Article

Analysis of Route Choice Decisions by Long-Haul Truck Drivers

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Abstract

This study has done an empirical analysis of long-haul truck drivers' route choice decision making as they navigate the U.S. highway network. The most important factor that has been analyzed is how long-haul truck drivers trade off between distance and time when faced with multiple routes. From information gathered from a revealed preference data set consisting of about 250,000 trucks over a 13-day period, a logistic model was constructed to describe route choice behavior when truck drivers are faced with alternate routes. The logistic model predicted the percentage of trucks that used the bypass route as a function of the perceived speed on the downtown route. The results of this study show that time is a significant factor in the decision-making process.

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... Thus, a haulier will select a potentially longer, but more efficient route, if lower vehicle operating costs are available. Knorring et al. (2005). ...
... Income Knorring et al. (2005). ...
... Hazards avoided Knorring et al. (2005). ...
... Because of their possibility of occurring and potentially catastrophic nature, the associated risks turn to shape attitudes and actions of players concerned. The relationship between hazardous material transportation and risks has been theorized to take the form of 'absent' presence or fire space (Law and Mol, 2001). Law and Mol (2001) have argued that within a spatial setting, the risks posed by hazardous material transporting trucks are defined by their presence, their absence as well as a simultaneous absence and presence, hence the absent presence. ...
... The relationship between hazardous material transportation and risks has been theorized to take the form of 'absent' presence or fire space (Law and Mol, 2001). Law and Mol (2001) have argued that within a spatial setting, the risks posed by hazardous material transporting trucks are defined by their presence, their absence as well as a simultaneous absence and presence, hence the absent presence. To them, absent presence could be understood from the analogical point where fire is both present and absent at the same time: thus, in one vein it is visible, puts forth heat and light, and undeniably has and leaves behind material traces of its presence, but in the other vein it is not a stable object that can be pinned down at a specific place at a specific moment. ...
... However, they should be based on UN Model Regulations on the Transport of Dangerous Goods which present a scheme of provisions that allow uniform development of national and international regulations governing the various modes of transport (United Nations, 2015). A number of the well documented regulatory measures include driver training Kara and Verter, 2004); controlling driving hours (West Africa Trade Hub, 2010); container specifications (Berman et al., 2007;Kara and Verter, 2004); inspection stations to monitor compliance (Kara and Verter, 2004); toll policies (Marcotte et al., 2009); vehicle and container designs (Guo and Verma, 2010); and route selection (Erkut and Alp, 2007;Knorring et al., 2005;Kara and Verter, 2004). Despite these interventions, there are considerable threats to humans in the transportation of hazmats, especially in developing countries where compliance to regulations and standards have been far from satisfactory. ...
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This study estimates population exposure risks associated with the transportation of hazardous materials using the Accra – Kumasi Highway (N6) in Ghana as a case corridor. Using the mixed methods approach which resulted in collecting both qualitative and quantitative data from transport operators and relevant agencies, the paper estimates that accident probabilities were observed to be high on relatively longer sections of the road (those over 50 km) as there are few speed control measures to check over speeding. It was also found that the risk of a single shipment of a hazardous material was 0.09144 inhabitants per vehicle/km, implying approximately 1464 inhabitants stand a risk of either being killed or injured over the entire 293.3 km stretch of the N6. The paper recommends the use of multiple risk prevention measures by all drivers as it has been shown in the study results that truck operators who combined at least three measures were those who had not been involved in accidents in the last ten years.
... Only few behavioural studies on route choice decision-making of truck drivers can be found in the existing literature. Empirical studies by Kawamura (2002), Knorring et al. (2005) and Vadali et al. (2009 consider the trade-off behaviour of truck drivers among distances, times and/or toll costs when faced with multiple routes. Road accessibility factors have not received much attention in quantitative research to date. ...
... Only few behavioural studies on route choice decision-making of truck drivers can be found in the existing literature. Empirical studies by Kawamura (2002), Knorring et al. (2005) and Vadali et al. (2009 consider the trade-off behaviour of truck drivers among distances, times and/or toll costs when faced with multiple routes. Road accessibility factors have not received much attention in quantitative research to date. ...
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In this paper, we report the results of a stated choice experiment, which was conducted to examine truck drivers’ route choice behavior. Of particular interest are the questions (i) what is the relative importance of road accessibility considerations via-a-vis traditional factors influencing route choice behavior, (ii) what are the influences of particular personal and situational variables on the evaluation of route attributes, (iii) how sensitive are truck drivers for possible pricing policies, and (iv) is there a difference in impact if environmental concerns are framed as a bonus or as a pricing instrument. The main findings indicate that road accessibility characteristics have a substantial impact on route preferences which is of the same order of magnitude as variation in travel times. This suggests that provision of adequate travel information in itself can be an effective instrument to prevent negative externalities of good transport associated with shortest routes. Furthermore, the results indicate that truck drivers/route planners when choosing a route are relatively sensitive to road pricing schemes and rather insensitive to environmental bonuses.
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This research develops a gravity-based index of public school competition from private schools within local markets. Proponents of educational reform often call for policies to increase competition between schools. A major hurdle for researchers examining this issue is to determine a workable definition of “competition” by which they can measure the degree of competition within local markets. This study addresses this challenge by developing a school competition index for public schools in the Jackson metropolitan area of Mississippi, USA that considers the enrollments in public schools and the enrollments in their neighboring private schools, as well as the distances between them. The school competition index reveals the degree of competition for each public school based on its spatial location relative to peer private schools operating within its service area. This methodology can be useful for evaluating competition in other markets and redefining the traditional market structure.
