INTEGRATED TRANSIT Dillon Gogarty | Trevor Gunderson M. Arch Fall 2015 Professor: Darrin Griechen
INTEGRATED TRANSIT Dillon Gogarty | Trevor Gunderson M. Arch Fall 2015 Professor Darrin Griechen
Integrated Design Research Studios | Washington State University | School of Design + Construction
Abstract How can smart technology and smart citizens created a vibrant, healthy, and resilient Spokane? Washington State University School of Design and Construction is studying Smart Cities — data driven decision making, interactive environments, and the Internet of Things — as a collaborative Integrated Design Research Studio problem. Architecture, Interior Design, and Landscape Architecture will focus on Spokane to explore how the built environment can use Smart City ideas to facilitate resource management, build community, and promote health and well-being. A city is a living organism with unique individual metabolisms. Its metabolic requirements can be defined as all the materials and consumable commodities that inhabitants need at home, work, or play. Smart cities are places that take information technology and combine it with the architecture, infrastructure, and material objects to solve and address problems in real-time. The key to making a smarter city is collecting and analyzing big data that allows a city to predict and adapt to different problems, in this case transportation. Spokane Washington has a problem, the car hinders the built environment. Wide streets make walking and biking difficult, the current downtown surface conditions and parking garages disrupt the flow and connectivity, and the public transportation system is poorly integrated. Our goal is to rearrange the current hierarchy with a transportation network that reduces wait time to less than one minute through the use of collected data and real time adaptive analytics.
Table of Contents 01 Introduction 02 Precedents 03 Spokane’s Surface Conditions 04 Spokane’s Spatial Conditions 05 Catalytic Connection 06 Smart Stations 07 Smart Phone App 08 Gondola Integration 09 Spokane Connected 10 Future Development
Our integrated transportation network aims to combine existing infrastructure with technological infrastructure utilizing big data in real time to enhance efficiency. Thus, resulting in a smart system that predicts changes in future circumstances.
Chapter 01 Introduction
Where are Cities Going
01.1 The world just passed the threshold where there are more people living in urban areas than rural. By the year 2050 the urban population is projected to double and cities need to begin to prepare for a huge increase of people. In order for future cities to be successful, they will need to invest in efficient and diverse transportation to give people the options to move freely throughout the city. Jaime Lerner, the mayor of Curitiba, Brazil, states that there are three main issues facing cities and citizens as they interact in the world: sustainability, tolerance, and mobility. Transportation is a key element in an efficient city: highways, train lines, airports, and bike paths determine the form and character of our communities. Our focus, will be on improving the mobility and transportation of the city of Spokane.
What is a City
01.2 Traditionally, old planning used to be about intuition. It was based on very old and unresponsive datasets to plan urban transportation networks. The time scale between these datasets, to inform these decisions were months to years, making them unresponsive.
What is a Smar t City
01.3 Now we have the smart city. Smart cities are places that take information technology and combine it with the architecture, infrastructure, and material objects to solve and address problems in real-time. Throughout the city, sensors and data collectors are placed to be analyzed. These smart city systems feed data into software that has the capacity to see the bigger picture, take action, and adapt. But rather than being reactive, future infrastructure designs will need to be anticipatory and proactive to be truly sustainable. Big Data is the collection of massive amounts of information, whether structured or unstructured. Big data and machine learning work in three phases: collection, analyze and predict, and adapt. These steps have been disconnected until now, because of the growth in technology.
COLLECT
ANALYZE & PREDICT
ADAPT
01.4 Think about this like how the human brain learns from life experiences vs. from explicit instructions. The more data, the more effective the learning, which is why machine learning and big data are intricately tied together. Predictive analytics is using machine learning to predict future outcomes, or to infer unknown data points from known ones. We are saying, with this technology it can be more responsive because we can get real-time data about where people are at, where they are going, and what’s happening on the network. This allows us to be more effective in the use of the traditional infrastructure.
E v o l u t i o n o f G . P. S .
