Loading

Module 1: Multimodal Transportation Systems

Notes
Study Reminders
Support
Text Version

Multimodal Level of Service for Non-Automobile Modes

Set your study reminders

We will email you at these times to remind you to study.
  • Monday

    -

    7am

    +

    Tuesday

    -

    7am

    +

    Wednesday

    -

    7am

    +

    Thursday

    -

    7am

    +

    Friday

    -

    7am

    +

    Saturday

    -

    7am

    +

    Sunday

    -

    7am

    +

In this lecture, we will, uh, continue the series and now we'll introduce you to, uh, developing, uh, concept, uh, for the, uh, non automobile mode. Right. And then also, finally, we will look at how you develop an integrated Emma Lewis. Uh, considering all of the modes together. So, uh, we've already looked at, uh, the level of service for an automobile mode and how, and we have seen what are the factors on which the level of service of an automobile mode is based on now, when we, uh, if you look at the non automobile mode and start looking at the first non-entrepreneurial mode, which is. Uh, the pedestrian mode, uh, we will see that, and you've already gone through the level of service or of, uh, of, uh, pedestrians. What you already know is that the pedestrian level of service, uh, depends upon the average pedestrian space. And, uh, pedestrian level of service score, right? Uh, so a score is developed, uh, by, uh, uh, by, in getting the perception of different pedestrians on different, uh, facilities off the street, for example, uh, what do they, what they perceive about the sidewalk? What are do they perceive about shade, comfort? All of those things, uh, aggregated up, uh, to develop a level of service score. And then you actually look at. Uh, how much average pedestrian space is available for them to walk on. Uh, so an interaction between those two, uh, gives you different levels of service. So that is essentially how you develop a level of service, uh, for pedestrians. Uh, even when we are looking at it from the point of view of an MMOs for pedestrians, uh, if you want to, uh, develop, uh, MMOs. Uh, from the point of view of, uh, transit or bicycle, uh, it is still at a very nascent stage and it is all, all, uh, um, um, the researchers have been able to develop so far is a level of service. Uh, for, uh, either transit or bicycle, uh, using only the level of service score. Uh, but however, uh, the score is developed separately for transit and separately for bicycle, but the ranges, uh, remain the same and the, uh, and the, uh, level of service in a versus B versus C ranges remain the same. But, uh, obviously the questions or the variables that are asked are the variables that are input, uh, would be different for transit versus, uh, different for bicycles. Uh, you would again, uh, see that, uh, the level of service for pedestrians is done in a similar manner. As we have shown you, uh, for the level of service of the automobile mode, again for the entire facility is broken down into different segments. And, uh, the segment level of services are individually developed, uh, level of service service for each of the segments. And then we, uh, a weighted average of the, uh, all the segment level of service scores are aggregated up. To develop the level of service score for all the level of service for the entire facility. Also. So a similar model is followed, uh, here as well. Uh, even for the bicycle and transit levels of service, you will see that the individual, uh, level of service scores for, uh, each of the links. Uh, calculated and then a weighted average of them for the entire length of the facility is developed. So that is, uh, that is how these things have been, uh, started, uh, in that implementation because these are very new concepts. So, uh, as more and more data gets available as more and more sophisticated, uh, techniques are developed, I'm sure these will evolve, uh, into, uh, into more robust. Uh, methods of developing levels of service. Uh, but, uh, for now, uh, what latest we have is, uh, is these weighted average levels of service scores for each of these three different modes are four different modes. When we look at, uh, the multimodal level of service concept, So again, uh, if you take the same, uh, kind of, uh, uh, street segment, uh, which we have already calculated the auto level of service, if you remember in the previous lecture to be C uh, then now if you have, uh, for the same three segments, if you have different levels of service scores, uh, for pedestrians, bicyclists and transit, Uh, how do you develop, uh, then can you, uh, can you compare the levels of service, uh, of, uh, offered for each of those modes on the same segment? Uh, this is the big advantage that, uh, has to be, uh, uh, driven home that, uh, each of the segments may have, may offer different levels of service to different types of modes. So it may be good for. Um, walking, but it would be not be very good for the motorized vehicles. Whereas, uh, sometimes it may be very nice for the bicyclists, but not so good for the, uh, pedestrian. So, uh, same piece of road or same stretch of road. Uh, how can you analyze it from different perspectives? This is what, uh, 2010 technique allows us to do. So now you have got, uh, uh, uh, there's a, the free flow speed, uh, for, uh, uh, for this segment, uh, free flow. So all of you, uh, each of these, um, parameters for each of the three segments are given to you. Uh, so if you start looking at the pedestrian level of