Professional Pilot Transumo IV - Study on a Safest-route Functionality with Financial Incentive for Professional Drivers
report
The main objective of the Transumo project Intelligent Vehicles was to use in-vehicle telematics as a breakthrough technology to improve the quality of travel and sustainable road traffic and to appreciate the potential of in-car telematics in terms of safety, throughput, reliability and environment. The subproject "Professional Pilot" is performed within the framework of the Intelligent Vehicles Transumo project. The aim of this pilot was to influence the route choice behaviour of professional drivers by providing a financial incentive for following a safest route. The pilot addressed how this goal can be achieved. In the literature review it was concluded that the relationship between route choice and safety is not often described. One study was found, were the focus was on private drivers instead of professional drivers. Therefore, the concept of influencing the route choice to a safest route for professional drivers appeared to be new. For the theoretical and practical implementation, two different components have been explored. Firstly, a general model for the incentive program was proposed.
This conceptual model was used as a basis for two studies conducted within this research. Secondly, a safest route algorithm was developed and described. In the literature, one can find algorithms to determine a fastest route or shortest route. However, ready-to-use algorithms for a safest route were not available. Therefore,
a safest route algorithm was developed based on existing ‘Duurzaam-Veilig (Sustainable Safety)’ criteria. Besides the exploration, three studies have been undertaken in this part of the Transumo project Intelligent Vehicles. The first study was undertaken to assess the drivers’ response to incentives and thereby the potential benefit of safest routes advice with incentive. This study introduced a route-based incentive program operated by a logistic company together with an insurance company. In total 45 Dutch professional drivers participated in a survey about expected behaviour in case of a rewarding scheme for safest routes as implemented in the professional pilot, as preparation of participation in the professional pilot. The results showed that drivers tend to ignore safety-related information in making their route choices; however, the incentives had a significant effect on these choices. The incentives therefore seem to present an efficient way of influencing drivers’ route choices. The online survey used in this study is a stated preference technique to investigate driver behaviour in future situations. When the incentive program is put into practice, the actual driver behaviour (i.e. revealed preference) may differ. The second study, the main part of this Transumo subproject, was conducted to determine the revealed preference, i.e., whether incentives have a significant effect on the route choice in practice. During the Field Operational Test, which lasted for
2 months, the driving behaviour and route-choice of professional drivers were unobtrusively measured. The vehicles were equipped with a navigation system, which could generate a fastest and a safest route to a given destination. After one month,
the participants were also rewarded when they drove the safest route. The used route algorithms have been compared for a sample of origin-destination points taken from the field operational test. In the comparison between the resulting safest and fastest route,
it was found that in 78% of the cases the trips were equal. This result is an important requirement for the sustainable safety principle were one is aiming at both safest routes and fastest routes. For the remaining 22% of the cases, there were differences between the fastest and safest routes. The travelled distance for the safest route was longer compared to the fastest route. The differences were caused by an increase of travelled distance on motorways and access roads. The FOT did not show a positive effect on the use of an incentive as was hypothesised. There are many possible causes that could have an influence on the result found. The main point was that both systems differed with respect to functionality and usability, e.g. the time to generate a safest route took significant longer compared to the calculation time for a fastest route.
In addition, due to various technological set-backs, the measuring period of the pilot was reduced several times. Because of the reduced measurement period, it is possible that an existing effect was not found. The third study was performed to assess the probability that public authorities, automotive industry and insurance companies are going to apply certain deployment options to influence the user to buy Advanced Driver Assistance Systems (ADAS),
and the probability that users will buy an ADAS given these deployment options.
To this end, an actor and user survey were held, using the stated preference methodology, to estimate models of actor and user decision making. To the actor survey, 75 reactions were received of which 72 were usable, and to the user survey
250 reactions were received. Three different Advanced Driver Assistance Systems (ADAS) were considered (for each of which it was expected that another actor would take the lead in deployment) and three deployment options were included for each actor (do nothing, stimulate or enforce). The different ADAS generally did not significantly influence the probability that actors will apply a certain deployment option.