... The odds ratio showed that the expected change in the 41 odds of selecting the north route increased 1 percent when the north route became less reliable. 42 As shown in Table 2, the correlation between TTIRATIO and PTIRATIO was 0.52. Even this is 43 not a very large correlation value; with a large dataset and a binary response, the correlation 44 between these two variables could lead to questionable results. ...
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This study represents the first research to investigate the impacts of two critical determinants—level of congestion and travel time reliability—on routing decisions with two groups of truck drivers having different levels of awareness of the real-time and the historical traffic conditions on available routes. The research analyzed 14,538 global positioning system devices recording trips on the I-495 crossing through Maryland, Virginia, and Washington, DC, and 2,166 trips in the Dallas area, to explore how truck drivers make routing decisions based on real-time travel time and reliability information by applying a binary logistic regression model. Researchers found that for truck drivers who are not familiar with the historical traffic and travel time conditions on available routes, real-time congestion information is a significant factor in their routing decision-making process, while travel time reliability is not a major consideration. For frequent truck drivers who are familiar with the historical traffic and travel time conditions on available routes, travel time reliability is a significant factor in their routing decision-making process, and traffic congestion information is not a significant factor. These results bring more accuracy to travel time prediction and provide valuable insights into traffic management and reliability performance measures. Moreover, this research provides statistical evidence proving the potential value of delivering travel time reliability information to drivers, traffic management agencies, and navigation map developers.
... When accounting for the schedule delay, the travel time itself was not significant in predicting route choices. Knorring et al. (2005) found that long-haul truckers are willing to trade an increase of 1% in their travel distance for a speed gain of 0.4 mph in situations in which they have a choice between a route passing through a metropolitan area and a bypass route. Hyodo and Hagino (2010) found an effect for the road type, in addition to tolls and travel times, on truck route choices in Japan. ...
... Hagino et al. (2010) used records of traffic permit applications submitted by drivers. Knorring et al. (2005) collected GPS traces using in-truck systems. However, both studies suffer from substantial limitations: they do not collect any information about the shipments or the drivers. ...
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This paper reports on tools, methods and experimental designs that have been developed to study the routing behavior and movement of trucks. The application of these capabilities is demonstrated with a case study on the route choices of North American intercity truck drivers’, with a focus on the choice between tolled and free roads. An extension to the urban freight context, currently ongoing in Singapore, is briefly discussed, highlighting the challenges and main differences compared to the intercity case.
... ata and photos respectively as the possible predicting route. Various aspects have also been considered in travel behavior analysis. From the research of Li et al. (2013), route choice behavior changes relating to the familiarity to OD pairs while Lanser et al. (2005) focused on overlap in multimodal transport networks using the path size modeling. Knorring et al. (2005) had an empirical analysis of long-haul truck drivers, with the result showing that time is a significant factor in the decision-making process and Spissu et al. (2011) proved that higher levels of intra-individual variability were found for discretionary trips, whereas higher levels of inter-individual variability, as well as greater de ...
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The lack of sufficient data is the result of the inherent complexity of gathering and subsequently analyzing route choice behavior, which unfortunately hasn't been revealed much by existing literatures. With the assistance of GIS technology and taxi-based floating car data, the authors found that the majority of urban drivers would not travel along the shortest or the fastest paths. This paper studies the factors that influence commuters' route choice and route switching based on objective real-world observations of travel behavior. Possible factors that may affect driver's route choice are then analyzed and regression methods were introduced to attain if there existing a clear quantitative relationship between drivers' route choice and these factors. The result indicates that such connection is difficult to be established. Consequently, eight scenarios were proposed to quantify the influence of various potential factors. Analysis shows that travel distance, travel time and road preference have comparable higher influence on drivers' route choice. To this end, a new route prediction model is proposed, adopting the road usage as the weight and the shortest route's length and the fastest route's time as the constraints. The proposed model was implemented and validated using the FCD data of Shenzhen, China. The results indicate that by combining the external influence with the driver's personal preference, the predicted travel route has a higher matching ratio with the actual one, which consequently indicates the effectiveness of the model.
... The raw GPS traces were map-matched to a high-resolution transportation network to derive more than 225,000 truck trips and their routes for use in this analysis. Given that the majority of route choice studies, other than a few exceptions (Arentze et al., 2012;Feng et al., 2013;Hess et al., 2015;Knorring et al., 2005), are in the context of passenger car or bicycle route choice, this study contributes to a currently small body of literature on generating route choice sets for modeling freight truck route choice. ...
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Thesis
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Thesis
Understanding truck drivers’ routing selection behavior according to congestion level, travel time reliability, and other factors can not only help transportation agencies improve the efficiency of traffic management but also increase the accuracy of travel time predictions. However, most of the existing studies on this subject used nonempirical methods such as stated preference, experimental, and theoretical modeling and simulations because real field data were not available. This research analyzes 17,024 observed trips on I-495 crossing through Maryland, Virginia, and Washington, D.C., to explore how truck drivers make routing decisions based on real-time congestion information, travel time reliability, and other factors such as rush hour and day of the week. The east loop of I-495 is defined as the east route, and the north loop is defined as the north route. The results show that the odds of selecting the north route significantly decrease if the travel time index ratio between the north route and east route increases. The research also demonstrates that the planning time index ratio has a significant impact on routing selection. Also, freight drivers’ routing decisions are influenced differently by factors such as morning rush hour, afternoon rush hour, and whether it is a weekday or weekend. A similarly detailed aggregate freight dataset from the Dallas–Fort Worth area validates the results from the Maryland dataset.
Thesis
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