Real-Time Traffic and Travel Information Systems - Role in Improving the Supply Chain Efficiency in Metropolitan Environment

Abstract

The economical efficiency of commercial companies located in dense metropolitan areas depends on many factors. Amongst these, transportation is one of the most unpredictable and time-consumer link of a supply chain. Many stakeholders depend on the effectiveness of the management in producing/obtaining freight, storing, supplying and/or delivering on-time all their products to the final user, or to their customers. The paper is focusing on the usability and the effects of employing real-time traffic and travel information systems (RTTIS) to help improve the efficiency in such management processes for supply chains. An analysis is made to estimate the impact in terms of time effectiveness, energy/fuel consumption reduction and a better fleet management. The study, based on an international research project, is offering solutions for a better integration of intelligent transport systems (ITS) in supply chain management. The authors believe that using RTTIS may improve the productivity associated with the transportation part of the supply chain. Operations such as: route guidance for supply vehicles, route / driver allocation, fuel management and vehicles maintenance can be shaped better to increase the productivity of a commercial company acting in dense urban environment, by beneficiating from a more efficient usage of traffic information.

Headnote

Abstract

The economical efficiency of commercial companies located in dense metropolitan areas depends on many factors. Amongst these, transportation is one of the most unpredictable and time-consumer link of a supply chain. Many stakeholders depend on the effectiveness of the management in producing/obtaining freight, storing, supplying and/or delivering on-time all their products to the final user, or to their customers.

The paper is focusing on the usability and the effects of employing real-time traffic and travel information systems (RTTIS) to help improve the efficiency in such management processes for supply chains. An analysis is made to estimate the impact in terms of time effectiveness, energy/fuel consumption reduction and a better fleet management. The study, based on an international research project, is offering solutions for a better integration of intelligent transport systems (ITS) in supply chain management.

The authors believe that using RTTIS may improve the productivity associated with the transportation part of the supply chain. Operations such as: route guidance for supply vehicles, route / driver allocation, fuel management and vehicles maintenance can be shaped better to increase the productivity of a commercial company acting in dense urban environment, by beneficiating from a more efficient usage of traffic information.

Keywords: real-time traffic and travel information systems, time efficiency, fuel consumption reduction, fleet management, maintenance scheduling

JEL Classification: R42

1. Introduction

Transports are one of the most important building blocks of an economy. Unfortunately, one of the most developed and employed mode of transportation, the road vehicle, is also a source of environmental pollution and, if the road infrastructure is not adapted to the traffic request, also a source of stress and delays. This causes, worldwide, the most adverse aspect of the road transportation: traffic accidents, with casualties and material losses.

In line with transportation, the energy consumption is nowadays one of the major concerns of all industry stakeholders and/or competent authorities. There are several specific directions that the research activities are carried on: inducing a different traffic behavior to the traffic participants via mobile information services, with the purpose of improving the supply chain efficiency, in case of stakeholders, reducing the environmental pollution [Cambridge Systematics, 2008], and implementing less energy consuming technologies for the traffic signaling. In the general concept of a supply chain, several information components are required:

- Which is the best route between origin O and destination D, considering many points of view: traveling on a route with less traffic congestions, shortest path, less consumption of energy, accepted vehicle weights etc.

- Which of the intermediate points of interest can be included on the route, with an optimization of time and distance consumed?

- How can the information regarding possible route obstructions, traffic incidents or congestion be included and transmitted in real-time onboard the vehicle, so it can automatically change its route in case of necessity;

- How can one scope with emergency situations, if any, in an automatically mode, so the rapid recovery is achieved in the shortest time possible, reducing negative effects, both in material losses and human injuries?

In Figure 1 above, the vehicles have onboard equipment capable of receiving actuated road and traffic information, thus helping them in re-routing if necessary. By introducing specific information, such systems may be able to induce a specific traffic behavior, beneficial both for supply chain efficiency or environmental impact.

A simple step on reducing the environmental impact and improve traffic signing visibility was to employ LED1 traffic signals. Based on past experiences and current statistics, an estimate energy saving impact of the measures proposed was estimated at:

- Modal shifting away from individual traffic: around 3%;

- Employment of modern traffic management equipment: larger than 50%

- Improvement of supply chain efficiency: better than 15%.

These percentages are expected to be achieved by optimizing traffic control (the so-called eco-flowing), by enhancing the product life-cycle, and by reducing power consumption of the signaling infrastructure, employing LED technologies. The main power consumers in such an installation are the traffic lights, with an amount of over 90% of intersection power consumption. In Bucharest, in 2007, the installation of a new traffic control system was announced, the Bucharest Traffic Management System beginning to be operational by 2008. Today, the system manages a network of more than 120 junctions, all equipped with LED traffic lights, traffic sensors, CCTV1 cameras and FO2 communications network. Switching to LED traffic signaling is already improving the energy savings, as the system will extend on all the signalized junctions in Bucharest.

