Describe the following develop

Metro rails are rail-based, mass rapid transit systems thatoperate on an exclusive right-of-way, which isseparated from all modes of transport in an urban area. Most often,the right-of-way is either undergroundor elevated above street level. These systems generally operate atan average speed of 20–35 km/h,and are characterized by their high capacity (50,000–75,000passengers per hour, per direction) and highfrequency of operation. The capital cost of construction is between20–30 times that of the Bus RapidTransit system, depending on whether the metro systems areunderground or elevated (Mohan, 2008).There has been a growing interest among policymakers about therelevance of rail-based systems inIndia, to address the mobility needs of the expanding population inthe cities. While evaluating differentmass transit options for Indian cities, metro systems are oftengiven preference due to the belief thatroad-based bus systems cannot cater to capacity requirements asmuch as metro systems. In additionto this, metr rails are perceived to have higher levels of comfort,speed and efficiency, than bus systems,making them more attractive to both policymakers and potentialusers of the system.Promoters of metro systems often claim that one of the benefits ofthe metro is reduced congestion, dueto the users’ shift from road-based motorized modes to metrosystems. This mode shift is then claimedto result in reduced air pollution and road accidents. Due to theinduced demand,the available road space fills up with motorized vehicles, and themodal shift to metro does not result inthe reduction of congestion or air pollution. The concentration isapproximatelythree times higher than safe levels. Similarly, the eight-hourlymaximum current level of carbon monoxide(CO) is touching 6,000 microgram per cubic metre – way above thesafe level of 2,000 microgram percubic metre – though the annual levels have registered a drop.Overall, these figures illustrate that theoperation of the Delhi Metro has not led to a reduction inpollution levels in the city (Randhawa, 2012).Due to the limited coverage of the city by rail-basedsystems1, as opposed to road-based bus systems, ametro commuter spends significant time during access (from originto metro station) and egress (metrostation to destination). As a result of this additional time, eventhough the average main-haul (in-vehicle)speed of the metro is above 30 km/h, the average door-to-doortravel speed gets reduced for a short tripon the metro system – as compared to a road-based system. Hence,metro systems have been found tobe most favourable, in terms of saving time, if the trips are 10 kmor longer. Due to mixed land-use and thepolycentric nature of Indian cities with multiple central businessdistricts (CBDs), however, the majorityof trips remain below 5 km (Jain and Tiwari, 2011).

# Efforts on the sizes and densities of cities.

Metro rails are rail-based, mass rapid transit systems thatoperate on an exclusive right-of-way, which isseparated from all modes of transport in an urban area. Most often,the right-of-way is either undergroundor elevated above street level. These systems generally operate atan average speed of 20–35 km/h,and are characterized by their high capacity (50,000–75,000passengers per hour, per direction) and highfrequency of operation. The capital cost of construction is between20–30 times that of the Bus RapidTransit system, depending on whether the metro systems areunderground or elevated (Mohan, 2008).There has been a growing interest among policymakers about therelevance of rail-based systems inIndia, to address the mobility needs of the expanding population inthe cities. While evaluating differentmass transit options for Indian cities, metro systems are oftengiven preference due to the belief thatroad-based bus systems cannot cater to capacity requirements asmuch as metro systems. In additionto this, metr rails are perceived to have higher levels of comfort,speed and efficiency, than bus systems,making them more attractive to both policymakers and potentialusers of the system.Promoters of metro systems often claim that one of the benefits ofthe metro is reduced congestion, dueto the users’ shift from road-based motorized modes to metrosystems. This mode shift is then claimedto result in reduced air pollution and road accidents. However, theexperience of metro rails in low andmiddle income counties around the world shows otherwise (Mohan,2008). Due to the induced demand,the available road space fills up with motorized vehicles, and themodal shift to metro does not result inthe reduction of congestion or air pollution.Due to the limited coverage of the city by rail-basedsystems1, as opposed to road-based bus systems, ametro commuter spends significant time during access (from originto metro station) and egress (metrostation to destination). As a result of this additional time, eventhough the average main-haul (in-vehicle)speed of the metro is above 30 km/h, the average door-to-doortravel speed gets reduced for a short tripon the metro system – as compared to a road-based system. Hence,metro systems have been found tobe most favourable, in terms of saving time, if the trips are 10 kmor longer. Due to mixed land-use and thepolycentric nature of Indian cities with multiple central businessdistricts (CBDs), however, the majorityof trips remain below 5 km (Jain and Tiwari, 2011).

Network structure varies across cities. This variation may yieldimportant knowledge about how the internal structure of the cityaffects its performance. This paper systematically compares a setof surface transportation network structure variables(connectivity, hierarchy, circuity, treeness, entropy,accessibility) across the 50 largest metropolitan areas in theUnited States. A set of scaling parameters are discovered to showhow network size and structure vary with city size. These resultssuggest that larger cities are physically more inter-connected.Hypotheses are presented as to why this might obtain. This paperthen consistently measures and ranks access to jobs across 50 USmetropolitan areas. It uses that accessibility measure, along withnetwork structure variables and city size to help explainjourney-to-work time and auto mode share in those cities. A 1percent increase in accessibility reduces average metropolitancommute times by about 90 seconds each way. A 1 percent increase innetwork connectivity reduces commute time by 0.1 percent. A 1percent increase in accessibility results in a 0.0575 percent dropin auto mode share, while a 1 percent increase in treeness reducesauto mode share by 0.061 percent. Use of accessibility and networkstructure measures is important for planning and evaluating theperformance of network investments and land use changes.

