Impacts on Transport Operation Efficiency

In document DANGEROUS GOODS TRANSPORTATION: A (Page 115-120)

5 System Impact Assessment Study: Indicative Results

5.2 Insight in System Expected Impacts

5.2.2 Impacts on Transport Operation Efficiency

5.2.2.1 Impacts on own Transport Operation

In the context of a socioeconomic analysis conducted (Landwehr, Krietsch et al., 2009), there were three alternative routes compared in terms of distance, travel time, cost and risk, namely the minimum cost route, the minimum risk route and the combined route minimising at the same time cost and risk.

Thus, for the sake of the study, the developed DSS simulator provided for the same transport request the following alternatives:

i) the minimum economic cost route, ii) the minimum (safety) risk route or iii) the minimum combined cost route.

The impact of each of the aforementioned routes had on the route length, the route duration, the overall economic cost and the overall risk of the route was examined.

In the table below, we can see the total distance, travel time, economic cost and risk for each of the three routes, as well as the deviation of those values when compared with the corresponding values of the first route (minimum economic cost route).

Table 5.1: Total distance, travel time, economic cost and risk for three alternative routes11.

Mimimum

Cost Minimum Risk Deviation Combined Minimum Cost Deviation Distance 53.84 96.449 79.14% 57.07 6.01% Travel Time 1:46:59 2:17:29 28.51% 1:52:32 5.19% Cost 36.21 58.629746 61.91% 37.95 4.81% Risk 49.02 10.061643 -79.48% 15.86 -67.65% 11

Minimum cost is expressed in km and cost in €. Risk is dimensionless (0-100 or 0-1 if normalised).

Hellenic Institute of Transport / Centre for Research & Technology Hellas 94 In the case of the minimum risk route, the overall distance and the total economic cost are greatly increased (79.14% and 61.91%), while the total risk is almost equally decreased (79.48%). The travel time is also increased (28.51%) but not so much as the aforementioned values. Thus, the minimum risk route achieves the minimisation of the risk with the price of an equally big increment of the cost.

In the case of the minimum combined cost route, however, we experience a similarly big reduction of the total risk (67.65) with only a slight increment of the overall distance (6.01%), travel time (5.19%) and economic cost (4.81).

Therefore, we conclude that the combined route, which minimises cost and risk in the best possible way in each case and which is the one that the system has been based upon, is the optimal one, when we take into account the overall risk as well as the business needs. It is also easier to be adopted by the interested parties than the more costly minimum risk route.

In addition to the above, another analysis was also conducted, in order to assess the impacts when a DG vehicle is not allowed to pass through a restricted tunnel, while those restrictions wouldn’t apply to a similar DG vehicle that makes use of the system (passport functionality).

As has been aforementioned, nowadays, most DGV’s are not allowed to pass through sensitive parts of the infrastructure, such as tunnels and bridges. In those cases, they are forced to follow big deviations, greatly increasing the cost of route, pollution and maybe even the overall risk. The system adoption allows the passage of equipped vehicles through special infrastructures. These two cases have been compared in terms of the total distance, travel time, economic cost and risk of each of the two alternative routes.

In the study example, two DGVs carrying ammonia start their journey at the same time. The first one does not use the system, while the second does. The equipped DGV is allowed to pass through the Gotthard Tunnel (test site of GOOD ROUTE used as a case study here), while the other one is not.

Hellenic Institute of Transport / Centre for Research & Technology Hellas 95 The minimum cost route of the non-equipped DGV was compared to the minimum combined cost route of the equipped DGV. Due to the area being underpopulated, the two routes differed only in the restricted tunnel, which is part of the latter only, while the former follows a deviation around it.

In the table below, we can see the total distance, travel time, economic cost and risk of each of the two routes, as well as the deviation of those values when compared with the corresponding values of the first route (minimum combined cost route of the equipped DGV).

Table 5.2: Total distance, travel time, economic cost and risk for equipped and non-equipped DGV (allowed/not allowed to pass through the

infrastructure)

Source: Landwehr, Krietsch et al., 200912. Equipped DGV equipped Non- DGV Deviation Distance 44.28 56.94 28.58% Travel Time 0:50:58 1:24:29 65.76% Cost 26.39 37.13 40.64% Risk 0.21 0.62 189.49%

It is obvious that the deviation which the non-equipped DGV is forced to follow has a very negative impact to all the observed values. The distance increases by 28.58%, the travel time by 65.76%, the total economic cost by 40.64% and the total risk by 189.49%. From the above, we conclude that the use of the system cannot only reduce the overall risk, but the total economic cost as well, when sensitive parts of the infrastructure are concerned.

