Cost, Fuel, Emissions

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SIDRA INTERSECTION and SIDRA TRIP software for Operation Cost, Fuel Consumption and Emissions

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Two essential elements of good fuel consumption and emission modeling in relation to traffic management are:

  1. a good traffic model that has sensitivity to traffic characteristics (road geometry, traffic control type, demand volumes, driver behaviour, acceleration - deceleration and other vehicle characteristics), and 
  2. a good fuel consumption / emission model that has right sensitivities to vehicle parameters (fuel consumption and emission characteristics, mass, acceleration - deceleration characteristics, and so on) and at the same time is well integrated with the traffic model.

SIDRA INTERSECTION and SIDRA TRIP are two products that use different levels of model detail but both models are based on the same power-based model of vehicle fuel consumption and emissions. 

SIDRA INTERSECTION uses a four-mode elemental model for estimating fuel consumption, operating cost and pollutant emissions for all types of traffic facilities (roundabouts, actuated and pretimed/fixed-time signals, sign-controlled intersections, signalised pedestrian crossings).  This helps with estimation of air quality, energy and cost implications of alternative intersection design. 

SIDRA TRIP is a single-trip microsimulation model for assessment of road traffic conditions using in-traffic vehicle data or user-defined drive cycles.   It employs an instantaneous model to determine various trip characteristics for assessing traffic and travel level of service, performance (delay, speed, travel time), and provide estimates of fuel consumption, emissions, operating cost and user cost.

The four-mode elemental model used in SIDRA INTERSECTION is based on aggregation of the instantaneous model used in SIDRA TRIP.  For this purpose, a unique vehicle drive-cycle model (acceleration, deceleration, idling, cruise) is used. Drive cycles (consisting of driving "modes") are derived for each movement in each lane of traffic as a function of all traffic characteristics specific to each situation.  A "tractive power" (or "energy") based fuel consumption / emission model is used.  The model is one of a a range of models (simple to microscopic) developed in Australia during the energy crisis in 1980s. The models are based on our research work which won the Institute of Transportation Engineers (USA) 1986 Transportation Energy Conservation Award in Memory of Frederick A. Wagner for research into energy savings from urban traffic management.  This research benefited from working very closely with researchers from the automotive industry.

For each lane of traffic, SIDRA INTERSECTION constructs vehicle movements through the intersection as a series of cruise, acceleration, deceleration and idling elements (see below), distinguishing between stopped and unstopped vehicles as well as light and heavy vehicle characteristics.  Fuel consumption, cost and pollutant emissions are calculated for each of the four modes of driving, and the results are added together for the entire driving manoeuvre.  Detailed information about the SIDRA fuel consumption, operating cost and emission models is included in the SIDRA User Guide. Several publications on this topic are listed below (also see the Publications page).

In evaluating alternative intersection treatments, it is important to model different intersection types in a consistent way.  Model consistency for different intersection types is a unique strength of SIDRA INTERSECTION.

The four-mode elemental model is applied in SIDRA INTERSECTION as follows.

  • Traffic performance is different in each lane of traffic at intersections. Therefore, SIDRA calculates the fuel consumption, operating cost and pollutant emission estimates for each lane of traffic separately.
  • In each lane, the model is applied to queued and unqueued vehicles separately according to the proportion queued estimated by SIDRA. For unqueued vehicles, only the cruise and geometric stop components apply. For queued vehicles, SIDRA determines the "drive cycles" distinguishing between major stops, queue move-ups (stops in queue) and geometric stops (slow-down or full stop in the absence of any other vehicle). These drive cycles are very different for different intersection types (signalised, sign-controlled, roundabout), for different signal phasings (one or two green periods in the cycle), for yield and stop control, and for different congestion levels.
  • If the approach and exit section cruise speeds are different for unqueued through vehicles at traffic signals and priority movements at unsignalised intersections, they are considered to be subject to an acceleration or deceleration during their travel.
  • Drive cycles are defined by the initial and final speeds in each element of the driving manoeuvre. Approach and exit cruise speeds, intersection negotiation speeds and queue move-up speeds are used for this purpose. Some of these speeds are specified as input by the user, some are calculated by the program according to the intersection geometry and traffic congestion levels, and some default parameters are used where applicable.
  • The drive cycle information is used to calculate acceleration and deceleration times and distances for each element of the drive cycle individually. Effective cruise distance, cruise time and idling time are calculated using this information as well as traffic performance estimates (delay, number of stops). The drive cycle information is also used to calculate different delays (stopped delay, queuing delay, geometric delay, control delay, etc), which are reported to the user along with the proportion stopped (proportion queued for a more precise term), effective stop rate, queue move-up rate, etc.
  • The fuel consumption, emission rates and operating cost values are calculated for each element of the drive cycle individually using the statistics derived as explained above. The results are added together for the entire queued vehicle manoeuvre, and then the results for queued and unqueued vehicles are aggregated.
  • Fuel consumption and emission rates are calculated from a set of equations which use such vehicle parameters as mass and fuel / emission efficiency rates, as well as road grade and relevant speeds (cruise, initial, final).
  • In the above process, light and heavy vehicles are treated separately with different parameters (e.g. different mass, different acceleration and deceleration characteristics).

