buses required for period j is: where P, is defined as the load in period j associated with the daily max load point. Additional notations are: max i Pii = f P,, and ES j-1 j-l P, = max P, LS where there are q considered time periods; S represents the set of all bus stops i, and P, is a defined statistical measure (simple average or perhaps with the standard deviation consideration) of the total number of passengers which are on-board all the buses departing stop i during period j. Table 1 displays the ride check information which will be used throughout the paper. This is actual data collected on one route in Jerusalem-route 27(A) of Egged (The Israel National Bus Carrier). In Table 1, the first and second columns are the distances (in kilometers) between each two adjacent bus stops and the stop name, respectively. The set of stops S includes 34 i’s excluding the last stop. The first two rows represent the time interval, j = 1,2,. . . , 14, where each period of one hour is associated with a given column. In the third row are the number of buses scheduled in each period. The fourth row Bus frequency determination using passenger 1. Initial data count A data 441 Table for bus No. 27 direction: 12 59 1. 75 75 20 . 5 75 76 5. 9. 93 99 (25 ,511 102 16. to2 (81) (02 (98 ‘08 206 108 19. ,,, 126 (80 (84 192 (92 132 14, (95 195 (55 196 162 19. (93 18. (93 132 159 I. 1 (47 138 (35 (28 I,7 ,,a t,. (3. ‘(1 I32 10. 9 ,,a 108 96 78 78 78 78 53 33 19 20 (2 ____ ____ 158 20. 208 215 220 252 268 259 28. 280 280 250 28. 295 295 29. 299 252 2. 9 235 236 228 22. 212 2,6 (80 l-72 (5. 452 ,. O tar (0. 72 40 ____ 180 223 225 239 2. 5 2. 5 2. 5 250 2. 8 2. 3 2. 2. 5 2. 5 235 240 2. 0 239 203 198 195 200 (98 190 (78 159 (53 I38 135 115 105 93 95 90 68 ____ 175 235 220 220 220 220 230 255 2. 0 295 3,s 320 320 320 3m 300 290 290 320 250 290 3t0 310 285 255 210 (90 195 (75 (55 (00 (35 90 20 ____ 239 266 255 270 266 263 259 253 29. 265 270 273 253 259 2. 9 239 228 23, 2,7 (93 $75 ,. , 151 1. 7 t. 0 ,,a 95 8. 60 49 . 9 . 9 32 ,I ____ 280 351 375 379 375 378 37, 36, 3 6. 399 37, 37, 35. 37, 357 3. 7 335 239 2. 5 210 196 199 192 165 133 102 77 ;; ii 50 10 i; 42 10 –__ 320 411 395 392 397 3,. 395 398 390 387 390 40, 398 403 403 39. 55 339 3. 7 29. 299 270 25. 256 2. 8 209 192 179 136 120 109 (28 (0, 37 ____ 275 4. 1 450 462 . 95 . ,7 455 465 477 495 . BO 47, 455 474 4,. .,, . 50 . 26 120 350 3. 5 336 339 336 303 25. 2. 9 225 (92 183 (68 ‘80 255 26, 25. 273 257 273 285 297 29, 306 32. 3,s 3,2 315 303 29. 2. 9 2. 0 23. 229 20, ,,. ,53 (38 II iii 51 ____ (05 235 295 308 315 3,9 325 329 325 3,s 31. 9 320 320 32. 9 325 335 338 3,9 2. 3 2. 3 239 220 213 200 170 (65 155 153 155 (43 130 129 (15 70 30 . ___ 90 (08 ,. I 14, 150 I. 7 I. 4 I. 7 f50 (50 1. 4 1. 7 153 159 (59 $55 1. 7 ,,, I,, 4 17 123 (1. Il. iO5 93 57 39 36 30 2, 2. I. 9 6 0 ____ 225 2. 9 2. 5 2. 5 2. 0 23. 23, 228 228 219 219 216 215 20. 198 (85 (7, 1,. 3,. ii9 96 90 8, 69 5, ,A ii ii 15 12 ,a 9 i 3 -___ 37 . 2 42 47 50 5, 5, 52 5, 52 50 50 5. 5. 52 . 9 . , 40. 35 32 28 2, 23 1, 15 12 9 8 4 2 2 2 I , ____ 2. 85 3159 3232 33,3 3399 3. 20 3. 85 3557 3597 3575 3696 3732 37,5 3,,9 359. 3610 350. 3092 3096 2950 2793 25,. 25. 3 2356 2170 ,725 ,673 1596 ,376 12,. (07. (02. 7. 3 356 – – – – represents the policy headway which is equal to 60 min, and the fifth row is the desired occupancy, 4. As can be seen, 4 = 65 has been assigned to peak hours and 4 = 47 (the total number of seats) assigned to off-peak hours. The last column in the table represents ? Pv where each entry in the table is Pu j=l (an average value across several checks). Thus, the daily max load point is the 12th stop with a total of 3732 passengers and P, in eqn (2) refers only to those entries in the 12th row. The second point check method is based on the max load observed in each time period. That is, This method is called Met/Z. Table 2 lists the value of P. , and the values of Pi for allj based on the input data given in Table 1. The comparison between methods 1 and 2 and between the point check and ride check methods using more data sets is performed in a following section. 2. 