service, uh, the space, uh, pedestrian, uh, first you want to understand what is the average pedestrian space. So if you, each of the space values are given, uh, and each of the lens segments are given. So if you, um, uh, use the formula and get the score, uh, and then if you develop the, uh, level of service score for each of the segments, uh, weight by the length of that segment, And, uh, summit, uh, divided by the sum of the entire segments, you would get a value of 3.6. So then if you go back to, uh, to the, um, table and you'll see that your average area per pedestrian is 25. So which falls between 24 and 40, and then your, uh, uh, pedestrian level of score is 3.6. Uh, which falls, uh, uh, between 3.5 and 4.25. So if you see the point where these two meet, you will see that it is level of service D so now you can already start to think that, uh, this gives a poor level of service for pedestrians, uh, when compared to, uh, the level of service for motorized, uh, for automobiles, for example, it was giving a level of service of seat. Uh, as we signed it, but he was selected, right. So already, uh, you can see, uh, the variation in the levels of service offered by the same stretch of road to different, uh, modes that are playing on it. Uh, similarly, if you do it for, uh, bicycles, remember for bicycles, it is only the level of service, uh, score that is used, uh, as of now to develop, uh, to determine the level of service. So if you know the scores for each of the length segments, you just do a weighted average and you get 3.76. Uh, so a 3.76 level of score, uh, for bicycle, uh, would mean that, uh, it falls in this range. And so even for bicycles, it's a level of service D and for transit, uh, if we do it in a similar manner, you'll get a 2.8, nine level of service, which. Gives you a level of service. See, so, uh, for, for transit and for, uh, automobiles, uh, this stretch, uh, provides a level of service C that I, for bicycles and pedestrians, it provides a level of service D so, uh, so you can conceptually and now, uh, figured out, uh, that, uh, this, uh, this stretch of road. Is a more favorable towards motorized vehicles because public transportation mostly is, uh, motorized. Uh, some form is non-motorized if you have cycled pictures, so on and so forth, but, uh, mostly it is motorized and, uh, automobiles obviously are motorized. So, uh, so the way in which the street is designed, maybe, uh, favors these motorized modes, hence offers better level of service. Whereas, if you are a non-motorized, um, uh, more user or if you're a pedestrian, uh, then, uh, it offers her what our level of service, which is off deep. So this is an easy way of comparing, uh, various levels of service data segment has to offer. So we have gone through all of that. Uh, we already know that the, uh, for level of service for this has been already calculated in the previous. Uh, method. So now we can compare all of that. Uh, so essentially what is happening, how we are measuring all this level of service scores, right? We have to develop that, uh, perceived level of service score. We. Uh, for simplicity sake, we already gave you the scores, but we actually have to develop these scores. Right? So what these scores consists of usually are, uh, perceived, uh, levels of service or perceived quality of service that, uh, uh, various traffic characteristics, geometry design, other features of that road offer to them. Um, users. So when I am walking, I think on the street, I perceived that street in a different fashion, traffic, traffic wise, geometry wise, and other factors wise versus another person maybe perceive it differently. So when fair enough, uh, when we, uh, essentially ask enough pedestrians on that street, uh, about the depth perception of different factors, different traffic factors, different geometry design factors in different. Um, maybe comfort factors, which are grouped under others. Uh, and you then develop a statistical technique to come up with a score. That is what is called a pedestrian, uh, LOL score. So that is the other, uh, element that, um, you are using when you're developing a pedestrian level of service. Uh, you're not only using the average, uh, uh, space, uh, but a space for pedestrian, but you're also using that level of service score. So these scores are coming from either design factors, uh, traffic, operational traffic, characteristic factors, or other factors, which may include, uh, uh, for example, uh, shown here. So these are all, uh, these are all, uh, uh, say comprehensive, uh, factors, uh, are input parameters that have been used. Well for developing, uh, pedestal, uh, levels of service scores for each of these modes, right? So when you look at developing the level of service score for a pedestrian mode, uh, you are taking, you are taking the mid-segment flow rate of motorized vehicles into consideration. You are taking the percent of heavy vehicles. No, you're not taking into consideration. You are taking the pedestrian, Florida into consideration. You're taking the proportion of on-street parking occupied into consideration. So these are very, very important to know that what does the pedestrian level of service score depend upon? Right? So the pedestrian level of service score or bicycle level of service score will not only depend upon. The, uh, pedestrian mode or the, uh, bicycle mode, but there comes the interaction. So now, yeah, even though you are walking, but you are effected by the percent of heavy vehicles, you are