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Driving advice systems are on-board tools giving recommendations to drivers for a more energy efficient driving style. In main line operation, rather sophisticated algorithms taking into account a number of track and vehicle characteristics exist to continuously calculate the optimum driving pattern for the remaining route. |
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Technology field: Energy efficient driving |
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General information | ||||
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Description | ||
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(no details available) | ||
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General criteria | ||||
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Status of development: test series | ||
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Various European railways have tested driving advice systems.
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Time horizon for broad application: 5 - 10 years | ||
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(no details available) | ||
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Expected technological development: highly dynamic | ||
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Systemic optimisation Future driving advice systems could integrate a link to the control centre and thus take into consideration unscheduled stops arising from the traffic situation. This would require some communication channel between the DAS and the control centre as well as a corresponding IT support at the control centre. Extended functionalities Future driving advice systems could go far beyond giving driving recommendations and offer a wide range of functionalities such as monitoring for maintenance processes and accident investigation etc. |
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Motivation: | |||
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Energy saving. | ||
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Benefits (other than environmental): big | ||
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Punctuality In-service testing in different systems have shown clear improvements in punctuality. Capacity DAS could help drivers to stay inside their infrastructure slot at all times. This would improve slot management and thus increase capacity. Wear Coasting instead of braking reduces the wear of the brakes especially if electric braking is not possible. Passenger comfort Small improvements in passenger comfort can be achieved through smoother driving. In addition, early train arrival often leading to trains waiting outside stations (a situation hardly comprehensible for passengers) is ruled out by DAS. |
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Barriers: medium | ||
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Availability of digital infrastructure data For a system-wide introduction of DAS-based energy efficient driving, infrastructure data have to be supplied in a digital form, containing the exact position of stops, junctions, curves and curve radii, slopes etc. In most railway companies these data are only available on paper. Digital version may be obtained by different methods:
The digitalisation of infrastructure data is one of the principal bottlenecks for the implementation of DAS systems in countries with a big railway network. In smaller railways like SBB, a manual route-by-route approach is feasible. Updating of track information For the effectiveness and reliability of DAS recommendations, up-to-date information on track conditions are crucial. If static track and timetable information is used, temporary low-speed sections are not taken into consideration and may lead to DAS causing additional delays. Dynamic information could be supplied via an automatic update at stations (e.g. by a W-LAN link) or via continuous updating by GSM (or other). At DB AG it is planned to make use of the new electronic timetable method (EBuLa) as a data basis for the driving advice system ESF (cf. Example). Acceptance by drivers and management Some drivers will be reluctant to follow the recommendations of a DAS for several reasons:
Some decision makers think that acceptance by drivers puts too much uncertainty to the effectiveness and thus payback of the system. Delayed trains The effectiveness of the system is reduced if train punctuality in the network is low, since the DAS has no effect in this case. Unexpected stops If unexpected stops due to red signals occur on the trip, the DAS can no longer operate or may even lead to additional delays. This cannot be avoided even by up-to-date track data, but would require a permanent link to the control centre being a future upgrade of DAS. Computing power DAS being a real-time-application, limitations of computing power installed on-board may pose a problem in some cases. |
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Success factors: | |||
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Time buffers A pre-condition for the use of DAS is the existence of time buffers in the timetable. The saving effect of DAS is the higher, the bigger these time buffers are. Winning drivers’ acceptance
Integration into existing ICT infrastructure When developing or introducing a DAS, synergy effects with existing hardware platforms as well as positioning and data supply systems should be sought in order to reduce costs and overall system complexity. International standard An international standard for DAS could create scale effects for the development and introduction of such systems. Furthermore, synergy effects with other international systems such as ETCS can be ensured at an early stage. A UIC project aiming at the definition of standard requirements for energy meters and DAS was finalised in 2002. |
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Applicability for railway segments: high | ||
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Type of traction: electric - DC, electric - AC, diesel | |||
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Type of transportation: passenger - main lines, passenger - high speed, passenger - regional lines | |||
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The present evaluation focuses on driving advice systems in main line operation. For application of DAS in other fields, cf. DAS for suburban operation and DAS for freight operation. | ||
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Grade of diffusion into railway markets: | |||
