Generating Emissions Information for Route Selection: Experimental Monitoring and Routes Characterization

Infrastructure and traffic management technologies can have substantial impact on fuel use and emissions. This article explores a way to generate information about emissions and other route characteristics for drivers faced with a choice of routes. Global positioning system (GPS)-equipped vehicles were used to traverse various paths between origins and destinations to collect second-by-second trajectory data required for microscale emission analysis. A methodology based on the vehicle specific power (VSP) concept was used to estimate the emissions impact. On-board video footage recorded route features, traffic incidents, and congestion levels. Two different vehicles and drivers traversed several urban and intercity routes to enable the consideration of the influence of driver behavior and vehicle dynamics. It was found that the choice of a route can substantially affect emission rates of the analysed pollutants and that smoother driving styles can also result in considerable emissions reduction. A trade-off between reducing CO2/fuel consumption and local pollutants has been identified. Specifically, faster intercity routes are more desirable in terms of fuel use and CO2 emissions. However, these same routes yielded carbon monoxide, nitrous oxides, and hydrocarbons emission increases of up to 150%. These findings have implications for future investment and policy decisions regarding eco routing strategies.

[1]  Jinpeng Lv,et al.  Traffic Assignment Considering Air Quality , 2010 .

[2]  Asad J. Khattak,et al.  Modeling Revealed and Stated En-Route Travel Response to Advanced Traveler Information Systems , 1996 .

[3]  Bart van Arem,et al.  Eco-routing: Comparing the fuel consumption of different routes between an origin and destination using field test speed profiles and synthetic speed profiles , 2011, 2011 IEEE Forum on Integrated and Sustainable Transportation Systems.

[4]  David Gaker,et al.  Experimental Economics in Transportation , 2010 .

[5]  Gwo-Hshiung Tzeng,et al.  Using a weight-assessing model to identify route choice criteria and information effects , 2001 .

[6]  M. Ben-Akiva,et al.  Modeling Revealed and Stated Pretrip Travel Response to Advanced Traveler Information Systems , 1996 .

[7]  Margarida C. Coelho,et al.  Assessing methods for comparing emissions from gasoline and diesel light-duty vehicles based on microscale measurements , 2009 .

[8]  Laurence R. Rilett,et al.  Traffic assignment under environmental and equity objectives , 1994 .

[9]  Hesham Rakha,et al.  INTEGRATION Framework for Modeling Eco-routing Strategies: Logic and Preliminary Results , 2012 .

[10]  Jeffrey L. Adler,et al.  Investigating the learning effects of route guidance and traffic advisories on route choice behavior , 2001 .

[11]  Laurence R. Rilett,et al.  Equitable Traffic Assignment with Environmental Cost Functions , 1998 .

[12]  Britt A. Holmén,et al.  Evaluating the ability of global positioning system receivers to measure a real-world operating mode for emissions research , 2005 .

[13]  Hesham Rakha,et al.  The effects of route choice decisions on vehicle energy consumption and emissions , 2008 .

[14]  H. Frey,et al.  Fuel use and emissions comparisons for alternative routes, time of day, road grade, and vehicles based on in-use measurements. , 2008, Environmental science & technology.

[15]  Franklin Farell Roadmap to a Single European Transport Area: Towards a competitive and resource efficient transport system , 2014 .

[16]  Hesham Rakha,et al.  Energy and Environmental Impacts of Roadway Grades , 2006 .

[17]  Gwo-Hshiung Tzeng,et al.  Multiobjective decision making for traffic assignment , 1993 .

[18]  Ana L. C. Bazzan,et al.  Simulation Studies on Adaptive Route Decision and the Influence of Information on Commuter Scenarios , 2004, J. Intell. Transp. Syst..

[19]  Bin Ran,et al.  A Hybrid Tree Approach to Modeling Alternate Route Choice Behavior With Online Information , 2010, J. Intell. Transp. Syst..

[20]  Miguel Figliozzi Emissions Minimization Vehicle Routing Problem , 2010 .

