Face with passengers’ attack: Individual ability and team tactics
The spatial distribution of the hailing demand is very important for DRT operation.
If all users' ODs (origin and destination) and departure times are the same, the shuttle service connecting the ODs is the optimal operation for DRT fleets. In other words, if the passenger’s 1) origin, 2) destination, and 3) depth time are the same, it is the easy to serve. This traffic demand can be transported to a fixed-time, fixed-route bus without waiting time and detour distance.
Conversely, the wider the passengers' departure time and the spatial distribution of ODs, the more difficult it becomes to transport with fixed-route bus services. As such, the spatial distribution of traffic demand (mainly comes from land use pattern) is a key factor in determining the operational difficulty of DRT.
The most common type of land use pattern is in which the Central Business District (CBD) exists in the middle, and an area with low land use density area exists outside. In these cities, many passenger’s ODs are concentrated in urban central areas. In the last article, Studio Galilei defined this area as 'Demand Swamp' as below (see ‘The biggest difference between Ride sharing DRT and the Simple hailing service’ ).
Under this traffic demand pattern, DRT fleets are difficult to escape from the central area because most passenger traffic begins and ends in the centeral area. However, even in this city, there is a certain number of passengers who have their origin or destination at the outer area. For serving to these passengers, DRT vehicles must abandon passengers in the central area and go out to the outskirts. In this case, a DRT fleet must run a distance traveled without passengers. That is called ‘dead-run’.
As this dead-run increases, unfortunately, the loss (to the DRT operating agency and all citizens) increases. This is because there are always numerous passengers hailing DRTs in the central area. In other words, the wait time for passengers in the CBD increases while the DRT fleets move to the outskirts.
As stated in my previous article about the ‘Demand swamp’, how to respond to this problem depends on whether DRT relies on citizens' subsidy or not. If DRT services are the subsidized public transport, every citizen has the right to receive services wherever they are called. Conversely, if the service is operated only with passenger's fare and DRT companies do not have a duty to serve all passengers, it is best for DRT fleets to operate only in central areas where demand is high.
In the end, the difficult situation is when DRT relies on subsidy raised by citizens' taxes. In this case, the biggest concern of DRT operators is how to efficiently handle outer passengers. What is the best solution to this?
The answer to this lies in the demand pattern. The root of the problem is that the passenger demand is spatially unbalanced. Therefore, the optimal solution can place DRT fleets spatially unbalanced as well. In other words, more vehicles are kept as long as possible in the CBD, and less vehicles are placed outside as below.
Studio Galilei is applying this concept of algorithm to DRT operation technology. Studio Galilei defined this DRT operating system as a ‘Picker and Sweeper’ system. The hailing demand of outside is handled by small vehicles, and passengers in central areas are handled by large buses.
The important point is that the roles of these two types of vehicles are clearly distinguished, and the two types of vehicles do not escape from their areas. In the case of a bus that acts as a ‘sweeper’, it is responsible for short distance trips that occurs inside the central area. Therefore, the number of passengers per vehicle per hour is also very high in the CBD. However, ‘picker’ DRT vehicles which defense outer area do not work often. Instead, it stays on the outskirts and plays a role in preventing vehicles in the central area from having to come out on the outskirts.
The two types of vehicles play like bystanders who do not assist each other, but in fact, they are thoroughly collaborating under the control of TAMOS-O platform. It is like a cooperative defense of a soccer team or a basketball team.
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The ‘Picker and Sweeper system’ can be said to be the 21st century version of the ‘Feeder and Corridor system’ that made it possible to operate public transportation efficiently in the 20th century. However, the 'Feeder and Corridor' system caused inconvenience because it required passengers to transfer. In contrast, in the 'Picker and Sweeper system', all passengers can be transported without transfer through strategic collaboration of DRT fleets.
What was the result of this strategy? Studio Galilei is applying an earlier version of the 'Picker and Sweeper strategy' to the TABARA DRT service, which is operated for tourists in the Gi-Jang area of the city of Busan. The area size is 16.0 km2 and the 4 ~ 5 vehicles are operated and a maximum of number of passengers is 370 per day. Despite the high demand at the peak, the waiting time did not exceed a maximum of 10 minutes after launching, and the average daily waiting time was 6.5 minutes. TABARA's operational performance was superior to that of other regions where the 'Picker and Sweeper strategy' was not applied.
Studio Galilei believes that a strategy such as 'Picker and Sweeper system' is essential in large size of DRT fleet operation (we call it ‘Super Fleet Operation’).
Of course, Studio Galilei’s philosophy of algorithm design and the optimization-based routing algorithm are also very important. However, Studio Galilei thinks that the various algorithms that make up each TAMOS-O are the individual players of the soccer team. In other words, having a good algorithm in DRT operation means having a good player.
But gathering good players does not always guarantee a good team. A good team is a team of good players with good teamwork. The teamwork is a tactic to effectively face with passenger attacks by using various fleets. Designing a good tactic needs a lot of experience, which is why Studio Galilei works with the best transportation planners.
Readers who need a more detailed description of the 'Picker and Sweeper system' or additional descriptions of Studio Galilei’s technology should click on the link below. This is a presentation video presented by Studio Galilei at the Next Mobility (NEMO) 2024 event hosted by Korea's leading mobility service company Kakao Mobility. The presentation is given in Korean, but there are subtitles, so you don't have to understand Korean. For additional questions, please send me comments or messages.