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Is it possible to control the budget of a Demand Responsive Transport?

budget Demand Responsive Transport

Is it possible to control the budget of a Demand Responsive Transport? In this series of articles, we suggest to deconstruct misconceptions about Demand Responsive Transport (DRT) and shared mobility. Misconception #1: “If too many people use my DRT, I won’t be able to control the budget”.

Some mobility stakeholders are setting up dynamic DRTs in the hope – unconsciously or not – that they will be used sparingly. They imagine the ridership incentive make the DRT too expensive to use. This encourages behaviours that are sometimes schizophrenic: the service must attract the public to demonstrate its added value (ride pooling). But not too much, because too attractive, it would be too expensive. Beware of abusive shortcuts!

Determining an “acceptable” offer

By determining an acceptable level of supply for the Public Transit Authority (PTA), we can get out of this schizophrenia. When contracting or designing the service, it is in the interest of the PTA to ask itself how much it is willing to pay for its DRT service. To do so, it is necessary to determine the maximum acceptable offer in terms of number of vehicles assigned to the service, number of rides per day or the cost of the service.

Once the means have been capped, an increase in ridership necessarily improves the performance of the service. The PTA has only one incentive left: to provide the best possible service at constant means.

Define the best service in this context

Once these means have been determined, the PTA will keep full control on its budget. It will have determined the maximum load it will be able to carry. It will then be up to it to set up the best possible offer (in terms of used algorithms, service design (a zonal configuration will be preferred to a fixed-line configuration), etc.).

In complete financial security, the PTA will take care of removing all obstacles to the adoption of DRT: short booking deadlines, simple and quick sign up and effective communication will make the service attractive and reliable. A success adapted to the means.

 

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4 essential steps for a demand responsive transport 2/2: Extending the service and integrating new use cases

essential steps for a demand responsive transport

The efficiency and success of a demand responsive transport (DRT) service is based on several steps. In this article, we will discuss the two other essential steps to the implementation of an efficient dynamic demand responsive transport service: the extension of the service and the technical and new use case integrations. essential steps for a demand responsive transport

What is a dynamic DRT?

The aim of a dynamic DRT is to rationalise public transport by adapting supply more closely to demand with more interesting economic and ecological benefits. Vehicles, reserved via a mobile application, a website or a call centre, replace underused or non-existent fixed lines. Their route is optimised thanks to algorithms.

Step 3: Service extension

The service extension stage is a move to scale aimed at perpetuating DRT to make it a structuring element of the mobility offer in the area in which it operates, to overcome the weaknesses of the existing transport network or to rethink the area’s public transport service plan by opening up poorly connected areas.

This step is used to identify the areas and use cases that best lend themselves to DRT in order to replicate the DRT model. It enables a “tools” strategy to be defined and implemented, following integration logics aimed mainly at replacing deficient fixed lines and/or converting under-utilised services.

The main challenges in extending the service are based on the method of acquiring the DRT software (calls for tender, over-the-counter, etc.), the balance with the rest of the network, integration with the existing network and its tools, performance monitoring and consolidation of service quality criteria.

What indicators should be taken into account at this stage?

  • The same as those of the pilot (step 2)
  • Acquisition, retention, use, mileage and knowledge of users.

 What questions should be asked before moving on to the next step?

  • Are there other needs or cases of unaddressed uses?
  • What is the capacity to replicate the service operationally in other areas, possibly with different operations or use cases?

Find out more about the service extension set up for Ile-de-France Mobilités by Padam Mobility

Step 4: technical integrations and new use cases

The principle of technical integrations: 

  • Adding new use cases to the existing ADP platform at marginal cost and benefiting from their advantages. In particular, this makes it possible to pool operating and management costs (vehicles, drivers, etc.).
  • To meet specific needs (e.g. transport of healthcare personnel in the event of a health crisis, substitution services in the event of works, occasional / event transport).

Cases of use that can be integrated:

  • Other shared public transport: TPMR, school transport, evening service in stations without reservation, airport shuttles, etc.
  • Occasional transport: transport of healthcare staff in the event of a health crisis, substitute services in the event of works, occasional / event transport (e.g. a concert or football match).

