Question

Describe the following developments :

a. The introduction of Metro and their efforts on the sizes and densities of cities.

b. The introduction of various motorised transportation modes and its effects on residential densities, physical size and forms of cities.

Transportation Engineering
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Answer 1

Metro rails are rail-based, mass rapid transit systems that operate on an exclusive right-of-way, which is
separated from all modes of transport in an urban area. Most often, the right-of-way is either underground
or elevated above street level. These systems generally operate at an average speed of 20–35 km/h,
and are characterized by their high capacity (50,000–75,000 passengers per hour, per direction) and high
frequency of operation. The capital cost of construction is between 20–30 times that of the Bus Rapid
Transit system, depending on whether the metro systems are underground or elevated (Mohan, 2008).
There has been a growing interest among policymakers about the relevance of rail-based systems in
India, to address the mobility needs of the expanding population in the cities. While evaluating different
mass transit options for Indian cities, metro systems are often given preference due to the belief that
road-based bus systems cannot cater to capacity requirements as much as metro systems. In addition
to 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 potential users of the system.
Promoters of metro systems often claim that one of the benefits of the metro is reduced congestion, due
to the users’ shift from road-based motorized modes to metro systems. This mode shift is then claimed
to result in reduced air pollution and road accidents. Due to the induced demand,
the available road space fills up with motorized vehicles, and the modal shift to metro does not result in
the reduction of congestion or air pollution. The concentration is approximately
three times higher than safe levels. Similarly, the eight-hourly maximum current level of carbon monoxide
(CO) is touching 6,000 microgram per cubic metre – way above the safe level of 2,000 microgram per
cubic metre – though the annual levels have registered a drop. Overall, these figures illustrate that the
operation of the Delhi Metro has not led to a reduction in pollution levels in the city (Randhawa, 2012).
Due to the limited coverage of the city by rail-based systems1
, as opposed to road-based bus systems, a
metro commuter spends significant time during access (from origin to metro station) and egress (metro
station to destination). As a result of this additional time, even though the average main-haul (in-vehicle)
speed of the metro is above 30 km/h, the average door-to-door travel speed gets reduced for a short trip
on the metro system – as compared to a road-based system. Hence, metro systems have been found to
be most favourable, in terms of saving time, if the trips are 10 km or longer. Due to mixed land-use and the
polycentric nature of Indian cities with multiple central business districts (CBDs), however, the majority
of 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 that operate on an exclusive right-of-way, which is
separated from all modes of transport in an urban area. Most often, the right-of-way is either underground
or elevated above street level. These systems generally operate at an average speed of 20–35 km/h,
and are characterized by their high capacity (50,000–75,000 passengers per hour, per direction) and high
frequency of operation. The capital cost of construction is between 20–30 times that of the Bus Rapid
Transit system, depending on whether the metro systems are underground or elevated (Mohan, 2008).
There has been a growing interest among policymakers about the relevance of rail-based systems in
India, to address the mobility needs of the expanding population in the cities. While evaluating different
mass transit options for Indian cities, metro systems are often given preference due to the belief that
road-based bus systems cannot cater to capacity requirements as much as metro systems. In addition
to 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 potential users of the system.
Promoters of metro systems often claim that one of the benefits of the metro is reduced congestion, due
to the users’ shift from road-based motorized modes to metro systems. This mode shift is then claimed
to result in reduced air pollution and road accidents. However, the experience of metro rails in low and
middle income counties around the world shows otherwise (Mohan, 2008). Due to the induced demand,
the available road space fills up with motorized vehicles, and the modal shift to metro does not result in
the reduction of congestion or air pollution.
Due to the limited coverage of the city by rail-based systems1
, as opposed to road-based bus systems, a
metro commuter spends significant time during access (from origin to metro station) and egress (metro
station to destination). As a result of this additional time, even though the average main-haul (in-vehicle)
speed of the metro is above 30 km/h, the average door-to-door travel speed gets reduced for a short trip
on the metro system – as compared to a road-based system. Hence, metro systems have been found to
be most favourable, in terms of saving time, if the trips are 10 km or longer. Due to mixed land-use and the
polycentric nature of Indian cities with multiple central business districts (CBDs), however, the majority
of trips remain below 5 km (Jain and Tiwari, 2011).

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

Introduction

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

The structure of urban networks shapes the efficiency of the cities they serve. While in general there are many characteristics that scale with city size (metropolitan population (the terms “cities” and “metropolitan areas” are used synonymously in this paper)), not all cities are created equal. They grew under different technological, political, and legal regimes and operate in different physical environments, and as a consequence manifest different physical forms.

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

There is also a large and growing literature examining the outputs from cities: how productive are cities, do they generate agglomeration economies, GDP, patents, and if so, how large is their agglomeration benefit. The literature finds that larger cities produce more GDP per capita, more patents, and more innovation, though there are of course debates about magnitudes.

The travel behavior literature shows that larger cities have more congestion and longer commutes, which implies inefficiency, even if those commutes are not increasing as fast as population growth However if those longer commutes result in better jobs (a better match of worker skills to employer needs), and that congestion is the result of non-work travel caused by expanded consumption (goods that better fit desires) then those implied inefficiencies of transportation are simply the product of choices that urban consumers make that is dominated by the benefits that created them After all, people could choose to have shorter commutes or to consume fewer specialist goods and services, even if they lived in a large city.