2. Importance of real-time traffic and travel information in supply chain efficiency and environmental impact

Road traffic is the less controlled mode of transportation, compared, for example, with the rail traffic. Significant economical losses are recorded annually due to traffic congestions, incidents and vehicles' delays. The European Commission recently adopted a roadmap of 40 concrete initiatives for the next decade to build a competitive transport system that will increase mobility, remove major barriers in key areas and fuel growth and employment. At the same time, the proposals hope to dramatically reduce Europe's dependence on imported oil and cut carbon emissions in transport by 60% by 2050.

It is also estimated that, by 2050, the key goals will include:

- No more conventionally-fuelled cars in cities;

- 40% use of sustainable low carbon fuels in aviation;

- At least 40% cut in shipping emissions;

- A 50% shift of medium distance intercity passenger and freight journeys from road to rail and waterborne transport;

- All of which will contribute to a 60% cut in transport emissions by the middle of the century.

The Intelligent Transportation Systems (ITS) and their components intensify the efforts to add information and communication technologies (ICT) to both infrastructure and mobile platforms, in a sustained effort to manage factors that typically are at odds with each other, such as vehicles, loads and infrastructure, to help improving safety and reduce vehicle wear, trip durations, fuel consumption and emissions.

These telematic technologies involve wireless communications, computational technologies, vehicle flowing data, sensing technologies, specific software, cooperative systems and information delivery procedures and systems. Information is a key factor which, when used correctly and delivered to the traffic participants, can significantly improve the traffic safety and environmental impact reduction. In fact, the increasing interest in ITS comes from the problems caused by traffic congestion and a synergy of new information technology for simulation, real-time control, and communications networks.

Previous European research projects, such as e-MOTION1, Kite2, LINK3 etc. have discovered the most relevant factors that an MRTTI system developer should take into account.

Enhanced inter-modality in passenger transport is one key to a higher efficiency of the transport system, it improves the ease of travelling for the travellers and minimises impacts on side of the environment. The mobility trends and forecasts like the growth of long distance travel and air traffic or partially a loss of significance of rail and local public transport would increase the imbalance of more sustainable modes.

3. The concept of the system and services

The idea of the MRTTI integrated platform is to collect static/dynamic information from different sources related to traffic and travel, infrastructure, weather and modes of transport, to convert it into a common agreed format, to process the information for efficient management and to deliver it to the final users. There are two types of information exchanges in this process: a business-to-business exchange, where relevant traffic information service providers collect and deliver information to/from competent authorities and stakeholders, and the business-to-user service, that deliver information for multimodal travel planning service, either on fixed devices (PCs) or on mobile ones. The "pre-trip data" can be delivered via a multi-functional application, which can offer public transport, parking, weather, traffic and routing information. This may be used before the user starts the trip. The "on-trip data" is available via mobile Internet access on PDAs or smart phones with GPS, being able to offer multimodal routing dynamic information, helping the traveller to better manage the route, to avoid congestions, to reduce fuel consumption and thus, emissions. By constantly using these types of applications, it is expected that the effect in the near future will be the modal shifting of the single travellers, who will prefer travelling based on a constant level of information delivered on route, avoiding stress and optimising the trip.

The central part of the service concept is an interoperable and multimodal Regional Data/Service Server (RDSS) which can be seen as a service-oriented middleware infrastructure (Figure 2), providing a number of data/services, covering:

- Individual traffic and travel;

- Public transport;

- Weather;

- Location based services;

- Intermodal transport/trip planning;

- Enabling the operation of the multi-modal real-time travel planning services.

This system is required to ensure interfacing with different information systems, collection, processing and effective transport of data to final, either mobile or fixed users. Due to the fact that, at the present moment, there are no standardised interfaces to traffic and travel information systems or local relevant authorities (such as Traffic Control Centres, Road Police, parking management, weather information providers, ports, airports or railway operators etc.), the mobile real-time traffic and travel information1 platform had to face a consistent challenge of how to unify the formats and contents of relevant information from these various sources.

Requirements related to mobile real time travel and traffic information services have been identified on the basis of previous research projects at the European level, mentioned before and were grouped in several categories, that helped the design of the system architecture, presented in Figure 3 above. The goal of this application is to deliver competent and trustful information to the final mobile user, in order to increase the usage of the services, thus influencing the behavior of the travelers and traffic participants in a positive way for the supply chain efficiency and environmental impact.

The architecture of the system tested in Bucharest and other European cities is presented below.

4. Traffic Congestion Effects on Supply Chains

Traffic congestion has been defined as "a condition of traffic delay (i.e., when traffic flow is slowed below reasonable speeds) because the number of vehicles trying to use a road exceeds the design capacity of the traffic network to handle it." (Weisbrod et al., 2001). Most transportation literature and transportation impact models treat congestion as a cost factor, comprised of time delay and operating expense (Cambridge Systematics, 2008; Short et al., 2010). However, a premium is often added in recognition of the variability aspect of congestion delay that is masked by focusing just on average delay statistics.