Technical integrations are used to make TAD a brick perfectly integrated in your MaaS (Mobility as a Service) vision. As an aggregator of mobility solutions, it aims to offer individuals the opportunity to visualize their journeys from end to end regardless of the type of transport used (public/private, shared, soft, mass, etc.).

In practice:

  • DRT platform integrates with the local MaaS and allows users to complete their public transit trips with DRT.
  • The TAD itself integrates with the network, synchronizing with train schedules for example.
  • Finally, other transport solutions exist, such as carpooling, bike sharing, car sharing, taxis/VTC etc. The TAD can be combined with these other forms of transport to complete its offer when it becomes saturated. For example, the TAD platform can offer carpooling or taxi/VTC alternatives when no TAD is available in the next half hour, and vice versa.

Learn more about the integration of MaaS in Padam Mobility solutions

Our experience in ADP design, configuration and optimization leads us to the observation of these 4 steps that we consider to be a good factor of success and efficiency of an ADP service. The success of an ADP service mainly includes user satisfaction with the service. In all cases, the best approach to adopt always consists in getting in touch with a dynamic ADP professional who will be best able to advise you in the implementation of your service.

Learn more about the two other essential step 1/2

 

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Padam Mobility offers technological solutions to ensure social distancing in transport

End of stay-at-home order

During the month of May, the population will experience a gradual end of lockdown. Returning to school or to the work, the issue of traveling within safe distances is a challenge.

Transforming bus lines that embark passengers at stops into vehicles that take reservations via mobile app, website or phone, will guarantee social distancing.

This will avoid passengers having to let buses pass because they carry too many passengers. With the right technology, it is also very simple to implement.

It is a matter of accompanying public transport in in the end of lockdown for which it is already urgent to prepare, with ambition and a sense of responsibility. To get out of the health crisis, but also the economic and social crisis we are experiencing.

Grégoire Bonnat, Co-founder and CEO of Padam Mobility

Presented by governments around the world, the end of the saty-at-home order plans set out broad strategic guidelines. Priority subjects: public health, getting people back to work, reopening businesses, schools and transport.

To avoid contagion in metros, buses or trams while allowing citizens to move around, one possible solution may be to transform the usual lines into on-demand transport, easily adaptable and meeting health safety requirements.

Transforming a bus line into a on-demand Transport : a preferred means of mobility to adapt to all demands while ensuring health safety.

On a very simple model, users will be able to reserve a seat on their bus via a mobile application, a website, or a dedicated call centre. The number of seats available in a vehicle at a given time will depend on health constraints. This number could be evolving very easily as the end of the stay-at-home order progresses: technology allows it. Thus, it will be possible to ensure a filling of 20%, then 40%, 60%, and so on until the return to normal. It will even be possible to go back if necessary.

Transportation is guaranteed, there is no more risk of ending up in a full bus, or of having to let it pass without knowing if there will be room in the next one. The transportation offer becomes clear and readable for everyone.

Several customers have already asked us to set up reservation solutions adapted to the specific needs of the period.

From one day to another, we will get instructions related to the opening of this school or that factory. Public transportation must be able to adapt very quickly. On-demand Transport works with an associated software that allows us to foresee and guarantee reservations. It is a tailor-made mobility solution, adaptable in real time and therefore extremely relevant in this context of end of stay-at-home order.

Grégoire Bonnat, Co-founder and CEO of Padam Mobility

End of lockdown and massive influx of passengers: the concern of public transit operators

“Transports are a key factor in economic recovery, but it is particularly difficult to maintain physical distancing and sanitary measures,” introduced the French Prime Minister before detailing future government measures for public transport.

For the entire Paris region, RATP President Catherine Guillouard already explained on France Inter on 24 April that ensuring safe distances would not be feasible, given the hyper-density of the Parisian network: “If we had to apply the rules of social distancing, we would only produce 2 million journeys per day, compared to 8 million with a network supply at 70%. …] We must plead for teleworking and refer to the new mobilities”. Maintained until now at 30%, RATP traffic should increase to 70% from the first day of the end of stay-at-home order. An opinion supported by the UNSA-RATP union, judging that it would be “unmanageable by the company” to police all travellers and committing everyone to take responsibility and to telework as much as possible.