Finally, according to the socioeconomic study held (Landwehr, Krietsch et al., 2009), on one hand, the system itself takes a minimum investment of 2.66 Mio. € for one year operation in one site. Within a time horizon of five years, the system costs reach a total of +27 Mio. € for one site. The main reason for this economic fact is the massive investment and operational cost related to the OBUs of the DG vehicle fleet, which can be hardly justified for a single infrastructure object (one site).

12 Minimum cost is expressed in km and cost in €. Risk is dimensionless (0-100 or 0-1 if

Hellenic Institute of Transport / Centre for Research & Technology Hellas 96 Thus, although even one site can be theoretically operated with overall benefits under certain assumptions, nevertheless, it is recommended, for both economic and safety reasons, that the system is being introduced for all/most critical infrastructures in a region (at least two sites).

Finally, as made evident from the analysis of the technical validation, the system does not create any additional delays in the transport pre-trip and on-trip phases. The operation time between the Control Centre and the DSS, which encompasses both the communication time and the processing time of the DSS and the Control Centre is negligible, while the DSS does not also seem to affect at all the overall time required for the accomplishment of the routing/re-routing scenarios (in comparison to the existing route guidance systems), although one should take into consideration the fact that the DSS is still a prototype, which by default does not incorporate all those, frequently “heavy” features, that a commercial product does.

As also shown from the Pilots, efficient enforcement is also enabled through the system. Nowadays, several dangerous goods vehicles pass through a toll station of a highway, soon after which a long bridge or tunnel starts. The vehicles either pass through the bridge/tunnel or are sent by a RO-RO ferry to the other side, loosing far too much time. If the police decides to make checks, it needs to stop all heavy trucks, to check their speed (through the speedometer on-board) and pass them through a specific infrastructure to measure the load per axle. It should also check the type of load carried, etc. The overall check time per vehicle is 10-30 minutes, while the expected rate of rules violation is roughly 7-10%. The technical validation results showed that for the accomplishment of the enforcement task (where both the driver and the respective enforcement units are being notified) less than 1.5 minutes are required (mean value according to the test results) for all vehicles in the area. This reveals the great economic, traffic efficiency but also safety impact the system enforcement could bring about. Time delays related to enforcement are minimised, automation inevitably prevents from unnoticed violations, which could result in great safety risks, whereas the enforcement personnel effort is minimised.

Hellenic Institute of Transport / Centre for Research & Technology Hellas 97

5.2.2.2 Impacts on Other Road Users

In addition to the above work, the impact of the Dangerous Goods Vehicles traffic on other road users was also investigated, through another impact assessment study.

The minimum risk methodology gave as a result the DGV paths that minimize the environmental and human risks, without taking into consideration the traffic conditions of the network and the problems that this volume may add. The road users’ impact analysis added the parameter of traffic volume restrains in the above methodology. To succeed that, the network and its conditions were simulated and running the traffic assignment procedure, different minimum time paths were resulted.

These paths were compared with the minimum risk ones and data such as the volumes of the network, while the travel time and the v/c were also analyzed. Furthermore a conflict resolution methodology was simulated giving optimized paths for the DGV volumes. In depth analysis of the above results was developed. The main results from the analysis are the following (Kauber, Emmanouilidis et al., 2009):

 The routing of DGV based on shortest time & distance paths and traffic conditions gives longer distance paths but utilises higher capacity and free capacity links of the network.

 The minimum risk routing methodology results to paths that utilise congested links (minor free capacity) of high hierarchy since the avoidance of dense population areas is dominant criterion for route selection.

 Negative impact to the traffic conditions in the links involved to the minimum risk route and therefore negative impact to the other users of the road network.

 Reduction of vehicle kms for the examined area (by 33%).  Reduction of average speed for auto vehicles (by 14%).  Increase of V/C ratio for the specific utilized links (by 24%).  The conflict resolution approach seems to result to better traffic

conditions for the DGV and the other users of the network and decreases negative impacts.

 A more in depth analysis in the way that the heavy vehicle volumes should be assigned in the network must be implemented according to the methodology followed. The final methodology should take into account the safety parameters but also the network conditions, the capacity of the roads, the

Hellenic Institute of Transport / Centre for Research & Technology Hellas 98 equable assigned of the volume and the minor extension of the travel time.

In document DANGEROUS GOODS TRANSPORTATION: A (Page 115-120)