3 Load profile methodr The data collected by ride check enables the scheduler to observe the load variability among the bus stops. Usually the distribution ,of loads will suggest possible improvements in route design. The most common operational strategy resulting from observ- ing the various loads is short turning (shortlining). A turnback point before the end of the route may be chosen, creating a new route overlapped by the existing route. Other route design related actions using the load data are route splitting and route shortening. For the route design considerations, bus operators frequently use the histogram of the average load plotted with respect to each bus stop without relating the loads to the distance between the stops. The only concern of these operators is to identify a sharp increase or decrease in the average load for possible route design changes. This has been observed at SCRTD (Los Angeles), CTA (Chicago)–while using the EZDATA program provided by the company ATE, Egged (Israel), and other bus properties world-wide. A more appropriate way to plot the loads is to establish a passenger load profile. In this technique, the loads are plotted with respect to the distance traveled from the departure stop to the end of the route. It is also possible to replace the distance by the average running time, but in this case it is desirable for the running time to be characterized by low and persistent variations. Two examples of the load profile are given in Figs. 1 and ‘2, exhibiting the data of two time periods appearing in Table 1. Each asterisk in the figures represents five passengers. The area under the load profile curve is simply passenger-miles, or in this example, passenger-kilometers, both of which are AVISHAI CEDER Table 2. Output indication of variables used in methods 1 and 2 320 1259 1359 1459 ,559 284 389 . ,1 0 0. 0 0. 6 ‘†¦Ã¢â‚¬ ¦. *‘†¦ 50 100 150 2po .. *. **.. **†¦.. * †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 2. 1 2. 9 3. 2 3. 5 3. 9 4. t 4. 7 5. 3 5. 5 5. 9 9. 5 5. 7 7. 3 7. 7 9. I 8. 5 9. 1 9. 5 10. 0 10. 4 IO. 6 10. 9 ,,. I 11.. 11. 5 12. 1 ‘2. 5 13. 2 13. 9 I.. 1 14. 8 15. 0 †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚ ¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ ’ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚ ¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦. †¦ Fig. 1. A load profile for one morning time period (8:00-8: 59) based on the data in Table 1. Bus frequency determination using passenger count data 443 NIJMSER PISSENGERS OF FOR INTERVAL ~500 TO 1559 DlSTlNcE (KY. 1 50 – NUMBEP PAssENGERI OF 200 250 300 ’ 350 400 450 500 I 100 150 L†¦Ã¢â‚¬ ¦.. 1†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 1†¦Ã¢â‚¬ ¦.. L†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ L†¦ *†¦.. ~.. *.. *†¦ ~†¦ **†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ *.. *.. ~†¦.. ~†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. *.. *†¦ *†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ *†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã ¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã ¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ 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¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚ ¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. Fig. 2. A load profile for one afternoon time period (15:0@-15:59) based on the data in Table 1. measures of productivity. If a straight line is drawn across the load profile at the point where the number of passengers is equal to the observed average hourly max load, then the area below this line but above the load profile is a measure of the non-productive service. When method 2 is used to derive the headways, and dj is equal to the number of seats then this measure is the empty seat-miles (or empty seatkilometers). Figure 1 is characterized by a relatively large value of empty seat-kilometers per bus in comparison to Fig. 2. However, the additional information supplied by the load profile enables one to overcome such an undesirable characteristic. This can be done by introducing frequency determination methods which are based on passenger-miles rather than on a max load measure. The first load profile method considers a lower bound level on the frequency or an upper bound on the headway, given that the bus capacity constraint is held. Method 3 is: q? = max One way to look at method 3 is that the ratio A,/L of the load P, (regardless of its statistical definition) as opposed to the max load (P,) in method 2. Method 3 guarantees, on the average basis of P,, that the on-board passengers at the max load section will not experience crowding above the given bus capacity c. This method is appropriate for frequent cases in which the schedulers wish to know the number of bus runs they can expect to reduce by relaxing the desired occupancy standard, avoiding overcrowding at the same time. This allows them to handle the following: (i) demand changes without increasing the available number of