The same concerns and observations were made by other French cities, such as Le Mans and Lyon, which are preparing to reopen 80% of their public transit networks. Last Wednesday (22 April), the SYTRAL president Fouziya Bouzerda presented the measures envisaged during the end of the stay-at-home order to manage the flow of passengers to come: installation of vending machines in metro stations allowing the purchase of kits containing masks and hydroalcoholic gel, installation of automatic disinfecting kiosks and cleaning of trains with virucide.

By offering to reduce and guarantee the number of seats available in the vehicles to respect social distancing, Padam Mobility ensures the continuity of its services in strict compliance with the health measures in force (wearing of masks for drivers, systematic disinfection of vehicles).

 

Find out more about DRT’s adaptations in times of CoVid 19

Coronavirus : learn how Padam Mobility helps DRT operators to adapt their services

 

 

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4 essential steps for an effective demand-responsive transport: the feasibility study and the pilot

étapes essentielles pour transport à la demande

The efficiency and success of a Demand-Responsive Transport (DRT) service is based on several steps. In this article, we will discuss the first two essential steps for an effective DRT: the feasibility study and its simulations, and then the pilot.

What is a dynamic Demand-Responsive Transport?

The aim of a dynamic DRT is to rationalise public transport by fine-tuning supply to demand with more interesting economic and ecological benefits. Vehicles, reserved via a mobile application, a website or a call centre, replace under-used or non-existent fixed lines. Their route is optimised thanks to algorithms.

Step 1: the feasibility study and the simulations

The goal of the feasibility study is to understand the operation and use of DRT on a territory and to question its rationality from an economic point of view. It is used to define supply and demand scenarios, obtain reliable performance indicators, and understand how these evolve according to the different scenarios defined.

The simulations, preferably taken from the DRT platform, make it possible to put figures on the different scenarios based on reservation data, demographic data, transport surveys or telephone data, making it possible to anonymously track journeys within a territory. The simulations operate in-vivo and also make it possible to validate the economic relevance of the service, to ensure the correct configuration of the offer and to identify the risks.

What indicators should be taken into account at this stage?

  • Quality of service: waiting time, percentage of requests served and average detour rate: how do users feel about the quality of service? Are they satisfied enough to re-use the service on a regular basis?  
  • Cost of service: number of people per hour per vehicle per trip, mileage, number of vehicles used and maximum vehicle occupancy rate.

What questions should be asked before moving on to the next step?

  • Is the service financially sustainable and acceptable to the community?
  • Is the project politically tenable?
  • Will users and operational teams agree to host an innovative project such as DRT?

Read more about the feasibility study and simulations carried out for Aviapolis (Helsinki, Finland) by Padam Mobility

Step 2: the pilot

The pilot, whose watchword is agility, is used to test, measure and iterate over short cycles. The pilot is used to validate the relevance of the new DRT service for the need for mobility, the digital transition to a SaaS tool and the strategies and means of communication with the population. It also makes it possible to test the uses of DRT and to understand the issues involved (traction, quality of service, operational handling, etc.).

What indicators should be taken into account at this stage?

  • Quantitative data: number of visitors, distribution of the reservation application & website VS call centre, number of passengers per vehicle and per commercial trip, quality of service.
  • Qualitative data: human transition and change management, satisfaction surveys.
  • Network balance: frequentation of non DRT lines that pass nearby.

What questions should be asked before moving on to the next stage?

  • What is the trend? Is it stable?
  • How is the economic balance of the service?
  • What is the capacity to replicate the service operationally in other areas, possibly with different operations or uses? 

Learn more about the pilot carried out for Keolis in Orleans by Padam Mobility

Find out how to build an efficient DRT

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How to build an efficient Demand Responsive Transport? The business model 3/3

Demand-Responsive Transport business model

The success of DRT service rests on several pillars. In this third and final section, we will discuss the importance of Demand-Responsive Transport business model to ensure its efficiency and sustainability.