A separate line of research studies on supply chain behavior have used systems dynamics models to show how traffic congestion can change the optimal decisions of producers, distributors and retailers along a supply chain. The most basic impact is that congestion delay and uncertainty increases requirements for (and hence costs of) product inventory (Disney et al., 1997; Mason-Jones et al., 1997). That, in turn, can affect supply chain behavior by encouraging shipment of smaller lot sizes to reduce cost risk (e.g., Moinzadeh et al., 1997).

Traffic congestion is determined by its composition (Transport distinctive and service vehicles impact the supply chain), during the day and the spatial pattern of congestion, and has effects on intermodal connectivity. There are several key reasons:

- Time Periods - Congestion can affect both truck and service delivery travel at specific times of day. For industries that are most affected by congestion delays and schedule unreliability, there are important differences in the extent of their options to modify work shifts and delivery schedules.

- Spatial Patterns of Congestion - For industries that are most dependent on closely integrated logistics, congestion can affect deployment and use of truck fleets, and that can lead to subsequent changes in the number, location and dispersion of manufacturing and distribution facilities.

- Intermodal Linkages - Ultimately, every change in congestion along a segment of the road network is likely to affect access from some areas to airports, marine ports or rail intermodal facilities. Conversely, every change affecting the activity at an airport, marine port or railroad facility is likely to also affect traffic levels on its access routes.

By Eilon et al. (1971) refers to the results: The average value of the number of customers on any one route (C) critically affects the length of vehicle routes, Do (the total distance of the routes) has a very well-defined relationship with Dr (the sum of the radial distances between the depot and customers) and C.

Do = 1.1sqrt(L*Dr) +1.8Dr/C (1)

The relationship does not greatly depend on depot location.

5. Conclusion

In examining a range of congestion impacts on supply chains and related business activity, several conclusions arise. First, it is clear that supply chain simulation models based on systems dynamics can be useful to illustrate why congestion delays and uncertainty lead businesses to shift schedules, delivery lot sizes and sometimes even locations.

Congestion impacts can go far beyond mere changes in operating cost, to also affect the size and nature of business organizations, production processes and customer markets served. And businesses can have a wide range of responses, depending on the type of affected business activity and the nature of congestion growth. They can be important to consider in planning processes, policy development and economic impact analysis models.

There are some situations where the economic impacts of traffic congestion can be less than expected because businesses adjust their operations to help mitigate congestion costs. However, in other situations, the economic impacts of traffic congestion can be greater than expected because of additional impacts on workers and on operators of other transport modes. In addition, there are effects on land use and business location patterns - all of which are unaddressed by models that assess the direct cost impacts of delivery delay.

Many of these additional elements of economic impact take place slowly over time and may not be noticed until their consequences are severe (i.e., entire business operations are rescheduled, reconfigured or relocated), at which time it may be too late to reverse business decisions.

Footnote

1 Light Emitting Diode

1 Close Circuit TeleVision

2 Fiber Optic

1 eMotion - Europe-wide multi-Modal On-Trip Traffic Information, http://www.austriatech. at/index.php?id=516&L=1

2 Kite - a Knowledge Base for Intermodal Passenger Travel in Europe, http://www.transport- research.info/web/projects

3 LINK - the European Forum on Intermodal Passenger Travel - a project which is funded by the European Commission (DG Energy and Transport within the 6. Framework Programme) for 3 years and has been launched in April 2007

1 Also known by the acronym MRTTI - Mobile Real-Time Traffic and travel Information

References

References

Cambridge Systematics, Cambridge Systematics (2008) Estimated Cost of Freight Involved in Highway Bottlenecks. Federal Highway Administration, Washington, DC, USA.

Disney, S., et al. (1997) Dynamic Simulation Modelling for Lean Logistics, International Journal of Physical Distribution and Logistics Management, Vol. 20, No.3-4, pp 194-196.

Mason-Jones, R., et al (1997). The Impact of Pipeline Control on Supply Chain Dynamics, International Journal of Logistics Management, Vol.8, No.2, pp 47-61.

Moinzadeh, K., Klastorin, T. & Emre, B. (1997). The Impact of Small Lot Ordering on Traffic Congestion in a Physical Distribution System, IIE Transactions, Vol.29, p. 671-679.

Short, J., Trego, T. & White, R. (2010). Developing a Methodology for Deriving Cost Impacts to the Trucking Industry that Generate from Freight Bottlenecks, Transportation Research Record, Vol.2168, pp.89-03.

Weisbrod, G., Vary, D. & Treyz, G. (2003). Measuring Economic Costs of Urban Traffic Congestion to Business, Transportation Research Record, No.1839. www.intechopen.com