buses; (ii) situations in which some buses are needed elsewhere (e. g. breakdown and maintenance problems, or emergencies); (iii) fewer drivers than usual (e. g. due to budget cut, or problems with the drivers’ union). On the other hand, method 3 can result in unpleasant travel for an extended distance in which the occupancy is above 4. To eliminate or to control this possible undesirable phenomenon, another method is introduced. Method 4 establishes a level of service consideration by restricting the total route distance having loads greater than the desired occupancy. Method 4 takes the explicit form: is an average representative A. P. -A-,1 dj. L c 1 [ [ 4. L’ Ai1 pj c where Ii is the distance between stop i and the next stop (i + l), Aj is the area in passenger-miles (km) under the load profile during time period j, and L is the route length. The other notations are previ )usly defined in eqns (l)-(3). 4? =max St. 1 Ii I jJj. L, *I) 444 AVISHAICEDER by time of day are same to that indicated in Table 2, and for all five sets the capacity is c = 80 passengers. In method 4 based on eqn (5), three values are assigned to /I, for all j’s: 0. 1, 0. 2 and 0. 3. That is, 10, 20 or 30% of the route length is allowed to have an observed occupancy, P, exceeding the desired one, 4. The results for route 27(A) appear in Table 3. The headway results of the four methods are compared graphically in Fig. 3 where the results of method 4 are for only the 20% limit case (8, = 0. ). Similarly to Fig. 3, the results of the remaining four data sets are displayed only in the computer generated graphical form in Figs. 4-7. . These illustrations are used for further analysis of the results. The first comparison can be made between method 1 and method 2 for the point check decision. Obviously, it is less costly and more convenient to retain a n observer at one bus stop during the entire working day, than to assign the same observer or others to a different stop at every period j. This candidate bus stop is the one characteiized by P, (see eqn (2)). The comparison between the two methods is performed by the ,$ test between two sets of actual observations-P. , vs P, for each data set (see Ceder and Dressier, 1980). The results are as follows: where I, = {i: (P,,/F,) d,} or 4 is the set of all stops i in time period j such that the load Pq exceeds the quantity of 4 times the number of buses determined iteratively by F,, and pj is the allowable portion of the route length at period j in which Pti can exceed the product (4)()(d,). The other notations in eqn (5) are previously defined. By controlling the parameter /Ii it is possible to establish a level of service criterion. Note that for /I, = 0, /I, = 1. 0 method 4 converges to method 2 and method 3, respectively. 2. 4 Results of actual data and comparison A pL/l program has been written for all the four methods. This program, in addition to calculating the bus frequencies, determines the associated integer headway (in minutes) by simply dividing the length (in minutes) of a considered time period j by 4. , and rounding it to the nearest integer. The headway information is essential for the timetable preparation, as is explained in the next section. The input data presented in Table I and also the data taken from four more routes have been run by the program. The additional data are four Egged routes: 2(A), 2(B), 12(A), and 39(A)—all from Jerusalem. Their policy headway and desired occupancy Route (Direction) 27(A) 2(A) 2(B) d. f. 13 16 18 14 16 X2 63. 24 14. 59 58. 51 492. 82 117. 82 null hypothesis about equal methods (at the 5% significance level) reject don’t reject reject reject reject I4) 39(A) Bus frequency determination using passenger count data 445 BUS NO. 27 , DIRECTION A LEGEND o – METHOD + – METHOD . – METHOD 1 2 3 L (BY2OP a – METHOD 0’. 7:oO . . 9 . . oo 11-00 . . TIME 13. 00 OF DAY ’ * 15. 00 ’ . 1Ãâ€"00 1 . 19:oo 21 00 g Fig. . Comparison of headway results for route 27(A). Consequently, only in route 2(A) can the daily max load point replace the hourly max load point. The PL/l program provides this comparison. The graphical comparison between the headways in Figs. 3-7 shows the expected result: method 2 always gives the minimum headways while method 3 result s in the highest headways (except in 2 out of 82 time periods). Another characteristic of the headways, exhibited particularly in Figs. 4 and 5, is that the given policy headway (60min) is used during off-peak hours. A point worth mentioning is that the esults might be sensitive to the length of the time intervalj and that different time intervals may be used for peak and off-peak hours. Further analysis and comparison of the results are addressed in the following two sections. 