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Diffusion into relevant segment of fleet: < 5% | ||
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Share of newly purchased stock: < 20% | ||
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Application is presently limited to pilot projects. | ||
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Market potential (railways): high | ||
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In long term perspective, the market for DAS in main line operation is very high. However, the experience from DB AG or NS Reizigers show that there are many hurdles on the way to a system-wide rollout. | ||
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Example: | |||
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German driving advice system ESF In co-operation with Hannover University, German DB AG developed a driving advice system called ESF (Energiesparende Fahrweise). The system gives coasting advices based on track and train data, timetable, position and time. Continuous speed optimisation could also be given by ESF but is presently not activated. The savings to be realised strongly depend on timetable, operational situation and degree of energy efficient driving previously realised by drivers’ skill. An average saving potential of over 5 % on German ICE has been confirmed by tests and calculations. A pilot on ICE 1 and 2 was realised in 2001. At the end of 2002 ESF is planned to start in all ICEs running on lines where the new electronic timetable method EbuLA has been successfully implemented. Exact structure data of the entire network is needed in a reliable and convenient digital version in order to successfully run both EbuLa and ESF. This is the main reason for these systems being restricted to only part of the network in the initial phase. |
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Environmental criteria | ||||
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Impacts on energy efficiency: | ||
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Energy efficiency potential for single vehicle: 5 - 10% | ||
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Energy efficiency potential throughout fleet: 2 - 5% | ||
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Comparing a DAS guided driving strategy with a shortest time driving strategy one gets the theoretical saving potential. For typical time buffers and running patterns, it lies over 20 % in main line operation. The real saving potential is however considerably lower, for three reasons:
Taking these factors into account, the remaining potential in main line transport lies between 5 and 10%. In individual favourable situations this value can even reach 15%. ESF test runs at DB AG Simulations and test runs with ESF on the ICE at DB AG yielded the following results:
Economymeter test runs at NS Reizigers In-service testing during two years in the Netherlands has yielded an overall reduction of 6 7 %. The reason for this value which is much lower than the theoretical potential are delayed trains and drivers ignoring the driving recommendations. |
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Other environmental impacts: neutral | ||
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(no details available) | ||
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Economic criteria | ||||
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Vehicle - fix costs: low | ||
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The on-board hardware is generally cheap, especially if synergy effects with existing hardware (display etc) are used. Main cost factors are the digitalisation of track data and the software development. | ||
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Vehicle - running costs: significant reduction | ||
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If an automated and radio based data supply and updating is in place, additional operating costs are almost negligible. | ||
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Infrastructure - fix costs: low | ||
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There are generally no major infrastructure measures needed. However, a data supply infrastructure to update on-board data is required. | ||
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Infrastructure - running costs: unchanged | ||
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(no details available) | ||
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Scale effects: low | ||
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(no details available) | ||
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Amortisation: 2 - 5 years | ||
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(no details available) | ||
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Application outside railway sector (this technology is railway specific) | ||||
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Overall rating | ||||
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Overall potential: very promising | ||
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Time horizon: mid-term | ||
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Driving advice systems for main line operation exist and have proven to be operable in in-service testing in several countries. Energy savings are lower than theoretically predicted but still high. Many operators are currently considering a system-wide introduction. The main technical barrier is the compilation of digital track data. Other obstacles are scepticism about the effectiveness and payback of the system as well as uncertainties about the acceptance by drivers. In view of the fact that DAS are among the most effective technological measures to reduce the fleet-wide energy consumption in mid-term perspective, strong efforts should be made to overcome remaining barriers. In long-term perspective, the integration of traffic situation into DAS algorithms could yield further efficiency gains. |
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References / Links: Sanftleben et al. 2001; Voß, Sanftleben 1998; Linder 2000; Meyer et al. 2002 |
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Attachments: |
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Related projects: Economy Meter; Ecodriving; ESF |
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Contact persons: |
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© UIC - International Union of Railways 2003 |