Introduction

The average American spends about 4 years of their life inmotion. The amount depends on who they are, what they do, wherethey live, and how they choose to travel. Most Americans live inmetropolitan areas that enable people to engage in the activitiesthey care about efficiently, by bringing activities and peopleclose together for mutual economic production, trade, and commerce,social interaction, education, and defense. This proximity(accessibility) must provide advantages, otherwise cities would notexist. But not all cities are equally efficient. They vary in sizeand scope, they vary in the density and location of activities, andthey vary in their internal circulatory systems that enable peopleto move between places. As the world continues to urbanize, evensmall gains in intra-urban organizational efficiency will lead tolarge gains for humanity as a whole.

The structure of urban networks shapes the efficiency of thecities they serve. While in general there are many characteristicsthat scale with city size (metropolitan population (the terms“cities” and “metropolitan areas” are used synonymously in thispaper)), not all cities are created equal. They grew underdifferent technological, political, and legal regimes and operatein different physical environments, and as a consequence manifestdifferent physical forms.

A recent book The Triumph of the Cities has publicized what hadbeen heretofore an academic debate about the efficiency of cities,both in reduced infrastructure costs per capita, and in increasedproductivity. There is a modest literature examining the inputs tocities, how do network structure and urban services vary acrosscities. This has been examined for metro systems,

There is also a large and growing literature examining theoutputs from cities: how productive are cities, do they generateagglomeration economies, GDP, patents, and if so, how large istheir agglomeration benefit. The literature finds that largercities produce more GDP per capita, more patents, and moreinnovation, though there are of course debates aboutmagnitudes.

The travel behavior literature shows that larger cities havemore congestion and longer commutes, which implies inefficiency,even if those commutes are not increasing as fast as populationgrowth However if those longer commutes result in better jobs (abetter match of worker skills to employer needs), and thatcongestion is the result of non-work travel caused by expandedconsumption (goods that better fit desires) then those impliedinefficiencies of transportation are simply the product of choicesthat urban consumers make that is dominated by the benefits thatcreated them After all, people could choose to have shortercommutes or to consume fewer specialist goods and services, even ifthey lived in a large city.

This paper compares networks across cities, examiningrelationships between the macro (overall system performance) andaverages of micro measures (network structure) with the aim ofdiscovering key relationships that might be used to inform futurenetwork designs. It focuses on the questions of how network scaleand connectivity vary with city size. This connectivity that citiesenable, and of which networks determine efficiency, may drive theexpanded outputs of larger cities noted above. On the one hand,larger cities consume more area, which makes connectivity moredifficult, on the other, they increase population density,requiring more connected networks to serve. Whether connectivityincreases is in the end an empirical question.

The authors have previously examined how network structureaffects transportation performance (congestion, travel per person)This paper considers how accessibility, network structure, and citysize affects other measures of transportation performance:journey-to-work time and automobile mode share. It has beenhypothesized that network connectivity increases with city size asthe value of the increased access outweighs the costs of buildingthe additional links.

This research posits that network connectivity increases withmetropolitan population. Network connectivity is created by agents(land developers, governments) who build network links to connectplaces to the network All places must have at least one connectionto the network (i.e. there must be at minimum a tree connectingdeveloped land parcels). However, there may be some value tonetwork builders to create cross connections (circuits) so that thenetwork becomes more web-like. The advantage of the additionallinks is reducing travel costs compared to trees, the disadvantageis the additional construction costs. That value is determined bythe accessibility the additional connection creates.

In short, this model predicts that road networks will be moreconnected, less circuitous, and less tree-like the greater theaccessibility a new link creates. Accessibility by road increaseswith population (i.e. more people can be reached in a given timethe larger (denser) the city is) if density increases accessibilitymore than the resulting congestion and decline in average networkspeed decreases it. This will be true if there is excess roadcapacity, or if there are non-road modes of transportation (e.g.metro systems) which serve travelers when roads are congestedthereby limiting the amount of road congestion, and perhaps inother conditions. Thus larger cities have a greater incentive foragents to build cross-connecting links since those links will bemore valuable. These cross-connecting links in addition to reducingtravel distances compared with dendritic networks also may relievecongestion on the network. If private developers are buildinglinks, their requirement is that the embedded land value of theaccessibility created by the new link exceeds the cost of linkconstruction. Public agencies require that the public welfarecreated exceeds the cost of link construction. Previous researchsuggests publicly built networks have different developmentobjectives than privately built ones

This paper begins with a discussion of network characteristics.This is followed by an explanation of the data used. Summarystatistics of how network structure varies with city size ispresented. Next are scaling rules, which used in a systematic setof regression models to ascertain whether city scaling is linear,sublinear, or superlinear with population for a set of variables.This study calculates and compares accessibility across 50 USmetropolitan areas. It then uses accessibility, network structure,and city size to explain journey-to-work travel time and automobilemode share. The discussion identifies some implications for urbanplanning.