3. A PRELIMINARY CRITERION IN DETERMINING FURTHER DATA COLLECTION METHODS In this section an assumption is tested that particular load profile characteristics suggest the data collection method to be used. The basic idea is to BUS NO. 2 , DIRECTION â€Å"A† . – METHOD 3 6, 04.. . . . . . . I a. . -METHOD LCBY20%1 * ’ . ’ 6. 00 800 10 00 12. 00 TIME OF 14. 00 DAY 16:OO 16 00 20. 00 2:oo Fig. 4. Comparison of headway results for route 2(A). 446 AVISHAICEDER BUS NO. 2 , DIRECTION â₠¬ËœB’ . 6 _ METHOD L CBY20T. l 01 . 5:oo . . 7 00 . 9 00 * 1100 . TIME . 13. 00 _ 15 00 OF DAY .. , 17 00 . 19 00 . . 21 00 23 00 Fig. 5. Comparison of headway results for route 2(B). provide the bus operator with adequate preliminary guidance in selecting the type of method based on old load profiles. The assumption to be investigated is that a relatively flat profile suggests the use of a point check procedure (method 1 or 2) whereas a ride check procedure (method 3 or 4) would be appropriate otherwise. One property of the load profile is its density, p. This is the observed measure of total passenger-miles (total ridership over the route) divided by the product of the length of the route and its maximum load (passenger-miles which would be observed if the max load existed across all the stops). Thus, the load profile density for hour j, pj, is P’=e. The load profile density is used to examine the profile characteristics. High values of p indicate a relatively flat profile, whereas low values of p indicate a significant load variability among the bus stops. A BUS 60 NO. 39 , DIRECTION â€Å"A† LEGEND % $ s 2 L2. 36. METHOD ‘ (BY ZCr%l = 30. p’ I 9 i P 12. 6. 24. 18. 0. 1 6 00 . a 00 . 10 00 . 12. 00 TIME OF woo DAY 16 00 18. 00 20 00 2200 Fig. 6. Comparison of headway results for route 12(A). Bus frequency determination using passenger count data 447 BUS NO. 12 , DIRECTION ‘A† LEGEND o _ METHOD + . METHOD METHOD 1 ;/ 2 3 : ,’ / ;* I 8 â €™ METHOD L (ByZoZl 0’ 500 I – I 1 7 . oo 9:oo 11:oo I . TpF ;nY15:00 ‘. 17:oo ‘ 19:oo ‘ ‘ Fig. 7. Comparison of headway results for route 39(A). 3. 1 Mathematical analysis One way to approximate the observed shapes of profile curves is by using a mathematical model. The lognormal model has been selected for this purpose since it provides a family of curves which can be controlled by varying the parameters p and u. The lognormal model takes the form: f(x) =. The equation satisfying (df(x)/dx) = 0, is e-oDX-*~/262; x ; 0. the optimum (7) conditions, x,=d-â€Å"= (8) This continuous model can only approximate some of the observed load profiles since it has only one peak and represents monotonically increasing and decreasing functions before and after this peak, respectively. Nonetheless, this model is useful in observing some general differences between the ride check and point check methods. In order to be able to compare the methods,f(x) is used as a normalized load (the load divided by the max load) and x is used as a normalized distance (the distance from the departure stop divided by the length of the route). At a given time interval of one hour, j, the considered max load is Pi = 650 passengers. Given that dj = 65 and that c = 100, the determined frequency and headway for both methods 1 and 2 are 4 = 10 and Hj = 6. By applying this information to methods 3 and 4, using a variety of lognormal curves, one obtains the frequencies and headways shown in Table 4. The results in this table are aranged in increasing order of density. For method 3, the capacity constraint determines the values of F and H up to an including p = 0. 64 and up to different p values (if any) for method 4. Examples of the lognormal normalized curves are shown in the computer generated Figs. 8 and 9 for two p and variety of p values. Note that the relative location of the max load point can be found by eqn (8). From Table 4 it appears that for method 3 the ride check (load profile) data results in the same rounded headway as for the point check (max load) data for p 2 a where 0. 4 ; a 5 0. 87. For method 4 the ride check and point check information tend to yield the same headways for p 2 ai where i = 1,2,3, for the 10, 20 and 30% cases, respectively, and 0. 34 ; a, I 0. 43, 0. 50 ; a2 I 0. 56, and 0. 64 ; a, 50. 68. 3. 