When it comes to the economic model of a DRT service, three points must be taken into account: pricing, the operating budget and the vehicle fleet.

1- Demand-Responsive Transport business model: the pricing

The prices of DRT are generally aligned with those of the existing network. However, in some cases, it may be adapted according to the use. For example, on a night service, the fare for the journey may be higher than during the day. Where there is no pre-established transportation network, such as in rural areas, it is possible to set a fare that will vary according to the distance travelled.

2-Demand-Responsive Transport business model: the operating budget

An effective way to optimize the operating budget and save money is to set the trigger threshold. Demand-Responsive Transport by nature operates on a trigger principle (the vehicle(s) will only run if at least one reservation has been made). Nevertheless, it is up to you to go further and define a trigger threshold higher than one reservation. For example, trigger a service from three reservations. The optimal setting of this threshold is highlighted in feasibility studies and simulations prior to launching your network.

It is recommended that you clearly identify the logic of the dynamic DRT software providers behind the capital and operating budget. More and more dynamic DRT solution providers are following a SaaS, Software as a Service model. This model makes it possible to provide a software suite, hosted not on the operator’s computer but on a remote server. In return, the operator pays for a monthly license that includes maintenance and hosting*. This licence is generally calibrated on the use of the DRT solution, which may raise questions about the way local authorities allocate their budget between investment and operation. If you are a local authority, you are encouraged to make your calls for tenders taking care that neither SaaS suppliers nor historical suppliers are excluded by the way the price grid is configured.

Also pay attention to the intellectual property clauses. For SaaS suppliers, intellectual property is the lifeblood of the business. It is therefore very difficult to ask this type of player to deploy its dynamic DRT solution while entrusting maintenance to a third party. This obligation would require them to open access to their code, which would endanger their model and technology.

3- The fleet of vehicles

There are two approaches to making vehicles available to users. They depend on the context in which the Demand-Responsive Transport service is set up. The latter can work thanks to:

  • A dedicated fleet: which may be suitable for areas of varying density, where demand is known to be relatively stable and permanent.
  • A subcontracted fleet (e.g. to taxi companies): which may be more suitable for low-density areas, where trips are triggered less often.

In addition, as in the case of transport for impaired mobility people, there is increasingly a ‘mixed’ approach. In this case, the goal is to meet demand entirely with dedicated vehicles while having the capacity to respond to peak demand with sub-contracted vehicles.

Asking the right questions about how to understand your user experience, how to parameterize your service design and how to configure your business model, in principle lays the foundation for an efficient and relevant Demand Responsive Transport service. If you would like to know more, and benefit from our advice and expertise,  Padam Mobility’s webinars are regularly posted on our YouTube channel.

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How to build an efficient Demand-Responsive Transport? The service design 2/3

Designing demand-responsive transport

The success of a DRT service rely on several pillars. In this second article, we will discuss the importance of service design when designing Demand-Responsive Transport. Even if dynamic DRT works with algorithms that make route decisions autonomously, the logic of building the offer (different from the scheduling / dressing used for fixed lines) requires a few choices to be made.

Designing Demand-Responsive Transport: the right questions

What is to be served?

We recommand to rely on demand and to define the areas (origin-destinations) that you would like to serve with DRT. Answering this question is not always easy, however, there is some data you can use:

  • Data from an existing service
  • Historical data on fixed lines
  • Travel surveys
  • Data from your national statistics bureau
  • Data from telephone operators, etc.

Which service for which purpose?

The aim here is to define the quality of service you want to achieve. These goals vary according to the context. For example, in a dense area, it may be interesting to offer a reservation at the latest 5 or 10 minutes before departure, or even in real time. In a less densely populated area, the focus may be more on the frequency of daily trips or the guarantee of interconnection with other modes of transport. For a company, one might even think about a guaranteed arrival time at the company’s location.

Which service model should be implemented?

Once the DRT’s goals are identified, the service model must be set. Several models exist, here are some of them:

  • The zonal model: this is the simplest and most applied model. It is also called “freefloating”. It involves defining a specific area in which vehicles will operate. Pick-up and drop-off within this zone is directly managed by the algorithm according to demand, with or without additional constraints. In Melun, the service model allows to take the DRT from and to any point of the area.