01.5 For example, when GPS first came out, it was dumb. It could tell us the shortest route from A to B,but it didn’t have any data about why you would not choose the shortest route. It didn’t tell you that maybe going further and traveling a longer distance on the freeway, the actual longer route in terms of time is shorter. Once GPS became informed the efficiency increased. Then GPS started to crowd source live traffic data and accidents informing the system to reroute around the problem. Eventually, after it analyzed the datasets, it became smarter and was able to predict when rush hour or other events were taking place to find you the quickest route to your destination. We are going to be adding a piece of infrastructure, which might be more traditional in reconfiguring this. However, this is coincided with a whole suite. A smart suite of technological infrastructure and a mobile application that routes and makes the utilization of this new infrastructure plus what’s existing, much smarter, efficient, and effective.
Chapter 02 Precedents
Precedent Studies
02.1 Jamie Lerner went on to state that “Public transportation can’t just be an option, it has to be the best option.“ Now we are going to look at a few cities that are doing public transportation right.
Portland, Oregon
02.2 Beginning with Portland Oregon, we see the use of High priority transit corridors with integrated streets for their light rail, streetcar, and bus network.
Medellin, Colombia
02.3 Medellin Colombia using a series of Escalators and gondolas to scale the steep terrain, connecting the lower-income neighborhoods to the downtown.
Curitiba, Brazil
02.4 Curitiba Brazil taking busing to the next level with dedicated lanes for the Bus Rapid Transit, and efficient, subway style, load and unloading systems to allow the buses to run as fast as possible.
Singapore
02.5 And finally Singapore who is striving for the title of “The Smartest City.� With all in one transit stations, and an all city pass for ease of access to public transportation as well as for collecting data.
Chapter 03 Spokane’s Surface Conditions
11 12 10
1
5 6
2
13
3
7 4 14
8
9
03.1 Currently, Spokane has a problem. Looking at the surface conditions of Spokane, the car dominates the built environment: its wide streets, some up to 9 lanes across, make walking and biking difficult, the downtown’s surface connectivity is disrupted by parking lots and main arterials, and the public transportation system is poorly integrated.
CAR
BUS
BIKE
WALK
03.2 Here is Spokane’s current hierarchy. On top, the car is king. Transport is mostly independent, and the majority of people personally drive from home to work. Then the bus network trickles down to biking and walking.
CAR
BIKE
BIKE BUS
WALK
WORK
BUS WALK
03.3 However, this system is flawed. If we take an example of a user going from home to work, the car’s experience is filled with obstacles: stop lights, accidents, and other drivers. The bus system is dependent on this, making transfers unreliable and unsyncable. Biking and walking have low priority and also face obstacles to their destination.
M od e s
Bu s
Co m m u te r Ra i l
E l e ctr i c Trol l e y
L i g ht Ra i l
Stre e t Ca r
03.4 Spokane recognizes this problem and has already considered transit options to improve the system. The city has already began to look at options to try and relieve Spokane from its transit options. The five options, bus, trolley, light rail, and streetcar, have all been considered heavily and are very viable options for Spokane moving forward. But in order to see which option or options are the best to solve traffic problems, we will put them through a series of comparisons to see which performs the best across the board.
Modes
Bu s
Co m m u te r Ra i l
E l e ctr i c Trol l e y
L i g ht Ra i l
Stre e t Ca r
Weathe r Res is t an ce
03.5 Beginning with weather resistance we can see that the light rail, commuter rail, and streetcar perform best. Winter is the time where traffic has its most issues when it comes to weather shutting down public transportation, and Spokane in particular has pretty severe winters, with a lot of snow and ice. When these weather conditions happen the bus system takes a huge hit when it comes to frequency because buses have a hard time navigating in the snow and ice. The trolley system also cannot perform well in winter weather conditions because of the slow speed and difficulty traveling up and down terrain.