2 Observed densities and discussion The five data sets mentioned in the previous section were also subject to the load profile density examination. The pi values for each considered hour j, based on eqn (6), were calculated and are shown in Table 5. For example, in Fig. 0, which is part of the PL/l program output, one can visually compare the load profiles associated with the highest and the lowest p value of data collected on route 39(A). As can be seen from Table 5, none of the p values exceed 0. 8. This suggests that one cannot reach, by calculation, same headways for method 3 and method 2. Figures 3-7 reveal that the determined headways of method 3 are always greater than those of method 2 excluding the cases of policy headway. However, no clear cut conclusion can be drawn when trying to associate the p values in Table 5 with those 448 Table 4. Frequencies (F) and headways log-normal AVISHAI CEDER (H) for different load profile configurations (derived from the model) using methods 3 and 4’ Method 3 profi 1e density T by 10% H F 7. 60 H Method 4 20% H 9 9 9 9 9 8 7 : 8 -%6 6 6 6 6 6 6 6 6 6 1 by by P F F F 30% H 9 9 9 9 9 9 0. 18 0. 25 0. 27 0. 32 0. 34 0. 43 E 0:48 0. 50 0. 56 0. 57 0. 59 0. 62 0. 64 0. 68 0. 75 0. 76 0. 78 0. 84 0. 87 *For Note: 6. 50 6. 50 6. 50 6:50 6. 50 6. 50 6. 50 6. 50 6. 50 6. 50 6. 50 6. 50 6. 50 6. 77 7. 46 7. 63 7. 77 8. 41 8. 72 9 9 9 9 E% 9’ z 9 9 9 9 9 9 9 : 7 7 -4. 8. 46 6. 50 8. 36 7. 55 9. 00 7 9 7 7 -i5: 6 6 6 6 6 6 6 6 6 6 6 6 6 6. 50 6. 50 6. 50 6. 50 6. 50 7. 05 8:05 E 7. 5 x 9:31 8. 85 9. 04 9. 42 9. 36 9. 68 9. 87 9. 76 9. 92 6. 50 6. 50 6. 50 6. 50 6. 50 6. 50 z! 9:45 9. 05 9. 92 9. 76 9. 81 9. 65 9. 79 9. 87 9. 86 9. 93 9. 97 9. 96 9. 97 constraint ?E 8’ 6:50 9 6. 50 9 9. 27 6 8. 16 7 8. 46 7 7. 80 7 8. 19 7 8. 72 -b 8. 76 6 9. 23 6 9. 72 6 9. 46 6 9. 82 6 Methods 1 and 2: Uhenever F-10. H=6 where d F =6. 50, H=9 the capacity = 65, c-100. is met. in Table 4 regarding the comparison between methods 4 and 2. Figures 3-7 clarify this by illustrating the results of method 4 for the 20% case. The matchings (same headways for methods 2 and 4) across all the five data sets range between p = 0. 38 (route 2(B), for the hour 22:00-22: 59) and p = 0. 744 (route 39(A), for the hour 16:00-l6:59). On the other hand, the non-matching cases range between p = 0. 457 (route 2(B), for the hour 8:00-8:59) and p = 0. 777 (route 12(A), for the hour 15:00-15:59). Consequently, when applying method 4 to the observed load profiles, the results of the lognormal model cannot be explicitly used and an actual comparison between methods 2 and 4 should be performed. In practice, the bus operator wishes to save bus runs and eventually to be able to perform the matching between demand and supply with fewer buses. As is shown in the next section, different headway values do not necessarily save bus runs or reduce the required fleet size. However, the analysis made about the profile density measure can be used by the bus operator as a preliminary check before entering a more comprehensive analysis. The following are practical observations: (i) for densities below 0. 5, p-o 66 OK 0 1 .2 .3 Fig. 8. Four approximated load profiles based on the log-normal model (a = 1. 00). Bus frequency determination using passenger count data Fig. 9. Four approximated load profiles based on the log-normal model (u = 1. 0). savings are likely to result by gathering the load profile information and using either method 3 or 4 (alternatively for such low p values, the profile can be examined for short turn strategies); (ii) for densities between 0. 5 and 0. 85, it is recommended that an actual comparison be made between the point check and ride check methods-along with further saving considerations (see next section ); and (iii) for densities above 0. 85 it is likely that the majority of the required information for the headway calculation can be obtained from a point check procedure (either method 1 or 2). . ALTERNATIVE The TIMETABLES AND FLEET SIZE possible to initiate the task of scheduling buses and crews to the previously determined trips. Naturally, the bus operator wishes to utilize his resources more efficiently by minimizing the number of required buses and the cost of the crew. To accomplish this, the scheduler examines different timetables during the bus and crew assignment processes. This is done by shifting the departure times or by reducing the number of departures without referring usually to the initial source of passenger loads-the profile. Therefore, it is desirable to extend the analysis deriving appropriate headways, to an evaluation of timetables in conjunction with the required resources. 4. 