In Clamart, DRT vehicles ride without restrictions throughout the entire perimeter of the service, with a few stops at mandatory times.

  • The feeder model: it is based on the zonal model, with additional constraint. This model allows users to be picked up in a delimited zone and impose the vehicle to go to a given point at a specific time, even if the vehicle’s route is flexible. For example, a stop at the train station may be mandatory at 8.00 a.m. because a train stops there at 8.10 a.m. This model is used in the context of intermodality (interfacing with other ways of transport). It’s one of the biggest challenges of DRT, which is not intended to replace the existing network, but to complete the mobility offer. In Strasbourg, zonal DRT for journeys within the metropolitan area is added to DRT for journeys to reach tramways and bus stations.

  • The virtual line: the historical model which respects the classical lines, but which stops only when there is a request.

How to optimize the grouping rate ?

There is no exact answer to this question because it depends on the context of implementation and use cases. Supply and demand will greatly contribute to providing a solution. For a given demand, the consequences will not be the same according to the number of vehicles available. Moreover, technical optimisation will impact the rate of groupage: frequency of journeys, authorised detours, etc…

Almost all of today’s dynamic Demand-Responsive Transport solutions offer simulations that allow the comparison of different scenarios by playing with various parameters to find a solution with the optimal estimated grouping rate.

Is the DRT service understandable to the user?

It’s always tempting to embark on a highly technical approach to achieve a highly optimized and intelligent service configuration. However, this configuration may in fact be too complex to be understood by users who will not want to use it. In order to design an efficient Demand-responsive Transport, it is better to design a service that is slightly less optimised from a technical point of view, but which is widely used because understood by the public.

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Padam Mobility meets elected officials and users of La Saire

Réunion publique information La Saire

Public information meeting: on January 30, 2020, Padam Mobility, local elected officials and users of La Saire (Le Cotentin, Normandy) met to take stock of the excellent results of the La Saire TAD Demand-Responsive Transport service.

Very encouraging feedbacks

The La Saire TAD DRT service has been very successful. It registered new users every day for around 1,000 trips made each month. Its ridership remained in strong increase and its pooling rate was close to 60%, which is very appreciable in a rural area. Finally, users rated the service on average 4.7 / 5.

Mothers and youngsters are the most satisfied

I think I can speak on behalf of all the mothers in the room who no longer need to bring their children to school, you have changed our lives at La Saire!”. A mother present in the audience.

The service is very practical and very easy to use”. A teenage girl present in the audience.

A service planned to restart and expand

The elected representatives of the Urban Community of Le Cotentin announced that they were studying very closely the follow-ups that could be given to the service. The chances that the service will restart and be extended to new areas in 2020 are great, but the decision must be submitted to the next Community Council for approval. Padam Mobility could continue to optimize its solutions and make them even more suited to the rural characteristics of the La Saire territory.

A DRT service like La Saire TAD has the potential to revive local life. We talked to the users and they told us that it made all the difference, especially for young people. The latter sometimes had no mobility alternative. We can also think of the tourists who get to Cherbourg train station and cannot move without a car to visit this wonderful region. We hope that the restart of the service and its extension will stimulate a real local dynamic and continue to address certain use cases and specific mobility needs”. Andreas Dieryck, Product Manager at Padam Mobility, present at the public information meeting.

A time of exchange between local elected representatives, the media, users and Padam Mobility

The public information meeting organized at the Digosville municipal hall brought together around fifty people. It was preceded by a press point with local correspondents (La Presse de la Manche, Ouest France and La Manche Libre). This was followed by a presentation of local elected officials: Noël Lefèvre, Transport and Mobilities Vice-President at Urban Community, mayor of Saint-Jacques-de-Néhou; Arnaud Catherine, delegate councilor for urban transportation of the Urban Community and Deputy Mayor of Cherbourg-en-Cotentin, Serge Martin, mayor of Digosville; Evelyne Mouchel, mayor of Mesnil-au-Val; Carole Gosswiller, Deputy Mayor of Bretteville and the Mayor of Bretteville, Pierre Philippart. Keolis (transit operator of the Zéphir network) was also present in the person of Romain Dandois, Marketing Manager.