M od e s
Bu s
Co m m u te r Ra i l
E l e ctr i c Trol l e y
L i g ht Ra i l
Stre e t Ca r
Tra v e r s i n g Te r rain
03.6 Spokane has some difficult terrain that public transportation needs to be able to go up and down in a timely fashion. The bus can traverse this terrain with the most ease, while all the fixed rail systems have a difficult time because of what they are meant to accomplish. All the fixed rail systems listed have a hard time traversing terrain because of what they are meant to accomplish. Light rail and streetcars are meant to cover downtown areas with relatively flat terrains, the motors don’t have the power to move them up and down hills, and the long cars makes it very difficult for them to go up and down.
M od e s
Bu s
Co m m u te r Ra i l
E l e ctr i c Trol l e y
L i g ht Ra i l
Stre e t Ca r
F l ex i b l e Ro u t in g
03.7 Flexible routing is something that needs to be addressed with cites because the dynamics are always changing and people may need to move to different places as the city evolves. A bus network is the most easily changed because of the flexibility of buses to change routes. All the fixed rail systems are just that, they are fixed in their routes and cannot be changed with any ease. A city a perform future projections about where people may need to go to. Portland is having issues with ridership being low because some of the light rail lines don’t go anywhere and people don’t have and reason to take them.
Modes
Bu s
Fre q u e n c y
8-3 0 M i n u t es
Co m m u te r Ra i l
30 M i n u tes
E l e ctr i c Trol l e y
15 M i n u tes
L i g ht Ra i l
30 M i n u tes
Stre e t Ca r
15 M i n u tes
03.8 Capacity is always something that a city looks at, the capacity can inform how much money the system can make, and the amount of people a system can handle. The light rail system is the best at moving people per car. Most light rail trains are 2 cars in total, meaning they can hold up to 320 people per train. This number is a little misleading because there is some data in the total people per hour. A bus system can move more people per hour because of frequency and number of buses on a route. But the buses run into problems when it comes to on time deliveries because of the factors that come with driving on the roads.
Modes
Bu s
Ca p a c i ty
50 Pe op l e pe r B u s
Co m m u te r Ra i l
10 0 Pe op l e pe r Car
E l e ctr i c Trol l e y
30 Pe op l e
L i g ht Ra i l
Stre e t Ca r
16 0 p e r Car
50 p e r Ca r
03.9 Capacity is always something that a city looks at, the capacity can inform how much money the system can make, and the amount of people a system can handle. The light rail system is the best at moving people per car. Most light rail trains are 2 cars in total, meaning they can hold up to 320 people per train. This number is a little misleading because there is some data in the total people per hour. A bus system can move more people per hour because of frequency and number of buses on a route. But the buses run into problems when it comes to on time deliveries because of the factors that come with driving on the roads.
Modes
Av e ra g e Spe ed
Bu s
12 m p h
Co m m u te r Ra i l
30 m p h
E l e ctr i c Trol l e y
7 mph
L i g ht Ra i l
Stre e t Ca r
15 m p h
8 mph
03.10 Average speed is a good way to judge how quickly people can move from place to place. The commuter rail has the fastest average, this is only because it travels unimposed over long distances. The streetcar and light rail move at fairly fast speeds when navigating through a city, as well as the bus.
Modes
Em i s s i on Type
Bu s
Hy d r i d D i es e l
Co m m u te r Ra i l
Diesel
E l e ctr i c Trol l e y
El e c tr i c
L i g ht Ra i l
El e c tr i c
Stre e t Ca r
El e c tr i c
03.11 Emissions are a huge factor in city transportation because these systems are constantly running right next to people and homes, and certain cities already have problems with downtown pollution. IBM has ran some calculations that says that over half of the pollution in most cities comes from transportation pollution. That being said, the trolley, light rail, and streetcar all run on electric, while the bus is a hybrid diesel.
Modes
Cos t p e r Mile
Bu s
4-4 0 m i l l i on
Co m m u te r Ra i l
3-2 5 m i l l i on
E l e ctr i c Trol l e y
2-1 2 m i l l i on
L i g ht Ra i l
20 -6 0 m i l l io n
Stre e t Ca r
10 -2 5 m i l l io n
03.12 Cost per mile is a huge factor when building public transportation. The bus, commuter rail and trolley system can all be built for around 2-40 million dollars per mile. This is pretty cost effective for places that don not want to spend a billion dollars on public transportation. If a city chooses to build a light rail system then there could be a range of prices. Portland is the best example to look at rail systems. Some of their older systems cost around 60 million dollars a mile, but Portland just opened up two new lines that cost a staggering 250 million dollars per line.