1 Construction of timetables The number of bus runs determined by the timetable and eventually the number of buses required, is sensitive to the procedure used by the scheduler to CONSIDERATION AT THE ROUTE LEVEL products of the derived headways are the timetables for the public, the bus drivers and supervisors. Once the timetables are constructed, it is Table 5. Load profile densities @) for five data sets I 500. ! :00 7:oo 8:00 9:oo lo:oo Time Interval : – 6:59 – 7:59 – 8:59 – 9:59 – 10:59 – 559 : Route Z(A) v-e 0. 489 Route Z(B) Route 12(A) ll:oo 12:oo 13:oo 14:oo 15:oo 16:00 17:oo l 19:oo 20:oo 21:oo 22:oo 23:00 – 11:59 12:59 13:59 14:59 15:59 16:59 17:59 18:59 19:59 20:59 21:59 22:59 23:59 0. 668 0. 557 0. 687 0. 548 0. 687 0. 477 0. 694 0. 652 0. 699 0. 606 0. 632 0. 73j 0. 610 0. 524 0. 588 0. 543 ___ 0. 524 0;702 0. 752 0. 457 0. 586 0. 592 0. 647 0. 620 0. 679 0. 764 0. 662 0. 717 0. 722 0. 618 0. 673 0. 633 0. 588 0. 538 0. 546 0. 661 0. 705 0. 625 0. 731 0. 637 0. 589 0. 680 0. 39 0. 740 0. 712 0. 777 0. 640 0. 565 0. 650 0. 509 –a _-_ -se -me ___ –0. 563 0. 567 0. 715 0. 765 0. 717 0. 672 0. 636 0. 733 0. 723 0. 641 0. 712 0. 639 0. 576 0. 593 ___ _____ Route 27(A) _-_ 0. 651 0. 561 0. 589 0. 674 0. 594 0. 559 0. 619 0. 644 0. 599 0. 691 0. 744 0. 626 0. 657 0. 544 0. 686 0. 610 0. 577 _-_ Route 39(A) 0. 0 0. 3 0. 4 0. 7 1. 1 1. 3 1. 7 2. 3 ?. I 2. 7 3. 1 3. 5 3. 9 4. 4 4. 9 †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 5. 6 5. 1 ‘6. 2 6. 4 6. 7 7. 1 7. 5 7. 8 8. 2 8. 4 8. 6 9. 0 9. 1 9. 2 9. 5 9. 6 †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. .; †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦ †¦ .* .. ** †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. Fig. 10. Two load profiles of route 39(A) with the highest density @ = 0. 744) on the left and the lowest density @ = 0. 544) on the right. construct the departure times. Some bus operators routinely round the frequency 5 to the next highest integer and then calculate the appropriate headways for the considered time period. By doing so, they increase the number of daily departures beyond what is needed to appropriately match the demand with the supply. Such a procedure may result in nonproductive runs (many empty seat-miles). For example, in Table 3 the number of daily required departures, F 4, is 77. 01, 55. 64 and 73. 24 for methods j=l 2,3 and 4 (20% case), respectively. When the quantity F, is â€Å"rounded up,† one obtains respectively: 85, 65 and 80 daily departures for these three methods. Obviously, by rounding k; to the next highest integer, the scheduler increases the level of passenger comfort but, at the same time, causes an unnecessary operating cost. However, in some cases the â€Å"round up† procedure may be justified if the scheduler uses the Pq quantity as an average load whereas the variance of the load is high. In this case (provided that additional runs are made by rounding up Fj), the possible overcrowding situations may be reduced as opposed to increasing the average empty seat-miles. Nonetheless, to overcome the problem of highly variable oads, one can use a statistical load measure which considers its variance as an input to a frequency method (see remarks in eqn (1)). Another characteristic of the existing timetables is the repetition of departure times, usually every hour (see Vuchic, 1978). These easy-to-memorize departure times are based on the â€Å"clock headways†: 6, 7. 5, 10, 12, 15, 20, 30, 40, 45 and 60 min. Generally, headways less or equal to 5 minutes are not considered by schedulers to influence the timing of passenger arrivals to a bus stop. The clock headway is obtained by rounding the derived headway down to the nearest of the above â€Å"clock† values. Consequently, and similar to the â€Å"round up† frequencies, the clock headways require a higher number of departures than what is actually necessary to meet the demand. In order to keep the total daily number of departures as close as possible to the sum of the obtained Fj’s by the four methods, the derived headways in Table 3 and Figs. 3-7 are simply based on the â€Å"round to the nearest integer† procedure. Note that for a high frequency value it may turn out that rounding Fj result in fewer departures than rounding the derived headway. However, for high frequencies, the timetable is not required. Also, if 5 is rounded first it is necessary to perform a second rounding on its associated headway (since timetables are built by headways-not frequencies). This by itself may ultimately decrease the accuracy of matching the demand with the number of departures. An attempt is made in Table 6 to construct six daily timetables for methods 2,4 and 3 using both the derived and the clock headways based on the information in Table 3. The only incompatability is that Bus frequency determination using passenger count data 451 Table 6. Various timetables for bus 27(A) based on methods used and considered headways Y I9 ii:01 :3a :oa :57 :15 a:17 :22 :3a :29 :59 :36 9:14 :43 ~24 :50 :34 :57 :44 14:04 :54 :I1 10:04 :1s :15 :25 :26 :32 :37 :39 :4a ~46 :59 :53 11:09 15:OO :ia :08 ~27 :I6 ~24 :36 :45 :32 :54 :40 12:03 :4a :13 :56 :23 16:06 :33 :la :43 :30 :si :i5 17:04 :30 :12 :45 :20 a:00 :2a :20 :36 :40 :44 9:oo :52 :lO ia:m :20 :la :30 :36 :40 :54 :50 19:oa 1o:oo :19 :lO :30 :20 :41 :30 :52 :4o 20:24 :50 21:17 11:OO :07. 