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Publications

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AKÇELIK, R., SMIT, R. BESLEY, M. (2014).  Recalibration of a vehicle power model for fuel and emission estimation and its effect on assessment of alternative intersection treatments. TRB 4th International Roundabout Conference, Seattle, WA, USA.
Available for download from Resources/Articles page.

 AKÇELIK, R., SMIT, R. BESLEY, M. (2012).  Calibrating fuel consumption and emission models for modern vehicles.  IPENZ Transportation Group Conference, Rotorua, New Zealand, 18-21 Mar 2012.
Available for download from Resources/Articles page.

AKÇELIK, R. and BESLEY, M. (2003).  Operating cost, fuel consumption, and emission models in SIDRA and aaMotion.  Paper presented at the 25th Conference of Australian Institutes of Transport Research (CAITR 2003), University of South Australia, Adelaide, Australia, 3-5 December 2003.
Available for download from Resources/Articles page.

BOWYER, D.P., AKÇELIK, R. and BIGGS, D.C. (1985). Guide to Fuel Consumption Analyses for Urban Traffic Management. Australian Road Research Board. Special Report SR No. 32. 
Available for download from Resources/Articles page.

AKÇELIK, R. (Ed.) (1983).  Progress in Fuel Consumption Modelling for Urban Traffic Management. Australian Road Research Board.  Research Report ARR No. 124. 
Available for download from Resources/Articles page.

AKÇELIK, R. and BIGGS, D.C. (1987). Acceleration profile models for vehicles in road traffic. Transportation Science, 21(1), pp. 36-54. 
Available for download from Resources/Articles page.

AKÇELIK, R. and BESLEY, M. (2001).  Acceleration and deceleration models.  Paper presented at the 23rd Conference of Australian Institutes of Transport Research (CAITR 2001), Monash University, Melbourne. Revised version. 
Available for download from Resources/Articles page.

AKÇELIK, R. (1981). Fuel efficiency and other objectives in traffic system management.  Traffic Engineering and Control, 22(2), pp 54-65.

LUK, J.Y.K. and AKÇELIK, R. (1983).  Predicting Area Traffic Control Performance with Transyt/8 and an Elemental Model of Fuel Consumption.  Australian Road Research Board.  Internal Report AIR 388-1.  (Also in: Proc. 12th ARRB Conf. 12(4), pp 87-101).

AKÇELIK, R. (1983).  Formulae for predicting fuel consumption of cars.  Traffic Engineering and Control 24(3), pp 115-118.

AKÇELIK, R., BAYLEY, C., BOWYER, D.P. and BIGGS, D.C. (1983).  A hierarchy of vehicle fuel consumption models.  Traffic Engineering Control, 24(10), pp 491-495.

AKÇELIK, R. and BIGGS, D.C. (1985).  A discussion on the paper on fuel consumption modelling by Post et al. Transportation Research 19B(6), pp 529-533.

BIGGS, D.C. and AKÇELIK, R. (1985).  Further work on modelling car fuel consumption.  Australian Road Research 15(1), pp 46-49.

AKÇELIK, R. (1985).  An interpretation of the parameters in the simple average travel speed model of fuel consumption. Australian Road Research 15(1), pp 46-49.

BIGGS, D.C. and AKÇELIK, R. (1986).  An energy-related model of instantaneous fuel consumption.  Traffic Engineering and Control, 27(6), pp 320-325.

AKÇELIK, R. (1986).  Models for estimation of car fuel consumption in urban traffic.  ITE Journal, 56(7), pp 29-32.

BOWYER, D.P., AKÇELIK, R. and BIGGS, D.C. (1986).  Fuel consumption analyses for urban traffic management.  ITE Journal, 56(12), pp 31-34.

BIGGS, D.C. and AKÇELIK, R. (1986).  Estimation of car fuel consumption in urban traffic.  Proc. 13th ARRB Conf. 13(7), pp 123-132.

AKÇELIK, R. (1986).  Discussion on the paper 'Estimating fuel consumption from engine size' by T.N. Lam.  Journal of Transportation Engineering, 113(1), pp 101-106.

AKÇELIK, R. (1989).  Efficiency and drag in the power-based model of fuel consumption.  Transportation Research 23B(5), pp 373-385.


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