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Disaggregate Modelling for Estimating Location Choice of Safe and Secure Truck Parking Areas: A Case Study
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Responding to the increasing need for safety and security in road freight transport, and to targeted legislation specifying the availability of freight drivers’ rest areas, this paper proposes a plan and a model for deployment of safe and secure parking areas for truck drivers. Disaggregate analysis within a stated preference and conjoint analysis framework leads to the modelling of truck parking area selection by each truck driver that registers in the system proposed in this research. The concept builds upon the Cooperative Intelligent Transport Systems (C-ITS) upgrading of the Trans-European Transport Network (TEN-T) infrastructure systems while adapting to novel transport and logistics needs in an operationally safe, secure, and efficient environment for the supply chain. The analysis is applied in the Orient/East-Med Corridor of the TEN-T and is supported by the clustering of available truck parking areas for each truck route in the application subnetwork. The personalised approach is scalable and can be integrated into platforms for safe and secure truck parking areas, thus facilitating their acceptance and increasing awareness by the end-users. From pilot implementation on the Hellenic motorways, functional evaluation of use cases indicates 94.4% estimated choice probability of the most suitable parking area by the pilot drivers.
Title: Disaggregate Modelling for Estimating Location Choice of Safe and Secure Truck Parking Areas: A Case Study
Description:
Responding to the increasing need for safety and security in road freight transport, and to targeted legislation specifying the availability of freight drivers’ rest areas, this paper proposes a plan and a model for deployment of safe and secure parking areas for truck drivers.
Disaggregate analysis within a stated preference and conjoint analysis framework leads to the modelling of truck parking area selection by each truck driver that registers in the system proposed in this research.
The concept builds upon the Cooperative Intelligent Transport Systems (C-ITS) upgrading of the Trans-European Transport Network (TEN-T) infrastructure systems while adapting to novel transport and logistics needs in an operationally safe, secure, and efficient environment for the supply chain.
The analysis is applied in the Orient/East-Med Corridor of the TEN-T and is supported by the clustering of available truck parking areas for each truck route in the application subnetwork.
The personalised approach is scalable and can be integrated into platforms for safe and secure truck parking areas, thus facilitating their acceptance and increasing awareness by the end-users.
From pilot implementation on the Hellenic motorways, functional evaluation of use cases indicates 94.
4% estimated choice probability of the most suitable parking area by the pilot drivers.
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