5 :I5 :22. 5 :30 :37. 5 :45 :52. 5 12:oa :lO :30 :40 :50 13:oo :06 :12 :la ~24 :30 :36 :42 :4a :54 14:oo :06 :12 :la ~24 :30 :36 ~42 :4a :54 1s:oo :07. 5 :15 z22. :30 :I5 :52. 5 16:Ml :12 ~24 :36 :4a 17:oo :07. 5 :15 :22. 5 :30 :37. 5 :45 :52. 5 la:00 :15 :20 :ll :40 :19 a:03 :27 :29 :35 :55 :43 9:13 :5i :23 :59 :33 14:06 :43 :13 :53 :20 10:03 ~27 :14 :34 :25 :41 :36 :4a :47 :55 :5a 15:oz ii:08 :lO :17 ii; :26 :34 :3s :44 ~42 I :53 :5Ll ! lZ:Oi :G :12 16:oa :21 :34 :34 :44 :47 :12:54 17:W :la ~27 :36 :45 :54 ia:oa ~27 ~46 :59 19:ll :23 :35 :47 2o:zo 21:15 ! uer~ved LIOC): Headway 00 12~30 16 00 7 :12 :23 ~24 :46 :36 a:lo :4a :36 17:w :55 :07. 5 9:oa I:00 :22. s :I5 :21 :10 :30 :34 :20 :37. 5 :22. 5 :46 :30 :30 :45 :37. 1o:oo :40 :52. 5 :15 :45 :50 14:oa :30 :52. 5 I:00 :06 :45 :10 :12 la:00 1l:OO :15 :20 :18 :I2 :30 :30 ~24 :45 :24 :40 :30 :36 19:oo :50 :36 :4a 1:oo ~42 :12 ~24 12:oa :07. 5 ~48 :15 :lS :54 :36 :30 :40 :22. 5 15:oo :45 :30 :07. 5 2o:oo 13:o o :45 ~27. 5 :15 :ll :45 :22. 5 21:30 :52. 5 :30 2:oo z37. 5 :10 :45 :44 :20 :52. 5 20’) i : . I :oo ’ I :lO :2o :Jo :40 :50 2o:oo :45 21:30 ! : z24 i ( i:: ; i ~55 uETmb3 He4dw4y , Clock HeadMy 14:os 7:oo 13:so 19:5 :20 14:oo :4 :14 :40 :07. 5 2o:a :23 :I5 a:00 21:c :32 :20 :22. 5 :41 :40 :30 :50 9:oo :37. 5 :59 :12 :45 15:08 :I4 :52. :ia 15:oo ~36 :2a :4a :10 :3fl 1o:w :20 :4a :15 :30 :5a :30 :40 16:lO :45 :50 :25 11:OO 16:OO :40 :12 :15 :55 ~24 :30 11:08 :36 :45 :20 :48 17:oo :32 . 44 12:oo :12 I56 :15 :I2 :30 :36 la: 16 :44 :45 :48 19:07 13:oo 18:OO :26 :lO :20 :20 :40 :45 :30 20:23 19:oo 21~23 :40 :15 I 1 the clock headway technique includes a value of 7. 5 minutes whereas the derived headways do not allow non-integers. The transition between the hourly periods for the derived headway is based on a smoothing rule that use the rounded down average headway whenever a transition from one hour to another occurs. For example, in method 2 the transition between the departures 8: 59 and 9: 14 is based on rounding down the average headway of 21 and 1Omin. A point worth mentioning here is that the schedulers often have the knowledge of different load patterns during one period j, e. g. more loads in the first half hour than in the second. In this case they can request splitting or changing the time period j for further data collection. Also, they can insert more departures in the heavy-load interval than in the remaining interval, while ensuring the approximate total of Fj departures. Further consideration about creating timetables appears in a report by Ceder (1983). This includes development of methods to construct timetables with even headways and timetables with even (average) loads on individual buses while the headways are unevenly spaced. 4. 2 Single-route fleet size examination Within a large-scale bus system, buses are often shifted from one route to another (interlining) and they frequently perform deadheading trips in order to operate a given timetable with the minimum required buses. It is desirable to analyze the procedures to construct timetables and scheduling buses to trips simultaneously. However, due to the complexity of this analysis, these two procedures are treated separately. Therefore, in a bus system with interlining routes, the alternative timetables can be evaluated on the basis of the total number of required departures. This can serve as an indicator for the number of buses required, but without inserting each alternative timetable to the scheduling procedure, it will be difficult to predict the effect on the fleet size. One fleet size test that can be performed is based on the assumption that interlinings and deadheading trips are not allowed and that each route operates separately. In this case, given the mean round trip time, the minimum fleet size for that route can be found similar to the formula derived by Salzbom (1972). Let T be the round trip time including the layover and turn around time and that departures occur at discrete time points: t,, t2, r,, . . . , t,. Also, let N, be the number of departures between and including the two departure points t, and t, such that three conditions (i) are fulfilled: t, ; tr, (ii) t, – tr I T and (iii) t,+, – t, ; T. Given that if t, = t, then the first tk, k = 1,2,. . . , n to agree with the first two conditions is t,. the minimum single-route fleet size, N,,,, is: Nmi,=max k i k=l Nk Following Salzborn arguments, eqn (9) simply means that N,, is the largest number of buses departing in any time interval of length T. This result can How to cite Bus Frequency Determination Using Passenger Count Data, Papers