not affected. For example, you are not affected by the percent of heavy vehicles that are playing on the road. Uh, next to which you're walking, but you are effected by the proportion of on street parking that is occupied. So if there is on-street parking available and, uh, what percentage of it is occupied affects the perception of the person who is walking along the road and that perception when it gets affected, it affects the level of service score. So these are a comprehensive list of all the data elements. Uh, that are, uh, used for developing these level of service scores. Uh, so you should, uh, you should be aware of this. You should, uh, take these as basic, uh, input parameters, at least for your own facility. Uh, you should know that these are all, uh, parameters that are used in the, at CMT 10 method, which is based primarily in the United States, but, uh, that does not mean that it may not reflect. Uh, the, uh, characteristics of your hometown or your home city, it may or may not, but at least it's a good starting point. So you start with this, you'll see if you'll get into it. Results of levels of service scores. If you don't get, then you look for other parameters to include in the development of her level of service score. So this is a good starting point. So there are different traffic, characteristic parameters, different geometry design parameters that are given here, uh, as well as different other parameters. For example, uh, in the other parameter section, you can have the area type, which is residential or not a payment rating condition. Maybe something a see it is important for the bicycle mode, but not important for the pedestrian moderate, because Palestinian usually should not be walking on the pavement. Uh, he, or she should be walking on a facility dedicated for pedestrians, but, uh, in our case, well, maybe in India. See, so that is maybe something that in Indian case, this becomes actually a factor, uh, which should be considered in developing the pedestrian level of service score. So that is what I mean when I say that these input parameters should be a starting point for you. To start understanding, uh, how to develop a score. Uh, some of these may change based on Indian conditions, uh, that is up to you to, uh, look at your local conditions and, uh, tweak them, uh, in a, uh, in a, uh, intelligent fashion. So now when we start looking at the interaction between modes, this is the last step in understanding how to develop a multimodal level of service. When you have actual interactions. Uh, between the modes and then you develop a level of service score. So as we just showed you that how these interactions may happen, right? When you're walking, you are not only affected by other people who are walking, but you may be affected by the vehicles on the road. You may be affected by, uh, parking on the road. So those are all not, uh, pedestrian, uh, factors, but those are factors from. Other modes, such as that is in factor from the automobile mode. So similarly for bicyclists, uh, you know, you may be affected by the, uh, volume of heavy vehicles that's on the road. Uh, and that's a factor. That's not a bicycle factor, but that's a factor from the automobile mode. So an automobile mode may affect. Or may have an effect on the level of service scores of the other modes. So that is essentially the interaction that we are going to show. Uh, uh, and also, uh, transit mode will have an effect on the pedestrian level of service and the bicycle pedestrian mode will have a effect on the pedis bicycle level of service and, and vice versa. So there'll be a lot of interactions. And when you see those interactions at the end of these. Uh, slides, you will understand that how complex, uh, this concept of a multimodal level of service could be, uh, when you actually develop now or when you try to develop one score. For example, uh, we have not yet ventured into developing, uh, one multimodal level of service score. Uh, we are still at the level of having. Uh, LA multimodal level of service, uh, score developed for each of the modes, uh, but for one specific facility. So that is where we currently are. We have not, uh, the state of the art has not developed, uh, uh, or not, not developed a combined level of service. And showed it for, uh, for the entire, uh, for the, uh, for the facility. We are showing it for individual modes, but if you start understanding, uh, the, uh, the interaction that is, well, you will be, uh, completely getting the, uh, depth of the, uh, problem that we are handling. Okay. Uh, the urban level of, uh, the urban street level of service for a given mode is the average degree of satisfaction with the urban street that is reported way. Yeah, large group of travelers using that mode if they had traveled the full length of the study section of that state. So these are some of the, uh, some of the nitty-gritties that you have to keep in mind when you're doing the survey, right? Uh, it is not, uh, you should be not asking a person who is maybe a leisure traveler, uh, maybe, uh he's uh, he's he or she's an out-of-city traveler who has come here for leisure. And then if you ask him or her, how good is this facility? That it would not be a representation of the people who walk on that street every day, for example. So, uh, when you do all this, uh, you have to keep in mind how to sample, how to develop a site, how to create your sample size, uh, what sampling, whom should you include in the sampling? You do