Identifying and Classifying Goods Vehicles

A BWIM system is capable of measuring the loading and spacing of a vehicle's axles; it is often desirable to use this information to identify the type of vehicle. By classifying vehicles we can infer useful data about their purposes and loads. For instance, by identifying concrete mixers and tipper trucks, we can resolve construction traffic from goods traffic. By identifying cars, tractors and buses, we can obtain a picture of the makeup of traffic accross the bridge, and its congestion patterns. By identifying the tractor unit and the class of iso-container we can estimate the goods load. Therefore, a system that can classify vehicles allows an informative economic analysis of bridge traffic.

In fact, there are many classification systems in use, these may differ because of their intended application or because of differing national standards. This document is intended to explain the main classification systems within the context of BWIM. We will discuss five systems, starting from the coarsest:

  • The legal definitions that hold within the European Economic Area
  • The system suggested for BWIM in the COST 323 guidelines
  • The 2003 Guide produced by the UK Department of Transport.
  • User defined systems
  • Advanced classification systems

All of these systems are defined in terms of weight or vehicle dimension, in the final section we shall define values for these parameters for typical vehicles.

1. EU Regulations
Class Designation Weight (T)
Medium Goods Vehicle (MGV) N1 3.5 to 7.5
Large Goods Vehicle (LGV or HGV) N2 7.5 to 12.0.
LGV (articulated) N3 16.5 to 44.0
Draw-bar 18.75.
Larger Heavier Vehicle (LHV) 44.0 to 75.0
1.1 Standard Containers in EU
Class Length (m) Width (m) Weight Empty (T) Weight Loaded (T)
20' 6.06 2.59 2.33 24.0
40' 12.2 2.59 4.0 30.48
45' HC 13.72 2.89 4.8 30.48
45' PW 13.72 2.59 4.8 30.48
48' HC 14.63 2.90
53' HC 16.15 2.90 5.0 30.48

2. COST Guidelines
The classification system adopted in COST 323 is designed specifically for BWIM systems
Category Description
1 Cars, vans, cars with trailers
2 2 Axle, rigid lorry
3 Rigid lorry, more than 2 axles
4. Tractor and semi-trailer with single or tandem axels
5. Tractor and semi-trailer with tridem axels
6. Lorry with trailer
7. Buses
8. Other vehicles
3. UK Department of Transport
Axles Description Weight (T)
2 Light Goods Vehicles < 3.5
2 Smaller lorries 3.5-7.5
2 Bigger lorries 7.5 to 18
3 Rigid 26
3 Articulated 26.0
4 Rigid 32.0
4 Articulated 38
4. Vehicle and draw bar trailer 36.0
5 or more. Articulated 40
5. Vehicle and draw bar trailer 40.0
6. Articulated 41.0
6. Draw-bar 41.0
5 or 6. Articulated 44.0
6. Draw-bar 44.0
6. Articulated 44.0
6. Draw-bar 44.0

4. User Specified

In some applications, clients wish to define their own classes. For instance, in a antural extension of the axle groups mentioned earlier, one client specified vehicle classes in terms of axle spacing distances. Other clients may wish to classify vehicles according to their gross weight, or their axle loading pattern.

Advanced Classification Systems

This section deals with classification systems that go beyond simply identifying the type of vehicle by its load pattern, and actually infer data about the quantity and nature of goods being transported. The data gleaned drom these inferences allow an economic analysis of the bridge trafffic. While the axle load pattern measured by BWIM is a core component of such a system is not always sufficient for the high specificity classifications required for economic analysis of traffic. For this reason we have developed a complementary measurement system that measures the silhoutte of the vehicle.
Economic Classes
  • Agricultural Tractors
  • Private cars
  • Small vans
  • Buses/coaches
  • Large vans
  • Small flatbed trucks
  • Large flatbed trucks.
  • Construction traffic
  • a. Tipper lorries
    b. Concrete mixers
  • Container traffic
  • Articulated lorry, non-container based.
  • Lumber transport
  • Tankers
  • Car transporters
  • Exceptional loads
We are currently working on systems that, together with iBWIM will be able to distinguish between these classes.