Mrs. Tilschers Class Essay Example

Mrs. Tilschers Class Paper â€Å"Over the Easter term, the inky tadpoles changed from commas into exclamation marks.† Tadpoles could be imagined as being the same shape as commas at birth, and later on growing up to be of similar shape of the exclamation mark, which is also a metaphor. The reason to why this sentence has been added could be because the Carol Ann Duffy would like to remind the readers of the main topic of the poem which is about change. (From the classroom innocence to the sad reality of the world) â€Å"Three frogs hopped in the playground, freed by a dunce, followed by a line of kids, jumping and croaking away from the lunch queue.† Which adds a chaotic image and no longer is the paradise image indicated in the previous stanzas. â€Å"A rough boy told you how you were born. You kicked him, but stared at your parents, appalled, when you got back home.† As could be noticed, in this stanza there are starting to be some changes. The previous stanzas were all positive and paradise-like meanwhile this stanza starts to change the image. This could be considered the stage of changing from innocence to experience. All the experience is the sex and violence that are being introduced to the child. The last stanza is now the conclusion being said. â€Å"That feverish July, the air tasted of electricity. A tangible alarm made you always untidy, hot, fractious under the heavy, sexy sky.† Feverish could be a mixture of being hot in temperature as well as making you sick. Also feverish might mean that the children are feverish could be due to the hormone growth that they will be experiencing as they grow up. Synesthesia (Confusing senses/changing it) is used when describing the air’s taste as that of electricity. The heavy sexy sky might link to the confusion that the kids will be experiencing as they are growing up, their thought processes might slightly change and the way they look at things would start to be different. â€Å"You asked her how you were born and Mrs Tilscher smiled, then turned around.† It is definite that the child feels comfortable with asking Mrs Tilscher questions, just as if she was her own mother, which adds another evidence of the love that the child has for the teacher. Mrs Tilscher did not want to answer this question as the child is obviously too young to know the reality. We will write a custom essay sample on Mrs. Tilschers Class specifically for you for only $16.38 $13.9/page Order now We will write a custom essay sample on Mrs. Tilschers Class specifically for you FOR ONLY $16.38 $13.9/page Hire Writer We will write a custom essay sample on Mrs. Tilschers Class specifically for you FOR ONLY $16.38 $13.9/page Hire Writer â€Å"Reports were handed out.† The reports might also symbolize the end of childhood, as results are based on reflections of the past. â€Å"You ran through the gates, impatient to be grown, as the sky split open into a thunderstorm.† The thunderstorm could represent danger and the future life that is going to be waiting for all the children. On the other hand, the thunderstorm might simply be talking about how all the children ran through the gates at once, which implies as though it were like a thunderstorm. There is no more safety that was once in Mrs Tilscher’s classroom. That safety that was represented by Mrs Tilscher’s class has been replaced by the danger, the excitement, the thrill, and the thunderstorm of growing up. I believe Carol Ann Duffy’s poem has been a great success, as it makes the reader think back to his/her life when you were a child, and how things have always changed as you were growing up. A lot of literary devices have been used which added an interesting touch to the poem in order to address the overall theme of growing up. Duffy has done a great job with giving the readers a lesson to be learned, which shows us how life has changed since childhood.