usually do random sampling, but the random sampling should include people who walk, uh, there more often than not. Right. So you have to be very careful when you, uh, when you develop your samples, uh, for these, uh, level of service. So now if you start looking at, uh, the interaction between modes, uh, there are 37 different variables to predict the perceived level of, uh, perceived level of satisfaction or degree of satisfaction. These 37 variables are divided into four types. Uh, one is the facility design. So how, what are the parameters that affect the design of that facility? Uh, facility control, um, whether it is, uh, uh, it has signalized intersections on signalized intersections, access points. Remember the diagram that we showed, uh, about the entire facility, uh, transit service, whether, uh, that piece of, uh, that stretch of road or that facility actually has bus routes, Metro routes, uh, does it, or does, does it not have, does it have multiple routes? Uh, so all that, uh, goes into account, uh, the factors going to account and the volume of all of the modes, obviously how much volume of. Uh, transit. Is there a tumbles, are there bicycle sedan, pedestrians are there all of these 37, uh, variables are grouped under these four factor, uh, these four factors. And then we see that these individual parameters, how they, uh, uh, interact amongst each other to develop the level of service for each of these modes. For example, the auto level of service model one and two uses only four variables. So you can develop an automobile level of service using, uh, one of the, uh, one of the two models that are shown here, the model one, uh, develops it based on, uh, delays. Uh, our, the presence of left-hand lane, whereas, uh, uh, the level of service model to, uh, develops it for, uh, using mean speed and the median time. So you can choose one or the other in order to develop the Ottoman by level of service. Uh, but they use only for four variables, uh, which are shown here. So these are the four variables that are shown here. These four variables, uh, differ for different types of. Uh, facility design the differ, uh, this variable differs by facility control and obviously all the volumes of, uh, the different, uh, the different modes will have a bearing on that, uh, variable. So this is what this entire table allows you to look at. Uh, it tells you what are the inputs, uh, for the level of service models. But each of the modes and, uh, how do that, uh, input variables, uh, vary by, uh, the type of, uh, uh, categories that we have, uh, classified them into, uh, uh, are the, uh, uh, does it, does the delay, uh, depend upon facility design or facility control? Obviously depends upon control because if it is an unsynchronized intersection, the delay will be different versus a person signalized intersection. So it depends upon, uh, the facility, the facility control of that, uh, piece of road, for example, uh, whereas the left-hand lanes, uh, the presence or absence of left-hand lane is not, uh, uh, control feature, but it's a design feature. So that is what this allows you to tell that this shows you. Uh, essentially, uh, XXX indicates the input variable, uh, is influenced by that factor. Uh, so, uh, if you see, uh, automobile mode, you have only four, uh, variables by which you can develop a level of service. Uh, well, whereas if you start looking at the other levels of service, for example, the transit level of service that uses six variables. One, two, three, four, five, six, and these six variables, uh, our group are, are effected by various things, uh, in these, uh, in this table, for example, uh, uh, the pedestrian is one of the, uh, one of the variables that has an impact, uh, on the transit level of service score. Is the pedestrian level of service. So this is, this is the interaction. So, uh, maybe higher the pedestrian level of service. Uh, the better is the transit level of service score as well. So this is an interesting interaction that you can immediately see how one mode is affecting the other mode. Right? This is what we mean when we say that there is interaction between, uh, different modes and their interaction actually affects the level of service of different modes. So you can easily follow to all of these, uh, uh, when we, uh, when we talk about pedestrian volumes, But a student volumes affect signal timing, which affects the delay for pedestrians and buses and hence affects pedestrian level of service. Right? If you have a high number of pedestrian volume, uh, it may, uh, at a signalized intersection, uh, then there may be greater green. I needed for the pedestrians to move that may impact the green time for transit and as the transit level of service, maybe. Perfect. So, so those are all the various interesting interactions. Yeah. These, uh, uh, different parameters have with different, uh, uh, four different, uh, levels of service of different modes. Uh, now when we start looking at the bicycle mode, you will see that, uh, it becomes even more compelling, but where the bicycle level of service now uses. Are 10 different variables in order to, uh, developer level of service score. So you see how we are gradually getting more and more comfort where automobile mode, you could just use two variables apart model to develop a level of service. Whereas a transit needs six variables to be now collected from the field. Um, uh, bicycle level of service now has to collect 10 variables in order for them to develop a level of service