M od e s
Bu s
S e r v i c e Type
Loc al Ur ban, Urban, and Inte rurban
Co m m u te r Ra i l
In ter u r ban
E l e ctr i c Trol l e y
Loc al Ur ban
L i g ht Ra i l
Stre e t Ca r
In ter u r ban
Loc al Ur ban
03.13 Finally the service type shows the diversity of each system. The bus is the most diverse when it comes to the areas of a city it can serve, serving all three urban, local urban, and interurban. The fixed rail systems have a difficult time serving a lot of urban types because of factors like, noise in residential neighborhoods, width of lanes needed, right of way issues on roads, safety, and terrain issues. The rail systems are better at serving downtown and long distance neighborhood stops. We can see that there really is no clear option for what suits Spokane’s needs. In Brazil Jaime Lerner proposed an ambitious goal: The most ideal transportation is where users shouldn’t have to wait more than one minute. This “most ideal form of transportation” can’t be achieved with the previously stated transport options, forcing us to explore outside the box and look at Spokane from another angle.
Chapter 04 Spokane’s Spatial Conditions
04.1 Previously, we analyzed Spokane as a city looking down in plan, now we are viewing the city in section. The surface condition of Spokane is busy. Car’s dominate the roads, forcing the buses to run inefficiently. There is also the terrain of the South Hill that makes roads in the winter dangerous. Essentially, the current surface is too messy and complex for expansion.
04.2 However, if we look at Spokane spatially, we have all this space above the chaotic surface. Giving us the opportunity to move the transportation network up.
04.3 When implemented, an urban gondola system streamlines transport by lifting off the chaotic surface, providing the users to have a consistent and efficient means of travel through the city. As we lift the mass movement of people off the ground, we free the surface for the buses to run more efficiently, and the people and bicyclists to ride safer. The gondola has few obstacles, it can easily climb terrain and be used as the consistent backbone of the cities transportation network.
GONDOLA + SMART INFRASTRUCTURE + APP
04.4 We are proposing an urban gondola system as the consistent backbone for our transit network. By itself, this is traditional old school infrastructure. But, with smart technological infrastructure and a mobile app we are able to make everything more efficient. First, we are going to talk about the gondola.
M od e s
Gondola
Bu s
Co m m u te r Ra i l
E l e ctr i c Trol l e y
L i g ht Ra i l
Stre e t Ca r
04.5 Now we are going to revisit the five transportation options, bus, light rail, streetcar, trolley, and commuter rail, and add in the gondola systems and see how well it performs in comparison to the previous five that were mentioned.
M od e s
Gondola
Bu s
Co m m u te r Ra i l
E l e ctr i c Trol l e y
L i g ht Ra i l
Stre e t Ca r
Weathe r Res is t an ce
04.6 Beginning again with weather resistance, we can see that the gondola performs the best in heavy winter conditions. This is because gondolas were originally intended to perform well in mountain weather at ski slopes. Urban gondolas are just as hardy as the ski gondolas, the only thing that can shut down an urban gondola system are winds that are up to 70 mph.
M od e s
Gondola
Bu s
Co m m u te r Ra i l
E l e ctr i c Trol l e y
L i g ht Ra i l
Stre e t Ca r
Tra v e r s i n g Te r rain
04.7 The gondola also performs well when it comes to traversing terrain. Gondolas already traverse some to the most difficult terrain, mountain slopes. The gondola in Whistler, BC, traverse a valley, unsupported, that is almost 2 miles across. There is no city in the world that needs this kind of system, but it shows just how diverse a gondola is when it comes to tackling any terrain that a city has.
