Impacts Resulting from Optimised Service and Infrastructure Management with ITS

The increased intensity of ICT solutions on the transport system in the COMPASS scenarios results on the road modal share increasing from 69.8% in the Baseline to 71.2% in the very high ICT scenario.

The reason behind this increase is the higher decrease in the cost of interconnections involving the road, as the decrease in travel costs and fees is assumed to be the same for all modes simultaneously. Higher performing interconnections between the road mode and all others imply allowing easier access to the road mode. This fact, in combination with a relatively high increase in speed makes roads more competitive, gaining modal share.

The improvement of road interconnections with other transport modes is mostly related to the decreasing congestion levels of metropolitan motorways, represented in COMPASS by city to road, rail to road and air to road connectors. This can be achieved via a number of different ITS solutions

FINAL RESULTS AND CONCLUSIONS

active hard-shoulder management, or ramp meters in accesses (infrastructure management dimension). It can also be addressed with smarter on-board route assistants for vehicles that consider real-time congestion on the network, advanced driver assistance systems (ADAS) that allow for more stable traffic flows, or with traffic jam assistants that allow quicker dilution of congestion waves (service management dimension).

Figure 9-9-1 Modal Split variation between COMPASS scenarios. Scenarios impacting on service and infrastructure management

Rail modal share decreases initially but then recovers between mid and high/very high ICT scenarios It is observed that while the rail modal share decreases from 6.2% to 5.8% between the baseline scenario and the mid ICT Scenario, it is then able to recover its initial share of 6.2% between the mid

ICT Scenario and the very high ICT Scenario.

The reason behind this behaviour is the different speed increases on each of the transport modes in the long-distance segments of the network (e.g. in the HSR, motorways, air flights and ferries). Whereas between the baseline and the mid ICT scenario, the road mode increases network speed on

a 2.5% and the air mode in 5.0%, the rail mode is assumed not to increase. Then, between the mid

ICT and the high ICT Scenarios, the rail mode begins increasing speed, up to 5% in the mid ICT

scenario (7.5% for road and 10% for air) and 10% in the very high ICT Scenario (12.5% for road and 15% for air).

When rail gains operational speed, it also gains competitiveness against other modes in a much faster proportion, allowing it to recover initial modal share. The air mode, by comparison, is not able to materialise the greater increase in average operational speeds, and keeps losing modal share from 23.0% in the baseline to 22.7% in the mid ICT scenario to 21.8% in the very high ICT scenario.

The speed increases in the air mode are assumed to derive from more direct routing of flights facilitated by more integrated air space management (already tested by EUROCONTROL’s FRAM pilot initiative above the skies of Maastricht); it is also assumed that planes can fly closer to each other due to more accurate radars (satellite based ADS-B successor to radar); and that take-off and landings are faster at airports as surface movements become optimally managed with new initiatives such as A-SMGCS. Ensuring better punctuality of flights allows for faster terminal transits during ‘plane connections, which can be reduced from 90 to 30 minutes (according to ACARE’s “Flightpath 2050” the goal is to reach that all flights arrive within 1 minute of the planned arrival time regardless of weather conditions).

Speed increases in the rail and road modes derive from technologies ensuring safety at higher speeds. In the case of rail, ERTMS is to allow for greater operating speeds (as trains are able to

69,8% 70,5% 70,9% 71,2% 6,2% 5,8% 6,0% 6,2% 23,0% 22,7% 22,2% 21,8% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Baseline2030 Results fo r EU27 scenario Mid ICT Operato rs

Results for EU27 scenario High ICT Operato rs

Results for EU27 scenario Very High ICT Operators

Modal split

FINAL RESULTS AND CONCLUSIONS

autonomously regulate operating speeds and automatically break in case of emergency with lower reaction times) and services can operate closer to each other (more service frequencies in busiest corridors). For cars, many devices aimed at increasingly autonomous driving regimes (e.g. ADAS, car platooning like in SARTRE, robotically driven cars such as Audi’s TT trial or Google’s) allow for increased driving speeds at motorways without compromising safety, vehicle-to-vehicle communications on VANET platforms (Vehicular Ad-hoc NETworks) allow anticipation of incidents on the road before vehicles reach hot spots, or even vehicle-to-infrastructure communications allow for vehicles anticipating bad road conditions or eventual traffic speed restrictions.

More vehicles on the network, more emissions and fuel consumption, but less overall network usage in passenger kilometres and particulates

The increase in use of road mode results in up to 1.8% increase in the number of vehicles in the network. This seems contrary to the fact that passenger-kilometres decrease a little, but is explained due to the modal shift from air, rail and maritime to the road, as these modes use high occupancy vehicles and a large number of cars are needed to substitute them.

Road vehicle kilometres increasing implies an overall increase in fuel consumption, up to 4.5% respect to baseline, and CO2 emissions, up to 4.3%. The increase in road is greater than the decrease in air and maritime fuel consumption (under the hypothesis that engine efficiencies are not relatively altered between scenarios and modes). Vehicle kilometres increase in the road mode are driven by the attraction of passengers in a mode where vehicles have less capacity (road is less occupancy- efficiency). Also, speed increases on the road, air and maritime modes increase the overall levels of fuel consumption.

An overall decrease on particulates emissions is registered simultaneously, up to almost 7%, due mainly to reduction of maritime and air traffic. These modes are the highest particulate emitters.

Despite the fact of having more vehicles on the network and greater volumes of vehicle kilometres, there is a total decrease of -0.25% passenger kilometres for higher ICT Scenarios. This suggests that moving traffic from air and rail modes to the road results in slightly shorter trips per passenger, even though transport is less efficient as it moves fewer passengers per vehicle on average.

Figure 9-2 CO2 emissions: different ICT Scenarios impacting on service and infrastructure management 0,0% 0,5% 1,0% 1,5% 2,0% 2,5% 3,0% 3,5% 4,0% 4,5% -2 -1 0 1 2 3 4 5 6

Results for EU27 scenario Mid ICT Operators

Results f or EU27 scenario High ICT Operators

Results f or EU27 scenario Very High ICT Operators

CO2 (Mtons)

FINAL RESULTS AND CONCLUSIONS

9.2.2 Impacts Resulting from Changing Travellers Behaviour and Perceptions of Travel Time Cost