This public information meeting enabled Padam Mobility to once again present its Demand-Responsive Transport solutions and in particular its optimization algorithms based on artificial intelligence and its user interfaces: application, booking website and call center. The meeting allowed to take stock of the level of deployment of Padam Mobility technology in France and abroad but also to answer questions from citizens on the La Saire TAD network, inaugurated in July 2019 for a first six-month experiment .

Find out more about Padam Mobility solutions

Learn more about the users of the La Saire TAD Demand-Responsive Transport

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How to build an efficient Demand Responsive Transport? The user experience 1/3

user experience

The success of a Demand Responsive Transport (DRT) service rely on several pillars. In this article, we will dive deeper regarding the user experience after a brief reminder of what  a dynamic Demand Responsive Transport is.

What are the contexts in which dynamic Demand Responsive Transport is being implemented?

Dynamic DRT complements the traditional public transports when the latter cannot meet the demand, such as paratransit, or in low density areas, or during off-peak hours (night transport for example) or the transport of employees. In addition, DRT can enhance transport in more or less densely populated areas with its first and last mile logic, by reducing the number of stops on existing networks. In this case, it supports public transport services without competing with existing fixed lines.

The user experience: a key condition for the success of Demand Responsive Transport

Target your users

“Who will use your DRT?” That’s the key question. User profiles are various and each has its own specificities. The success of a DRT network will depend on your target and its needs. For example, for a senior population, it would be wiser to provide a call centre to make reservations rather than a mobile application only, which is less suited to the use of elderly people.

User experience: take care of passenger informations

The second key point to consider is passenger information to ensure an optimal user experience.

Unlike conventional transportation, if there is no real-time passenger information, a dynamic DRT service cannot work. Punctuality and the ability to provide accurate departure and arrival times are important for users. Many channels are available to share passenger informations: SMS, emails or push notifications on smartphones.

In addition, since the rise of ridesharing apps, users can now rate their journeys. This allows operators to get a real-time indication about the quality of their DRT service and to quickly consider improvements.

If you offer a mobile app, it is important to think about the interface in terms of quality rather than quantity. An application with few but useful features is better than an app whose multitude of features will only confuse users.

User experience: Which payment methods?

The implementation of fast payment methods improves the user experience. For many transport operators, on-demand transport is integrated into the existing network. It is therefore relevant to propose a ticketing solution similar to the one used on the rest of the network.

A prepayment solution makes it possible to improve user loyalty. It allows an amount to be credited into the user’s account, which will be debited each time the service is used. Pre-payment solutions usually go along with promotional campaigns to stimulate the use of the service (e.g. pay for 10 journeys, be credited with 11).

Other payment methods exist but remain marginal due to the complexity of their logistics. This is the case of post-payment, which involves setting up a collection service, or instant payment, which is still very expensive since transaction costs are expensive compared to the small amounts paid.

 

Learn more: How to build an efficient Demand Responsive Transport? The service design 2/3

Access Padam Mobility’s Webinar replay: How to build an efficient Demand-Responsive Transport?

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Demand-Responsive Transport: Why aren’t they all equal? Reservation time limit and itinerary calculation

Demand-Responsive Transport parameters

Reservation time limit and itinerary calculation methods are important parameters for choosing a Demand-Responsive Transport (DRT) solution.

Reservation the day before or last minute

There are three main categories:

  1. DRT services requiring a reservation the day before. This time slot is often sufficient for people who use the service for commuting. However, it does not fit to other needs (shopping, leisure, etc.).
  2. DRT services with a 2 hours reservation time limit. Allowed by technical improvements but also and above all by compromises on other points. This delay is ultimately quite little different from the previous case in its advantages and drawbacks.
  3. DRT with real time reservation. Like Uber and Lyft, users can book their trip as late as they want. The DRT vehicle will pick them up as soon as possible. Real time reservations is a real plus. In Orléans, when real-time reservations were put in place, more than 30% of reservations were made last minute, resulting in a significant increase in traffic. In addition, some use cases are only possible if real time reservation is possible. For example, an airport DRT service. Indeed, with the plane delays and baggage claim time, users are never sure when they can be picked up.
Different methods of itinerary calculation

Some Demand-Responsive Transport operate following the “virtual line” service design. They operate like a conventional bus line, except that they only stop at requested stops. Simple to set up, the interest is also very limited. In fact, there is little optimization in terms of time or mileage since the itinerary remains unchanged. Also, they will not be able to cover a larger area than a conventional fixed line.