M od e s
Gondola
Bu s
Co m m u te r Ra i l
E l e ctr i c Trol l e y
L i g ht Ra i l
Stre e t Ca r
F l ex i b l e Ro u t in g
04.8 Flexible routing is still performed the best by the bus. But the gondola performs the better than the fixed rail systems in altering its route. This is due to the speed of construction. The fixed rail systems take a lot of effort to construct because of the road closures, altering how cars interact with the rail system, and all the new infrastructure that goes into a rail project. A rail system can take 5 plus years to construct a line that is a few miles long. The gondola system that is in Colombia was constructed in 2 years and it cover 6 miles. This allows for the system to evolve and adapt with a city, as a city grows and needs more transportation in certain places, the gondola is right behind.
M od e s
Gondola
Bu s
Fre q u e n c y
1 M i n u te
8-3 0 M i n u t es
Co m m u te r Ra i l
30 M i n u tes
E l e ctr i c Trol l e y
15 M i n u tes
L i g ht Ra i l
30 M i n u tes
Stre e t Ca r
15 M i n u tes
04.9 Frequency is a huge factor because people need to be able to count on transportation always being there when it says it will. The gondola has no traffic issues to deal with and always comes on time. Depending on the type of gondola that is used, they can range from every few seconds, to every few minutes.
M od e s
Gondola
Bu s
Ca p a c i ty
4-5 0 p e r Car
50 p e r Bu s
Co m m u te r Ra i l
10 0 p e r Car
E l e ctr i c Trol l e y
30 p e r Ca r
L i g ht Ra i l
Stre e t Ca r
16 0 p e r Car
50 p e r Ca r
04.10 Capacity per car is still bested by the light rail at 160 per car, where the gondola is only 4-50 people per car, depending on the style that is chosen. But if we revisit the system as a whole, the gondola performs at a very high level. The system in Colombia that was mentioned earlier has the capacity to carry up to 9,000 people per hour. This number is something that cannot be matched by any of the systems that were mentioned because of the frequency that they run. For a bus to match this capacity there would need to be an express route, with a total route time of 24 minutes with a minimum of 30 buses running all the time to be close to the total capacity.
M od e s
Av e ra g e Spe ed
Gondola
12 m p h
Bu s
12 m p h
Co m m u te r Ra i l
30 m p h
E l e ctr i c Trol l e y
7 mph
L i g ht Ra i l
Stre e t Ca r
15 m p h
8 mph
04.11 The average speed is still the best by the commuter rail, but when compared with the other systems, the gondola performs very well. The other modes may have a higher top speed, but there are factors that affect the overall average speed, like time at the station, loading time, traffic issues, traffic issues, and many more. The gondola has none of those and is always moving no matter the situation.
M od e s
Gondola
Bu s
Em i s s i on Type
El e c tr i c
Hy b r i d D i es e l
Co m m u te r Ra i l
Diesel
E l e ctr i c Trol l e y
El e c tr i c
L i g ht Ra i l
El e c tr i c
Stre e t Ca r
El e c tr i c
04.12 The gondola is also electric, meaning that it has a very low carbon footprint and that emissions in the city will be kept to a minimum. There is one issue with pollution, and that is the noise. The system is not very loud, but there is a low hum if you are near a support. The sound is not very loud but it is always happening, it is less noisy than a streetcar or light rail, the only difference is that the gondola noise is constant.
M od e s
Cos t p e r Mile
Gondola
3-1 2 m i l l i on
Bu s
4-4 0 m i l l i on
Co m m u te r Ra i l
3-2 5 m i l l i on
E l e ctr i c Trol l e y
2-1 2 m i l l i on
L i g ht Ra i l
20 -6 0 m i l l io n
Stre e t Ca r
10 -2 5 m i l l io n
04.13 The gondola is also very affordable in dollars per mile. There are some cases where the line can be as little as 3 million dollars per mile. This is a huge factor because in the end these are public dollars and a city has to be aware of how the are using them. Streetcar and light rail systems may be nice, but having multiple billion dollar projects can be daunting for any city.