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

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

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

In short, this model predicts that road networks will be more connected, less circuitous, and less tree-like the greater the accessibility a new link creates. Accessibility by road increases with population (i.e. more people can be reached in a given time the larger (denser) the city is) if density increases accessibility more than the resulting congestion and decline in average network speed decreases it. This will be true if there is excess road capacity, or if there are non-road modes of transportation (e.g. metro systems) which serve travelers when roads are congested thereby limiting the amount of road congestion, and perhaps in other conditions. Thus larger cities have a greater incentive for agents to build cross-connecting links since those links will be more valuable. These cross-connecting links in addition to reducing travel distances compared with dendritic networks also may relieve congestion on the network. If private developers are building links, their requirement is that the embedded land value of the accessibility created by the new link exceeds the cost of link construction. Public agencies require that the public welfare created exceeds the cost of link construction. Previous research suggests publicly built networks have different development objectives than privately built ones

This paper begins with a discussion of network characteristics. This is followed by an explanation of the data used. Summary statistics of how network structure varies with city size is presented. Next are scaling rules, which used in a systematic set of 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 US metropolitan areas. It then uses accessibility, network structure, and city size to explain journey-to-work travel time and automobile mode share. The discussion identifies some implications for urban planning.

(b) Mode of transport is a term used to distinguish between different ways of transportation or transporting people or goods. The different modes of transport are air, water, and land transport, which includes Rails or railways, road and off-road transport. Other modes also exist, including pipelines, cable transport, and space transport. Human-powered transport and animal-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 other goods from one place to another. The means of transport, on the other hand, refers to the (motorized) vehicles necessary for transport according to the chosen mode (car, airplane, ship, truck and rail). Each mode of transport has a fundamentally different technological solution, and some require a separate environment. Each mode has its own infrastructure, vehicles, and operations

Motorized Transportation Device means any motorized device used as a mode of transportation that includes: "Electric assisted bicycles", "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 of the population living in settlements defined as urban, primarily through net rural to urban migration. The level of urbanization is the percentage of the total population living in towns and cities while the rate of urbanization is the rate at which it grows.

rbanization has been one of the dominant trends of economic and social change of the 20th century, especially in the developing world. Although cities played a significant role throughout human history, it is not until the industrial revolution that a network of large cities started to emerge in the most economically advanced parts of the world. Since 1950, the world’s urban population has more than doubled, to reach nearly 4.2 billion in 2018, about 55.2% of the global population. This transition is expected to go on well into the second half of the 21st century, a trend reflected in the growing size of cities and in the increasing proportion of the urbanized population. By 2050, 70% of the global population could be urbanized, representing 6.4 billion urban residents

Transportation systems influence travel behavior in at least three ways. First, street
networks influence mode choice and trip frequency through the ways in which trip
origins and destinations are connected. Traditional street networks such as the grid
pattern reduce trip distances and increase route choices, factors believed to increase
walking and biking. Most contemporary suburban development, in contrast, minimizes
the degree of connectivity between trip origins and destinations through the heavy use of
T intersections, cul-de-sacs, and reduced access to subdivisions. Second, streets can be
designed to facilitate either automobile travel or nonmotorized travel. Streets that are
wide, smooth, and straight encourage automobile travel at fast speeds and discourage
travel by foot or bicycle. Conversely, streets that are narrow and irregular discourage
automobile travel at high speeds. Additionally, streets that incorporate pedestrian and
bicycle facilities (bike lanes, sidewalks, crosswalks, etc.) and that are calmed ( i.e., streets
that contain traffic-slowing obstacles and devices) are believed to facilitate more walking
and bicycling. In the United States, street design has been dominated by the desire to
facilitate the smooth flow of automobile traffic, resulting in design standards for streets
that encourage driving and discourage walking and biking. Third, transportation systems
can increase walking and biking through separate, dedicated bicycle and pedestrian
facilities such as bike paths and walking trails. While these systems are increasingly
popular, it is generally not feasible to create dense networks of them in existing urban
areas.

Land development patterns influence travel behavior in at least four ways:

(a) Low density can increase distances between origins and destinations. Its
relationship to travel is intuitive ñ higher density levels reduce trip distances,
theoretically increasing the incentive to walk and bike ñ and its measurement
is simple. For these reasons, density is perhaps the most-studied land
development variable. Much of the research on density and travel has
centered on motorized travel modes.

(b) The relative mix of land uses in a given area also affects the distances between
trip origins and destinations. The separation of uses into residential,
commercial, and industrial zones increases travel distances, with similar
dampening effects on nonmotorized travel behavior. While its relationship to
travel is easily conceptualized, land use mix is not as easy to measure as
density. Still, a body of scholarly literature on the effects of land use mix on
travel has emerged .

(c) Motorized travel is encouraged if trip destinations are widely dispersed at the
regional level. For example, if jobs are located far from housing, commuting
by bicycle or on foot will be nearly impossible. While recognitioin is
widespread that regional development patterns such as the mixture of jobs
and housing are important, this particular measure has difficulties. Among
other problems is the limited availability of data accurately portraying the
number and types of jobs and households in subregional locations.

(d) Site design impacts travel patterns in much the same way as street design.
Building design, orientation, and setback, along with other aesthetic
considerations, will create environments that are either attractive or
unattractive for nonmotorized travel. Not been many empirical studies have
attempted to isolate the effects of site design on travel behavior.