On the other hand, there are DRT solutions which make it possible to vary the itineraries according to user requests. They follow a “zonal” service design. In this case, operating optimizations are important.

Zonal Demand-Responsive Transport
  • Some “zonal” DRTs require human intervention. The transit operator receives indications allowing him to make an informed choice when he assigns a person to a bus. The trajectory is therefore made up by the human using the machine or by the machine using the human.
  • Other “zonal” DRT solutions build the itineraries using an algorithm once all the reservations have been filled in. This therefore requires stopping reservations before the start of the service (one night or half a day).
  • Finally, some solutions, based on artificial intelligence, are capable of creating itineraries as reservations are made. This allows in particular the real-time reservation like Padam Mobility solutions.

Under the name “Demand-Responsive Transport” there is therefore, on the one hand, a service which follows a predetermined line and, on the other hand, a service which is capable of optimizing itineraries in real time according to user requests. Not all solutions fit to all uses cases, and choosing the right tool is a crucial step for the success of a Demand-Responsive Transport service.

 

Read more about Padam Mobility Demand-Responsive Transport solutions

Read more about other parameters to keep in mind when choosing a Demand-Responsive Transport solution

 

 

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Why are the territories rushing to replace their demand-responsive transit systems?

demand-responsive transit

Because dynamic demand-responsive transit is to DRT what the smartphone is to the landline phone: a solution that makes its ancestor outdated, thanks the combination of technology and intelligence, in line with the changing uses.

A cheaper and more accessible shared mobility solution

Historically linked to senior public and mobility impaired people, demand-responsive transit is now opened to all audiences. Leisure, studies, shopping, employment… Suitable to all territories and scales, dynamic demand-responsive transit offers new opportunities for communities:

  • Flexible and intelligent, dynamic DRT ensures a significant decrease in operating costs and carbon footprint.
  • More accessible, it guarantees social inclusiveness by addressing the issues of precariousness-mobility, mainly in peri-urban and rural areas, while being compatible with the transport of mobility impaired people.
  • In sync with mobility innovations, it saves time for people.

Despite its many advantages, DRT suffers from the image of the aged demand-responsive transit solutions deployed decades ago: heavy in terms of investment, long to deploy and complex to operate.

Technological advances, particularly the optimization of journeys in real time thanks to artificial intelligence, make it an extremely easy mobility solution to implement.

Demand-responsive transit: a simple and fast solution to deploy

Nowadays, thanks to technological innovations, new turnkey solutions are being developed to answer more effectively the needs of territories and users.

Unlike other systems, SaaS demand-responsive transit solutions simplify service implementation and ease day-to-day network management:

  • No installation is required on the computers. The acquisition cost is significantly reduced, as well as the cost of maintenance and updates.
  • These solutions offer great freedom of use, since they can be accessed from any connected device.
  • The tools are hosted on secured servers: maintenance and service guarantee are greatly improved
  • The needs of the territory covered define the functionalities to which users have access.

In addition, SaaS demand-responsive transit solutions do not involve any disruption for end users. Indeed, these tools can coexist with older systems, such as reservation centrals that access reservation interfaces. Users may also prefer a mobile application to book their trips. As for drivers, they can follow in real time the evolution of their journey via the application.

To determine the outlines of the best offer to deploy, some solutions provide simulation tools to study a given territory beforehand: number of vehicles, number of stops, service models, etc…

Depending on the customization required, the deployment of a SaaS demand-responsive transit tool last from 1 to 3 months. The data collected during operation help to improve the service permanently and to study new approaches to evolve the demand-responsive transit network.

Ready to give up your wire? Find out about Padam Mobility’s on-demand transport solutions here.

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