M od e s
S e r v i c e Type
Gondola
Loc a l U r b a n , U r b an , an d I n t er u r b an
Bu s
Loc a l U r b a n , U r b an , an d I n t er u r b an
Co m m u te r Ra i l
I n te r u r b a n
E l e ctr i c Trol l e y
Loc a l U r b a n
L i g ht Ra i l
Stre e t Ca r
I n te r u r b a n an d U r b an
Loc a l U r b a n
04.14 Just like the bus system, the gondola is also very diverse in the urban types that it can serve. the very low footprint on the ground and minimum stations mean that having them in neighborhoods is not a big problem, especially because roads do not need to be laid out, and there are no huge infrastructure projects that need to happen.
GONDOLA
BUS
BIKE
WALK
CAR
04.15 Now, we are going to redefine Spokane’s hierarchy. We replace the car with the urban gondola as the backbone for the integration. Then the bus, bike, and walk can be intertwined to create a reliable system. Lastly, the car is given the least priority at the bottom of the hierarchy.
BUS
BIKE
BIKE BUS WALK
CAR
GONDOLA
WORK
BUS WALK
04.16 So now, we’ll go through the same scenario of a person traveling from home to work. You could still take your car, but you will continue to face the same obstacles and interruptions. If you take the integrated network or allow the mobile app to reserve and find you the best route, a scenario you might take would be: to walk to the bus station, get on a gondola and move up across the city, get off at the nearest station, rent a city-bike or just walk to the rest of the way.
GONDOLA + SMART INFRASTRUCTURE + APP
04.17 Our goal is an urban gondola system combined with smart technological infrastructure and a mobile application to make everything more efficient. Now, we are going to talk about the smart infrastructure aspect.
COLLECT
ANALYZE & PREDICT
ADAPT
04.18 Big Data can tell the vivid, hyper-detailed story of just about anything. You will need sensors or a way to collect this data in the system. We can get real-time data about where people are at, where they are going, and what’s happening on the network through our collectors.
Chapter 05 Catalytic Connection
05.1 If we now look at a generic gondola line we can see how the integration of the system will work. Each dot on the line represents a station.
05.2 First we apply a Ÿ mile radius for walkability. Doubling that radius to a ½ mile for bikeability. Followed by a bus rapid transit route running perpendicular to the gondola line. And then a walkability and bikeability radius are applied to the bus routes showing how far the network can expand.
COLLECT
ANALYZE & PREDICT
ADAPT
05.3 Next is to analyze and predict the data collected. Predictive, proactive, and actionable data allows travel and transportation companies to drive optimal efficiency and lower costs while enhancing the end-to-end traveler experience. Analytics is the digital pathway to maximize profitability and performance.
05.4 If we look at the same gondola line we can also predict the development that will happen in the surrounding area. First high density regions will form closest to the stations directly complementing the walkability. Then medium density would expand around the bike network. And finally, low density being served by the bus network.
1
3
2
4
05.5 Looking at Spokane as a whole, we needed to chose an area that would serve as a catalyst for the proposed smart system. We began by looking at the new development of the University District (1). Knowing that WSU Spokane is becoming the next big medical school, it made sense to provide a direct connection to Spokane’s medical district, moving students back and forth (2). Having these two districts be along the edge of the downtown it made sense to provide a connection (3). And finally we wanted to use the gondolas ability to move up and down steep terrain by connecting the residence on the South Hill to the rest of the network (4). Connected, these districts will serve as the catalyst for the growth of Spokane’s smart transit system.
COLLECT
ANALYZE & PREDICT
ADAPT
05.6 The last stage in using Big Data is anticipating the system to adapt. What’s happening today may influence what happens tomorrow. A lot of iteration needs to occur on a continual basis for the system to get smart. For the machine to “learn” it must explore the data, visualize it, build a model, ask a question, an answer comes back, bring in other data, and repeat the process. IBM researchers predict that in five years, cities will adapt to growing populations by using mobile apps, sensors, crowd-sourcing, and data analytics to better respond to citizens’ needs.