(b) Mode of transport is a term used to distinguish betweendifferent ways of transportation or transporting people or goods.The different modes of transport are air, water, and landtransport, which includes Rails or railways, road and off-roadtransport. Other modes also exist, including pipelines, cabletransport, and space transport. Human-powered transport andanimal-powered transport are sometimes regarded as their own mode,but never fall into the other categories. In general,transportation is used for moving of people, animals, and othergoods from one place to another. The means of transport, on theother hand, refers to the (motorized) vehicles necessary fortransport according to the chosen mode (car, airplane, ship, truckand rail). Each mode of transport has a fundamentally differenttechnological solution, and some require a separate environment.Each mode has its own infrastructure, vehicles, and operations

Motorized Transportation Device means any motorized device usedas a mode of transportation that includes: “Electric assistedbicycles”, “Mopeds”, “Motor Assisted scooters”, “motorcycles”,”motor-driven cycle”, and “personal motorized mobility device”

Urbanization: The transition from a rural to an urban society.Statistically, urbanization reflects an increasing proportion ofthe population living in settlements defined as urban, primarilythrough net rural to urban migration. The level of urbanization isthe percentage of the total population living in towns and citieswhile the rate of urbanization is the rate at which it grows.

rbanization has been one of the dominant trends of economic andsocial change of the 20th century, especially in the developingworld. Although cities played a significant role throughout humanhistory, it is not until the industrial revolution that a networkof large cities started to emerge in the most economically advancedparts of the world. Since 1950, the world’s urban population hasmore than doubled, to reach nearly 4.2 billion in 2018, about 55.2%of the global population. This transition is expected to go on wellinto the second half of the 21st century, a trend reflected in thegrowing size of cities and in the increasing proportion of theurbanized population. By 2050, 70% of the global population couldbe urbanized, representing 6.4 billion urban residents

Transportation systems influence travel behavior in at leastthree ways. First, streetnetworks influence mode choice and trip frequency through the waysin which triporigins and destinations are connected. Traditional street networkssuch as the gridpattern reduce trip distances and increase route choices, factorsbelieved to increasewalking and biking. Most contemporary suburban development, incontrast, minimizesthe degree of connectivity between trip origins and destinationsthrough the heavy use ofT intersections, cul-de-sacs, and reduced access to subdivisions.Second, streets can bedesigned to facilitate either automobile travel or nonmotorizedtravel. Streets that arewide, smooth, and straight encourage automobile travel at fastspeeds and discouragetravel by foot or bicycle. Conversely, streets that are narrow andirregular discourageautomobile travel at high speeds. Additionally, streets thatincorporate pedestrian andbicycle facilities (bike lanes, sidewalks, crosswalks, etc.) andthat are calmed ( i.e., streetsthat contain traffic-slowing obstacles and devices) are believed tofacilitate more walkingand bicycling. In the United States, street design has beendominated by the desire tofacilitate the smooth flow of automobile traffic, resulting indesign standards for streetsthat encourage driving and discourage walking and biking. Third,transportation systemscan increase walking and biking through separate, dedicated bicycleand pedestrianfacilities such as bike paths and walking trails. While thesesystems are increasinglypopular, it is generally not feasible to create dense networks ofthem in existing urbanareas.

Land development patterns influence travel behavior in at leastfour ways:

(a) Low density can increase distances between origins anddestinations. Itsrelationship to travel is intuitive ñ higher density levels reducetrip distances,theoretically increasing the incentive to walk and bike ñ and itsmeasurementis simple. For these reasons, density is perhaps the most-studiedlanddevelopment variable. Much of the research on density and travelhascentered on motorized travel modes.

(b) The relative mix of land uses in a given area also affectsthe distances betweentrip origins and destinations. The separation of uses intoresidential,commercial, and industrial zones increases travel distances, withsimilardampening effects on nonmotorized travel behavior. While itsrelationship totravel is easily conceptualized, land use mix is not as easy tomeasure asdensity. Still, a body of scholarly literature on the effects ofland use mix ontravel has emerged .

(c) Motorized travel is encouraged if trip destinations arewidely dispersed at theregional level. For example, if jobs are located far from housing,commutingby bicycle or on foot will be nearly impossible. While recognitioiniswidespread that regional development patterns such as the mixtureof jobsand housing are important, this particular measure hasdifficulties. Amongother problems is the limited availability of data accuratelyportraying thenumber and types of jobs and households in subregionallocations.

(d) Site design impacts travel patterns in much the same way asstreet design.Building design, orientation, and setback, along with otheraestheticconsiderations, will create environments that are either attractiveorunattractive for nonmotorized travel. Not been many empiricalstudies haveattempted to isolate the effects of site design on travelbehavior.