Emme users upgrading to Emme 4.4 will notice among other improvements a new interactive and animated 3D mapping environment called Emme Scenes. While not a modelling feature per se, Emme Scenes is designed to help you better understand your travel models. This post explains some of the ways that you can use Emme Scenes to animate time-of-day results, traffic flows, regional travel patterns and accessibility, and simulation playback to explore your travel model in new ways.
Disclaimer: The examples below were produced by INRO for illustrative purposes only and do not directly reflect data that has been used or approved for planning purposes in any way by any party, stated or otherwise.
The release of Emme Scenes represents another step on our journey to portray a more comprehensive and accurate representation of urban mobility. This journey was jump started several years ago with a number of requests from our client partners to help visualize increasingly disaggregate data from and related to travel models. The computational graphics systems that we were developing to visualize wide area dynamic traffic assignment models, activity-based travel models, and other large-scale mobility data sets like point events / activities, land-use and buildings and transit became so commonly requested that we ended up releasing it as CityPhi, a mobility animation studio for data scientists.
We then shipped the CityPhi animation engine as part of Dynameq 4 to allow detailed simulation playback of metropolitan-sized traffic simulations (1,000,000+ cars) including full vehicle- and lane-based trajectories for the first time.
Around the same time we noticed that Emme users were keen to develop CityPhi visualizations using data from their travel models. It turns out that even zonal aggregate travel models can produce some relatively big data sets, and we eventually became convinced of the utility of new visual treatments using this data. This first release of Emme Scenes includes some of the most popular CityPhi treatments using travel model data, but available natively in Emme 4.4 via simple workflows and a new user interface. Emme Scenes is motivated on the premise that seeing our models in new ways can bring new insights, and that if these are sufficiently easy to produce then they can become an important new tool for travel modellers.
Bandwidth plots don't show movement or time even though the traffic results produced by most travel models represent link-level traffic flow rates and speeds. You can conveniently visualize these aspects simultaneously from any existing travel model using the traffic flow layer in Emme Scenes. In the example here, traffic flow animation is shown against extruded 3D bandwidth plots of transit volumes. Notice how you can discern differences in traffic speed, number of lanes and even volume/capacity ratio between freeways, arterials or different parts of the network.
(You can read more about DTA here if you would like to see queuing, traffic dynamics and individual vehicle behaviour in your traffic models.)
Time is represented explicitly in travel models in other ways. Almost all models today include at least some kind of time-of-day choice to treat AM, mid-day and PM periods differently. And some network models, like the Space-time traffic assignment in Emme, produce explicit temporal results across time periods. With Emme Scenes you can easily animate network values across time periods, across scenarios or even to show ranges of response from sensitivity testing your model parameters or inputs. In the next example, hourly traffic flows are animated over the course of 24 hours. Notice how the commute direction change is clearly visible in and out of the CBD between the morning and evening. Values are interpolated smoothly between 1-hour periods, but this is configurable to preference.
Note also how 3D text labelling works so you can see quantitative values in addition to styles and symbols, and how the text also participates in the animation. When you take a top-down view in Emme Scenes you can replicate the effect of 2D bandwidth plots, but the choice is up to you: Emme Desktop worksheets let you save views, print to image, SVG and PDF, and write scripts to automate repetitive reports, while Emme Scenes lets you create storyboards with animated keyframes and record video. Your choice.
Origin-destination travel demand and accessibility are notoriously difficult to visualize at scale. Desire lines become very cluttered when you try to visualize anything more than a one-to-all or all-to-one plot, and they are completely unusable for visualizing all-to-all O-D pairs even for small models. The problem is illustrated below:
Emme 4.4 also includes another technique to visualize demand where triangulation is used to represent conceptual flows on a 'spider network', but while this method shows direction and demand 'flow', you lose a sense of the direct contributions between individual O-D pairs, as shown below:
In addition, Emme Scenes lets you animate complete travel demand simultaneously for all O-D pairs, even for regional models, where the rate of animation can be determined by an impedance or an accessibility value. The example below illustrates regional transit demand and accessibility for nearly 12 million non-zero O-D pairs. Demand is coloured and sized proportionally to value, but this is again configurable to preference. Also note that accessibility reflects a generalized cost measure instead of actual travel time. You should be able to identify the heaviest commute corridors and their relative accessibility, and once you take in the regional demand patterns you can then filter, select and dive into any details. You can produce demand and accessibility scenes for any demand matrix and any impedance or accessibility value so you can study differences across your travel market segmentation, modes, time periods or other aspects.
Simulation playback for disaggregate models can help tremendously with model validation, troubleshooting and quality assurance. With Emme 4.4, the Schedule-based transit assignment procedure has been upgraded and now works with crowding so that it is suitable for transit service planning applications in high-frequency, urban settings. There is an enormous amount of information in a day's worth of timetable itineraries for a metropolitan region and more so when you consider results like boardings, alightings and ridership details, all of which can be animated easily using Emme Scenes.
Emme Scenes is available now in Emme 4.4, which you can go ahead and downloadfrom your account. We're looking forward to your feedback on the INRO Community Forums, and make sure to keep in touch for more updates!
(And if you happen to like any of these animations and want to reproduce these or others from your own mobility data sets in a Python data science environment, you can do so with CityPhi. Let us know here.)