Chapter 06 Smart Stations
06.1 Each of our stations have the capability to collect all these types of data for future use by the city. Each station is equipped with city ride share bikes and most stations have integrated bus rapid transit. We are going to look at a few generic examples of how each station would serve an urban typology, beginning with the residential.
06.2 Mid-rise Economic
06.3 Bus Metro Station
06.4 Park and Go
06.5 Downtown, high density
GONDOLA + SMART INFRASTRUCTURE + APP
06.6 We are implementing an urban gondola system combined with smart technological infrastructure and a mobile application to make everything much more efficient. Among these kind of integration effects we begin to think about how walking, biking, and the bus lines all start to work together. This is paramount, in the sense of being more effectively done by adding our app. Now, we are going to talk about our mobile App. Smart Transit Anytime.
Chapter 07 Smart Phone App
07.1 Right now, there are all these transportation apps, but most are passive. You search your destination and see where it goes. With STA, you lock it in. You say this is my trip and you send out the information. This starts to queue a priority to make sure that your mode of transportation is there for you at that time, and the system builds to that capacity. If everyone starts to use this, then it becomes a much more responsive piece. Essentially, you are saying “I am here and I am going there, make sure I have a seat� and this makes a huge difference.
07.2 So now, let’s go through the same scenario of someone going from home to work. First in the app, you type your destination and lock in your trip. Then proceed to your first mode of transportation, beginning your trip.
07.3 The app tracks your trips progress giving you an accurate ETA to each of your modes of transportation and destination.
07.4 Your mobile transportation ticket will give you access to all modes of transportation and has the ability to rent you a city bike through personal QR code.
07.5 Finally when you have arrived at your destination it will provide a trip overview of your recorded miles giving incentives for free trips after mile goals are achieved.
Chapter 08 Gondola Integration
08.1 Now that the gondola, the smart infrastructure, and the app have been defined, it is time to define the gondola line. The line begins at 28th and Grand and moves north on Grand to Manito Park where it splits in two directions. The west portion goes to Shriners Children’s Hospital, while the east portion goes to Providence Hospital. After Providence Hospital the line splits again heading north on Division street and east on Sprague where the line deviates and heads north to Hamilton.
08.2 Now looking at the finished line we are going to revisit how walking, biking, and the bus network affect the gondola line. The first step is to apply that same Ÿ mile walking radius around each station. Second we double that initial walking radius and apply a ½ mile biking radius. Then the bus rapid transit network is applied to each station, running east to west. And that bus network has its own network of biking and walking showing how far someone can move around the city without ever needing a car.
08.3 Looking at the same line we can also anticipate the kind of density that will appear around each station. First we apply a high density radius that mimics the same radius as the walking radius. Then follows medium density that follows the biking radius. And finally the low density areas which are served by the bus network.
Chapter 09 Spokane Connected
GONDOLA + SMART INFRASTRUCTURE + APP = SMART CITY
09.1 When an urban gondola line, smart technological infrastructure, and a mobile application are combined it gives us a smart integrated transportation system.
N Hamilton + Desment
E Sprague + Hatch
N Division + MLK
S Division + Grand
Washington + 6th
17th +
Grand
28th + Grand
S Division + Grand
E Sprague + Hatch
Chapter 10 Future Development
010.1 Next, if we take a step back and view Spokane as a whole we can explore the future expansion possibilities. We begin by placing our catalytic connection, the University District line. Followed by the Liberty Lake to Spokane airport addition. Next is to expand the University District line further north on Division. Then to close the South hill loop by connecting Spokane Community college to the other universities and connecting Manito park to the rest of the east South Hill. After the south hill loop there is the north Monroe extension. Followed by the north Crestline expansion. And then the VA hospital expansion. Lastly, there is the west south hill loop that connects the rest of the South Hill with Manito park and the downtown.
University District
Liberty Lake to Airport
North Division
South Hill Loop
North Monroe
North Crestline
VA Hospital
West South Hill
INTEGRATED TRANSIT
Finally, the implementation of an urban gondola with smart technology and a mobile application will act as a catalyst for growth in Spokane, transforming it into a city that is flexible, adaptive, and most importantly integrated.
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