[21]  Mohamed A. Abdel-Aty,et al.  Examination of Multiple Mode/Route-Choice Paradigms Under ATIS , 2006, IEEE Transactions on Intelligent Transportation Systems.

[22]  T. Gärling,et al.  Spatial Behavior in Transportation Modeling and Planning , 2001 .

[23]  Kanok Boriboonsomsin,et al.  Impacts of Road Grade on Fuel Consumption and Carbon Dioxide Emissions Evidenced by Use of Advanced Navigation Systems , 2009 .

[24]  Anna Nagurney,et al.  A MULTICLASS, MULTICRITERIA TRAFFIC NETWORK EQUILIBRIUM MODEL WITH ELASTIC DEMAND , 2002 .

[25]  Matthew J. Barth,et al.  Environmentally-Friendly Navigation , 2007, 2007 IEEE Intelligent Transportation Systems Conference.

[26]  Constantinos Antoniou,et al.  Development of a Mixed Multi-Nomial Logit Model to Capture the Impact of Information Systems on Travelers' Switching Behavior , 2007, J. Intell. Transp. Syst..

[27]  Hussein Dia,et al.  An agent-based approach to modelling driver route choice behaviour under the influence of real-time information , 2002 .

[28]  David M Levinson,et al.  Determinants of Route Choice and Value of Traveler Information , 2006 .

[29]  Stuart C Burgess,et al.  A parametric study of the energy demands of car transportation: a case study of two competing commuter routes in the UK , 2003 .

[30]  Xiaoliang Ma,et al.  Integration of emission and fuel consumption computing with traffic simulation using a distributed framework , 2009, 2009 12th International IEEE Conference on Intelligent Transportation Systems.

[31]  Carlos Borrego,et al.  Impact of land use on urban mobility patterns, emissions and air quality in a Portuguese medium-sized city. , 2011, The Science of the total environment.

[32]  Margaret O'Mahony,et al.  Mixed Stochastic User Equilibrium Behavior under Traveler Information Provision Services with Heterogeneous Multiclass, Multicriteria Decision Making , 2009, J. Intell. Transp. Syst..

[33]  José Luis Jiménez-Palacios,et al.  Understanding and quantifying motor vehicle emissions with vehicle specific power and TILDAS remote sensing , 1999 .

[34]  M. Ben-Akiva,et al.  Cognitive cost in route choice with real-time information: An exploratory analysis , 2011 .

[35]  Karin Brundell-Freij,et al.  Optimizing route choice for lowest fuel consumption - Potential effects of a new driver support tool , 2006 .

[36]  Eran Ben-Elia,et al.  Which road do I take? A learning-based model of route-choice behavior with real-time information , 2010 .

[37]  Dominik Papinski,et al.  Exploring the route choice decision-making process: A comparison of planned and observed routes obtained using person-based GPS , 2009 .

[38]  Sushant Sharma,et al.  Optimal Emission Pricing Models for Containing Carbon Footprints Due to Vehicular Pollution in a City Network , 2011 .

[39]  A. Khattak,et al.  Comparative Analysis of Spatial Knowledge and En Route Diversion Behavior in Chicago and San Francisco: Implications for Advanced Traveler Information Systems , 1998 .

[40]  Anne Goodchild,et al.  Using a GIS-Based Emissions Minimization Vehicle Routing Problem with Time Windows (EVRPTW) Model to Evaluate CO2 Emissions and Cost Trade-offs in a Case Study of an Urban Delivery System , 2011 .

[41]  David Levinson,et al.  A Moment of Time: Reliability in Route Choice Using Stated Preference , 2010, J. Intell. Transp. Syst..

[42]  D. Niemeier,et al.  How Much Can Vehicle Emissions Be Reduced?: Exploratory Analysis of an Upper Boundary Using an Emissions-Optimized Trip Assignment , 2002 .

[43]  Kay W. Axhausen,et al.  Analysis of driver's response to real-time information in Switzerland , 2006 .