The deployment options itself and to a lesser extent, the deployment options of other actors were most important for the probability that actors will apply deployment options. The probability that users choose to buy an ADAS was found to be highly dependent upon financial incentives. In summary: A safest route algorithm is developed and implemented. This algorithm is successfully validated. In a survey drivers indicated a willingness to choose a safer route if a reward was given. Unfortunately, the field trial did not provide sufficient evidence that drivers actually drive this safer route. It is also uncertain whether the government or insurance companies are willing to provide incentives.
This conceptual model was used as a basis for two studies conducted within this research. Secondly, a safest route algorithm was developed and described. In the literature, one can find algorithms to determine a fastest route or shortest route. However, ready-to-use algorithms for a safest route were not available. Therefore,
a safest route algorithm was developed based on existing ‘Duurzaam-Veilig (Sustainable Safety)’ criteria. Besides the exploration, three studies have been undertaken in this part of the Transumo project Intelligent Vehicles. The first study was undertaken to assess the drivers’ response to incentives and thereby the potential benefit of safest routes advice with incentive. This study introduced a route-based incentive program operated by a logistic company together with an insurance company. In total 45 Dutch professional drivers participated in a survey about expected behaviour in case of a rewarding scheme for safest routes as implemented in the professional pilot, as preparation of participation in the professional pilot. The results showed that drivers tend to ignore safety-related information in making their route choices; however, the incentives had a significant effect on these choices. The incentives therefore seem to present an efficient way of influencing drivers’ route choices. The online survey used in this study is a stated preference technique to investigate driver behaviour in future situations. When the incentive program is put into practice, the actual driver behaviour (i.e. revealed preference) may differ. The second study, the main part of this Transumo subproject, was conducted to determine the revealed preference, i.e., whether incentives have a significant effect on the route choice in practice. During the Field Operational Test, which lasted for
2 months, the driving behaviour and route-choice of professional drivers were unobtrusively measured. The vehicles were equipped with a navigation system, which could generate a fastest and a safest route to a given destination. After one month,
the participants were also rewarded when they drove the safest route. The used route algorithms have been compared for a sample of origin-destination points taken from the field operational test. In the comparison between the resulting safest and fastest route,
it was found that in 78% of the cases the trips were equal. This result is an important requirement for the sustainable safety principle were one is aiming at both safest routes and fastest routes. For the remaining 22% of the cases, there were differences between the fastest and safest routes. The travelled distance for the safest route was longer compared to the fastest route. The differences were caused by an increase of travelled distance on motorways and access roads. The FOT did not show a positive effect on the use of an incentive as was hypothesised. There are many possible causes that could have an influence on the result found. The main point was that both systems differed with respect to functionality and usability, e.g. the time to generate a safest route took significant longer compared to the calculation time for a fastest route.
In addition, due to various technological set-backs, the measuring period of the pilot was reduced several times. Because of the reduced measurement period, it is possible that an existing effect was not found. The third study was performed to assess the probability that public authorities, automotive industry and insurance companies are going to apply certain deployment options to influence the user to buy Advanced Driver Assistance Systems (ADAS),
and the probability that users will buy an ADAS given these deployment options.
To this end, an actor and user survey were held, using the stated preference methodology, to estimate models of actor and user decision making. To the actor survey, 75 reactions were received of which 72 were usable, and to the user survey
250 reactions were received. Three different Advanced Driver Assistance Systems (ADAS) were considered (for each of which it was expected that another actor would take the lead in deployment) and three deployment options were included for each actor (do nothing, stimulate or enforce). The different ADAS generally did not significantly influence the probability that actors will apply a certain deployment option.
The deployment options itself and to a lesser extent, the deployment options of other actors were most important for the probability that actors will apply deployment options. The probability that users choose to buy an ADAS was found to be highly dependent upon financial incentives. In summary: A safest route algorithm is developed and implemented. This algorithm is successfully validated. In a survey drivers indicated a willingness to choose a safer route if a reward was given. Unfortunately, the field trial did not provide sufficient evidence that drivers actually drive this safer route. It is also uncertain whether the government or insurance companies are willing to provide incentives.
TNO Identifier
364535
Publisher
TNO
Collation
79 p.
Place of publication
Soesterberg