International Choice Modelling Conference, International Choice Modelling Conference 2017

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Factors affecting Interurban Freight Route Choice – Perspectives from Freight Forwarders and Truck Drivers
Athena Tsirimpa, Ioannis Tsouros

Last modified: 28 March 2017

Abstract


The ongoing globalization, the volatile economic environment and the growing need for flexible and reliable movement of goods have made freight transport to gain more attention both in corporate strategies and policy-wise.  This paper aims to understand and quantify the factors affecting interurban route choice, while exploring the effect that different incentives for the use of toll road alternatives, such as dedicated lane for trucks, higher speed limits, etc., may have on the decision-making process. A latent class route choice model is under development also capturing the importance that decision makers place on specific incentives.

A case study is presented using data from a survey that took place in 2016 in Portugal. According to Eurostat data, Portugal is one of the EU countries with more highway kilometers per millions of inhabitants (5th in the EU). However, the dense (34km/1000km2) and  high-quality network is clearly underused, with average annual daily traffic lower than 10.000 vehicles/day. The significant majority of the network is tolled. Latest developments led the Portuguese government to make some adjustments to the toll prices respective to purchase power and accessibility.

The questionnaire is addressed to operators and drivers. There is a similar approach for each group with the same stated preference experiment. The survey was available in paper and electronic format and included both revealed and stated preference data. Two questionnaires have been developed, one for freight operators and one for truck drivers, in order to: (a) obtain information on decision maker’s characteristics, (b) examine typical travel patterns followed (commodities transported, routes followed, etc.); and (c) examine the factors affecting route choice (e.g., toll road vs free road) using a stated preference experiment. In the latter, respondents were presented with two route alternatives for a future truck trip and they were asked to choose the one that they prefer most. The first route uses a toll road, while the second route uses a free road. A total of 10 scenarios, 2 for each one of the five different OD pairs, were presented to the freight operators. For each route alternative, maps were used, graphically representing the respective path from origin to destination. The attributes used in the SP experiment were: (a) total travel time from origin to destination; (b) Fuel cost (in Euros); (c) Projected Toll Cost provided by Toll Road Operator (in Euros); and (d) a number of incentives provided by the toll road, such as existence of dedicated truck lane; additional discounts for frequent users of the toll road on toll price and/or fuel; higher speed limits; overweight bypass; and rest area for the truck drivers.

The collected data so far includes 15 freight operators and more than 60 drivers. The average fleet is 28 trucks and the vast majority (75%) of freight operators’ trucks fleet is truckload, while the remaining are frequently parcels/express. Respondents replied that most of the times the decision for the route choice is either made compulsory by the operator – a single route that every driver should follow or decided by the driver (choice from a list of different options). Also, the majority of the respondents said that they decide for the route a day before the trip and the remaining the same day. Only a small percentage (10%) respondent that the routes are decided a long time before the trip. Finally, in the case of late delivery half of the respondents will have to pay an indirect cost or SLA impact while the other half will have a direct cost for each delay. The discount of fuel price was found to be the most attractive incentive followed by off-peak toll discounts and rest area for drivers, while the existence of a dedicated truck lane was found to be the most efficient incentive in the model estimation, increasing the probability of choosing the toll road alternative.

Preliminary model estimation results indicate that apart from the usual trade-off between travel time and travel cost, incentives play an active role in the final decision of route. The role of the incentives is furtherly explored by using the latent class choice methodology. The methodology allows for a user segmentation based on the preferability or the familiarity of certain incentives. For example, users that are more sensitive to incentives such as fuel or toll discounts are grouped as price sensitive/financially motivated. Other classifications may include safety oriented, comfort-oriented or speed/reliability oriented users. For each different user class, a class specific utility function is formed and a different probability of choosing the toll road is calculated.

The model estimation results, the different latent user classes along with the class-specific values of time are valuable both for policy makers and for the industry as it can among other results, assess the importance of various incentives towards the direction of traffic towards the underused toll roads which will lead to a more balanced traffic assignment and a better overall system performance.

 


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