score. And then when you go to get into, uh, pedestrian level of service Corps, uh, this is the, uh, something that gets really, really complex because now you're dealing with, uh, human beings who are walking and their perceptions and their perceptions may vary by age, gender, uh, occupation, uh, I mean multiple things. So, uh, now it becomes very, very difficult to just capture. Uh, the, um, uh, the level of service core using a few variables. Now you're gonna have a whole lot of variables, uh, to actually capture the level of service. And, uh, then we, when we talk about interactions now, uh, there are, uh, vehicles per wa, but our also has a bearing on the pedestrian level of service, right. Uh, if you see that, uh, let us look at the bicycle. Pedestrian bike, civil conflicts has an impact. Um, and that is directly related to the bicycle volume that has an impact, uh, pedestrian level of service, uh, uh, transit, uh, also vehicles transit vehicles, but, uh, but are, has an impact, uh, right turn on red. So, uh, that will be left, turn on red for our case because we'd drive on the left-hand side of the road. Uh, so if you are, uh, you're permitted three lefts, then that has an impact on pedestrian level of service as well. Right because pedestrians may be crossing that road and you have a free left, and then there'd be a conflict. A conflict point may rise. So you see when you're developing a personal level of service, now you have a whole lot of variables that can influence it. And then it becomes a very complex to develop the level of service. So if you put all of these together, now, if you put all of these together to actually see how the interaction between the modes occur, You have, uh, your, uh, uh, uh, your groupings on the top and you have all of these different variables, uh, shown in, uh, uh, uh, shown us adults here. You, you, you start to observe that the number of adults that feed into the autumn by level of service. Is much fewer when compared to the transit level of service, which is again much fewer when compared to the bicycle level of service. And finally, the pedestrian level of service has so many arrows that are coming in from different directions, which makes it even more complex to develop the pedestrian level of service. When actually you are looking at the interaction, if you had to just consider, uh, for example, developing a pedestrian level of service, Uh, for an off-street, uh, uh, trail, for example, a trail that goes, uh, that goes through a, uh, a forest area. And you want to develop a level of self, personal level of service for that trail. Now that is, uh, an easier task to do because on that trail, there is nothing else, no other mode that can go through. Right? So there is no interaction with other modes. You only have people to people interaction, uh, pedestrian to person interaction. And the level of service for developing a level of service score for such a facility would be. Easier, uh, then, uh, on the other extreme, if you want to develop a level of service score for an expressway. All right. And, and on an expressway, uh, no other modes are allowed other than regular modes, right? Uh, it is restricted for a non-motorized transport and obviously it is a, um, it's not restricted for, uh, buses, public transit, but, uh, just by the nature of the design of the, um, Uh, expressways, no public transport, no public transport runs on it. So when you're trying to develop a level of service score, uh, for automobiles, for, uh, expressway, it is. Much simpler than when you want to develop a level of service score, uh, for an automobile mode for an urban street, or maybe an urban collector or an urban article. Right. So why is it difficult? You can see now in this picture that, because there is interaction with other modes. Now this interaction with other modes makes things very complex, but we have given you a very simplistic methodology by which you can do it, uh, at cm 2010 methodology. Where you can calculate, uh, the level of service scores, uh, for each of the segments. And you know how to now develop the level of service scores, because we have shown you what input parameters can you use. And those input parameters, you can then take, uh, to develop a questionnaire, a survey questionnaire for your city or your town, and, uh, get the percept perceived values from the responses of the city or the citizens that are using those facilities, and then develop a level of service score. Using those level of service scores for each of the segments, you can then, um, uh, average it up using the lengths based on the length and develop the level of risk for the entire facility. So I hope that, uh, uh, this has been very helpful to you. This is a concept that, uh, uh, is clearly, uh, uh, uh, in, in the part of evolution. Still, a lot of research is happening. This is a new. A new Avenue that, uh, transportation, uh, researchers are engaging in. Uh, and also policymakers are more and more getting interested in this because, uh, many cities are now joked and congested and, uh, they want, uh, solutions, uh, to ease this condition and they can develop solutions only when they know. Uh, where the problem is, is the problem with the pedestrian mode is the problem with the automobile modes is the problem with the transit mode, unless they know that, uh, they cannot offer, uh, uh, point X solution. So this is something that is going to help, uh, everybody. And everybody's going to be need of this in the near future.